26 resultados para Affective Events Theory


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An analysis is presented of events containing jets including at least one b-tagged jet, sizeable missing transverse momentum, and at least two leptons including a pair of the same electric charge, with the scalar sum of the jet and lepton transverse momenta being large. A data sample with an integrated luminosity of 20.3 fb−1 of pp collisions at s√=8 TeV recorded by the ATLAS detector at the Large Hadron Collider is used. Standard Model processes rarely produce these final states, but there are several models of physics beyond the Standard Model that predict an enhanced rate of production of such events; the ones considered here are production of vector-like quarks, enhanced four-top-quark production, pair production of chiral b′-quarks, and production of two positively charged top quarks. Eleven signal regions are defined; subsets of these regions are combined when searching for each class of models. In the three signal regions primarily sensitive to positively charged top quark pair production, the data yield is consistent with the background expectation. There are more data events than expected from background in the set of eight signal regions defined for searching for vector-like quarks and chiral b′-quarks, but the significance of the discrepancy is less than two standard deviations. The discrepancy reaches 2.5 standard deviations in the set of five signal regions defined for searching for four-top-quark production. The results are used to set 95% CL limits on various models.

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A search for new particles that decay into top quark pairs is reported. The search is performed with the ATLAS experiment at the LHC using an integrated luminosity of 20.3 fb−1 of proton-proton collision data collected at a centre-of-mass energy of s√=8 TeV. The lepton-plus-jets final state is used, where the top pair decays to W+bW−b¯¯, with one W boson decaying leptonically and the other hadronically. The invariant mass spectrum of top quark pairs is examined for local excesses or deficits that are inconsistent with the Standard Model predictions. No evidence for a top quark pair resonance is found, and 95% confidence-level limits on the production rate are determined for massive states in benchmark models. The upper limits on the cross-section times branching ratio of a narrow Z′ boson decaying to top pairs range from 4.2 pb to 0.03 pb for resonance masses from 0.4 TeV to 3.0 TeV. A narrow leptophobic topcolour Z′ boson with mass below 1.8 TeV is excluded. Upper limits are set on the cross-section times branching ratio for a broad colour-octet resonance with Γ/m = 15% decaying to tt¯. These range from 4.8 pb to 0.03 pb for masses from 0.4 TeV to 3.0 TeV. A Kaluza-Klein excitation of the gluon in a Randall-Sundrum model is excluded for masses below 2.2 TeV.

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A generic search for anomalous production of events with at least three charged leptons is presented. The data sample consists of pp collisions at s√=8 TeV collected in 2012 by the ATLAS experiment at the CERN Large Hadron Collider, and corresponds to an integrated luminosity of 20.3 fb−1. Events are required to have at least three selected lepton candidates, at least two of which must be electrons or muons, while the third may be a hadronically decaying tau. Selected events are categorized based on their lepton flavour content and signal regions are constructed using several kinematic variables of interest. No significant deviations from Standard Model predictions are observed. Model-independent upper limits on contributions from beyond the Standard Model phenomena are provided for each signal region, along with prescription to re-interpret the limits for any model. Constraints are also placed on models predicting doubly charged Higgs bosons and excited leptons. For doubly charged Higgs bosons decaying to eτ or μτ, lower limits on the mass are set at 400 GeV at 95% confidence level. For excited leptons, constraints are provided as functions of both the mass of the excited state and the compositeness scale Λ, with the strongest mass constraints arising in regions where the mass equals Λ. In such scenarios, lower mass limits are set at 3.0 TeV for excited electrons and muons, 2.5 TeV for excited taus, and 1.6 TeV for every excited-neutrino flavour.

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The distribution and orientation of energy inside jets is predicted to be an experimental handle on colour connections between the hard--scatter quarks and gluons initiating the jets. This Letter presents a measurement of the distribution of one such variable, the jet pull angle. The pull angle is measured for jets produced in tt¯ events with one W boson decaying leptonically and the other decaying to jets using 20.3 fb−1 of data recorded with the ATLAS detector at a centre--of--mass energy of s√=8 TeV at the LHC. The jet pull angle distribution is corrected for detector resolution and acceptance effects and is compared to various models.

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Results of a search for new phenomena in events with large missing transverse momentum and a Higgs boson decaying to two photons are reported. Data from proton--proton collisions at a center-of-mass energy of 8 TeV and corresponding to an integrated luminosity of 20.3 fb−1 have been collected with the ATLAS detector at the LHC. The observed data are well described by the expected Standard Model backgrounds. Upper limits on the cross section of events with large missing transverse momentum and a Higgs boson candidate are also placed. Exclusion limits are presented for models of physics beyond the Standard Model featuring dark-matter candidates.

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We study the low frequency absorption cross section of spherically symmetric nonextremal d-dimensional black holes. In the presence of α′ corrections, this quantity must have an explicit dependence on the Hawking temperature of the form 1/TH. This property of the low frequency absorption cross section is shared by the D1-D5 system from type IIB superstring theory already at the classical level, without α′ corrections. We apply our formula to the simplest example, the classical d-dimensional Reissner-Nordstr¨om solution, checking that the obtained formula for the cross section has a smooth extremal limit. We also apply it for a d-dimensional Tangherlini-like solution with α′3 corrections.

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We analyze the low frequency absorption cross section of minimally coupled massless scalar fields by different kinds of charged static black holes in string theory, namely the D1–D5 system in d=5 and a four dimensional dyonic four-charged black hole. In each case we show that this cross section always has the form of some parameter of the solution divided by the black hole Hawking temperature. We also verify in each case that, despite its explicit temperature dependence, such quotient is finite in the extremal limit, giving a well defined cross section. We show that this precise explicit temperature dependence also arises in the same cross section for black holes with string \alpha' corrections: it is actually induced by them.

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The environmental and socio-economic importance of coastal areas is widely recognized, but at present these areas face severe weaknesses and high-risk situations. The increased demand and growing human occupation of coastal zones have greatly contributed to exacerbating such weaknesses. Today, throughout the world, in all countries with coastal regions, episodes of waves overtopping and coastal flooding are frequent. These episodes are usually responsible for property losses and often put human lives at risk. The floods are caused by coastal storms primarily due to the action of very strong winds. The propagation of these storms towards the coast induces high water levels. It is expected that climate change phenomena will contribute to the intensification of coastal storms. In this context, an estimation of coastal flooding hazards is of paramount importance for the planning and management of coastal zones. Consequently, carrying out a series of storm scenarios and analyzing their impacts through numerical modeling is of prime interest to coastal decision-makers. Firstly, throughout this work, historical storm tracks and intensities are characterized for the northeastern region of United States coast, in terms of probability of occurrence. Secondly, several storm events with high potential of occurrence are generated using a specific tool of DelftDashboard interface for Delft3D software. Hydrodynamic models are then used to generate ensemble simulations to assess storms' effects on coastal water levels. For the United States’ northeastern coast, a highly refined regional domain is considered surrounding the area of The Battery, New York, situated in New York Harbor. Based on statistical data of numerical modeling results, a review of the impact of coastal storms to different locations within the study area is performed.

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Mechanical Ventilation is an artificial way to help a Patient to breathe. This procedure is used to support patients with respiratory diseases however in many cases it can provoke lung damages, Acute Respiratory Diseases or organ failure. With the goal to early detect possible patient breath problems a set of limit values was defined to some variables monitored by the ventilator (Average Ventilation Pressure, Compliance Dynamic, Flow, Peak, Plateau and Support Pressure, Positive end-expiratory pressure, Respiratory Rate) in order to create critical events. A critical event is verified when a patient has a value higher or lower than the normal range defined for a certain period of time. The values were defined after elaborate a literature review and meeting with physicians specialized in the area. This work uses data streaming and intelligent agents to process the values collected in real-time and classify them as critical or not. Real data provided by an Intensive Care Unit were used to design and test the solution. In this study it was possible to understand the importance of introduce critical events for Mechanically Ventilated Patients. In some cases a value is considered critical (can trigger an alarm) however it is a single event (instantaneous) and it has not a clinical significance for the patient. The introduction of critical events which crosses a range of values and a pre-defined duration contributes to improve the decision-making process by decreasing the number of false positives and having a better comprehension of the patient condition.

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Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

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