Study of DiMuon Rare Beauty Decays with ATLAS and CMS

The LHC experiments will perform sensitive tests of physics beyond the Standard Model (BSM). The investigation of decays of beauty hadrons represents an alternative approach in addition to direct BSM searches. The ATLAS and CMS efforts concentrate on those B-decays that can be efficiently selected already at the first and second level trigger. The most favorable trigger signature will be for $B$-hadron decays with muons in the final state. Using this trigger, ATLAS and CMS will be able to accommodate unprecedentedly high statistics in the rare decay sector. These are purely dimuon decays, and families of semimuonic exclusive channels. Already with data corresponding to an integrated luminosity of \ensuremath{1 fb^{-1}}, the sensitivity in the dimuon channels will be comparable to present measurements (world average). The strategy is to carry on the dimuon channel program up to nominal LHC luminosity. In particular the \ensuremath{B_s \to \mu\mu} signal with \ensuremath{\sim}5 sigma significance can be measured combining low luminosity \ensuremath{10^{33}cm^{-2} s^{-1}} samples with those of one year of LHC operation at a luminosity of \ensuremath{10^{34}cm^{-2} s^{-1}Comment: Submitted for the SUSY07 proceedings, 4 pages, 2 figures, 4 table

How Would You Like Your Eggs: A History of U.S. Egg Regulation and Current Controversies

Government regulatory efforts concerning eggs are in the news due to a serious salmonella outbreak during the summer of 2010. Given the widespread concern this outbreak raised, there are already anecdotal reports of a negative impact on egg demand. This paper attempts to look at one aspect of eggs as a food commodity: the legal regime that regulates eggs as an item in the food supply. First, it will attempt an initial historical exploration of egg regulation in the 20th century. A web of different legal authorities sometimes seem to run overlapping circles around each other. The paper will address recent significant changes in egg safety regulation, driven mostly by the Food and Drug Administration and legislative changes to the overall food safety system. It will close by reviewing the recent salmonella enteritidis scare and possible future changes in the egg regulation system

Examining epigenetic variation in the brain in mental illness

Mental health represents one of the most significant and increasing burdens to global public health. Depression and schizophrenia, among other mental illnesses, constitute strong risk factors for suicidality which results in over 800,000 deaths every year. The majority of suicides worldwide are indeed related to psychiatric diseases. A growing body of genetic, epigenetic and epidemiological evidence suggests that psychiatric disorders are highly complex phenotypes originating from the multilevel interplay between the strong genetic component and a range of environmental and psychosocial factors. Deeper understanding about the biology of the genome has led to increased interest for the role of non-sequence-based variation in the etiology of neuropsychiatric phenotypes, including suicidality. Epigenetic alterations and gene expression dysregulation have been repetitively reported in post-mortem brain of individuals who died by suicide. To date, however, studies characterizing disease-associated methylomic and transcriptomic variation in the brain have been limited by screening performed in bulk tissue and by the assessment of a single marker at a time. The main aim of this thesis was to investigate DNA methylation and miRNA expression differences in post-mortem brain associated with suicidality and unravel the complexity of epigenetic signals in a heterogeneous tissue like the human brain by developing a method to profile genomic variation at the resolution of individual neural cell types. The results here reported, provide further support for a suicide-specific epigenetic signature, independent from comorbidity with other psychiatric phenotypes, as well as confirming the strong bias perpetrated by bulk tissue studies hence the need to examine genomic variations in purified cell types. In summary, this thesis has identified a) a suicide-specific signal in two different epigenetic markers (DNA methylation and miRNA expression) and b) a protocol to simultaneously profile DNA methylation levels across three purified cell types in the healthy brain highlighting the utility of cell sorting for identifying cell type-driven epigenetic differences associated with etiological variation in complex psychiatric phenotypes.1) ARUK-PPG2018A-010 – “Developing approaches to address neural cell heterogeneity in genomic studies of Alzheimer's disease”. 2) SBF001\1011 - “Using functional epigenomics to dissect the molecular architecture of schizophrenia

Searches for long-lived particles with the ATLAS detector at the LHC

Data taken in 2011 with the ATLAS detector at the Large Hadron Collider have been used to search for physics beyond the Standard Model. Results are presented based on luminosities between 2 and 5 fb−1 of √�(s) = 7TeV protonproton collisions focusing on final states with long-lived particles. No evidence of new physics is found

Search for long-lived neutral particles in ATLAS detector

A number of extensions of the Standard Model results in particles that are neutral, weakly coupled and have macroscopic decay lengths comparable with LHC detector dimensions. In the Hidden Valley (HV) models long-lived neutral particles that decay to heavy flavors or pairs of boosted leptons (lepton-jets) can be produced in SUSY processes, Z' decays and Higgs boson decays. Results are presented of a study of the ATLAS Detector performance for the Higgs decays h0 → π0vπ0v → b¯bb¯ b, and h0 → π0vπ0v → UUUU → 4(l+l−), where both π0v and U are neutral and can have a displaced decay. Triggers for processes with such nonstandard signatures have been developed and are now included in the trigger menu for data taking

Propaganda Use by the Union and Confederacy in Great Britain during the American Civil War, 1861-1862

At the beginning of the American Civil War, the United States (the Union) already had international diplomatic status, whereas the Confederate States of America wanted foreign recognition of its independence. The two governments sent agents and propagandists across the Atlantic, in particular to Great Britain to support their objectives. The Confederacy and the Union used various avenues, including rallies, talking with members of Parliament, and publications to convince the British that supporting the Confederacy was the correct action to take. The Union\u27s most well-known weapon emerged in January 1863: the Emancipation Proclamation. From the moment President Abraham Lincoln announced in September 1862 that he would emancipate slaves in the rebelling states, the nature of the American Civil War as viewed by the British changed. It could no longer be viewed simply as a war for southern independence, for it became more explicitly about the maintenance or abolition of slavery. For the British, slavery was a moral issue that they would never countenance

B+B^+ semileptonic rare decays in ATLAS

We discuss the latest studies on rare semileptonic decays of $B^+$ meson with the ATLAS detector

Rare semileptonic beauty decays in ATLAS

We discuss the latest studies on rare semileptonic decays of $B$-mesons and $\Lambda_b$ at the ATLAS detector

GAMoN: Discovering M-of-N{¬,∨} hypotheses for text classification by a lattice-based Genetic Algorithm

AbstractWhile there has been a long history of rule-based text classifiers, to the best of our knowledge no M-of-N-based approach for text categorization has so far been proposed. In this paper we argue that M-of-N hypotheses are particularly suitable to model the text classification task because of the so-called “family resemblance” metaphor: “the members (i.e., documents) of a family (i.e., category) share some small number of features, yet there is no common feature among all of them. Nevertheless, they resemble each other”. Starting from this conjecture, we provide a sound extension of the M-of-N approach with negation and disjunction, called M-of-N{¬,∨}, which enables to best fit the true structure of the data. Based on a thorough theoretical study, we show that the M-of-N{¬,∨} hypothesis space has two partial orders that form complete lattices.GAMoN is the task-specific Genetic Algorithm (GA) which, by exploiting the lattice-based structure of the hypothesis space, efficiently induces accurate M-of-N{¬,∨} hypotheses.Benchmarking was performed over 13 real-world text data sets, by using four rule induction algorithms: two GAs, namely, BioHEL and OlexGA, and two non-evolutionary algorithms, namely, C4.5 and Ripper. Further, we included in our study linear SVM, as it is reported to be among the best methods for text categorization. Experimental results demonstrate that GAMoN delivers state-of-the-art classification performance, providing a good balance between accuracy and model complexity. Further, they show that GAMoN can scale up to large and realistic real-world domains better than both C4.5 and Ripper

Bulk Analysis of Malicious PDF Documents

From 2007 onward, the PDF document has proven to be a successful vector for malware infections, making up 80% of all exploits found by Cisco ScanSafe in 2009 [1]. Creating new PDF documents is very easy and the volume of PDF documents identified as malicious has grown beyond the capabilities of security researchers to analyze by hand. The solution proposed by this thesis is to automatically extract features from the PDF documents to group and classify them, so that similar malware may be identified without manual analysis, thus reducing the workload of the malware analyst. These features may also be studied to identify trends within the PDF documents, such as similar exploits or obfuscation techniques. Our results show that the object graph structure of the PDF document is an effective way to create an initial grouping of malicious PDF documents. Finding similarities in PDF documents reveals further information about a data set. In our first case study, we examine the entire data set to identify large groups of similar PDF documents and make conjectures about their origins. In our second case study, we use a PDF document of known origin to find similar PDF documents within a data set. Through the two case studies, we were able to identify 50.3% of our data set with very little manual analysis of the malicious PDF documents