SR yields after reducing the p T of the electron with largest |η| by 5 GeV — a value bounding from above
the invariant mass resolution of same-sign ee pairs near the Z boson mass — in all weighted data events, which was found to have a negligible impact on the results. For the Rpc3LSS1b SR, the method is adapted by simply selecting data events with three or more leptons, which are weighted by the probability of one or more electron charges to be mismeasured such that the resulting event contains three same-signleptons. Another, more important, source of reducible background includes fake or non-prompt leptons, referred to in the following as ‘F/NP’ leptons. These may originate from electroweak-mediated decays of hadrons (in particular b- and c-flavoured hadrons in decays of top quarks and weak bosons), single pions stopped in the EM calorimeter that fake electron signatures, in-flight decays of kaons into muons, or the conversion of photons into pairs of electrons in the beam pipe or detector material. Lepton candidates reconstructed from these different sources share the properties of being generally not well isolated and being mostly rejected by the lepton identification criteria and impact parameter requirements. Therefore, all sources of background with F/NP leptons are estimated together, using a common method that exploits these properties.
least one opposite-charge same-flavour lepton pair satisfying 84 < m `` < 98 GeV.
each lepton channel and for events with and without a b-jet. No significant discrepancies are observed. Some example distributions are shown in figure 2 .
Each of the background types (fake electron, fake muon, charge-flip electron and prompt SS) is dominant, and thus validated directly, in particular regions of the kinematic phase space examined by these SS validation regions. However, the prompt SS contributions are typically dominated by inclusive W Z production, while the prompt SS or 3L background in the signal regions is expected to be dominated by t¯ tV and W Z events produced in association with several hard jets. The Monte Carlo modelling of these rare processes is tested in a further set of dedicated validation regions. The event selections are presented in table 3 . They are based on the object definitions described in section 4 , and impose different jet p T thresholds and require p T > 20 GeV for the leptons to increase the rejection of fake-lepton events. The t¯ tW and W Z+jets validation regions employ only SS µµ events to avoid fake-electron events. The signal contamination is verified to be negligible for the t¯ tZ and W Z+jets validation regions and at most 25% for the t¯ tW validation region for non-excluded SUSY models. The m eff distributions of these validation regions are shown in figures 3(a) – 3(c) . The prediction is observed to agree with the data, therefore validating the Monte Carlo modelling of these rare SM processes.
and silicon microstrip detectors within pseudorapidity 5 |η| < 2.5, and from a transition ra-
diation tracker that covers |η| < 2.0. The EM sampling calorimeter uses lead as absorber and liquid argon (LAr) as the active medium, and is divided into a barrel region that covers |η| < 1.475 and endcap regions that cover 1.375 < |η| < 3.2. The hadronic calorimeter consists of either LAr or scintillator tile as the active medium, and either steel, copper, or tungsten as the absorber, and covers |η| < 4.9. The muon spectrometer covers |η| < 2.7, and uses multiple layers of high-precision tracking chambers to measure the deflection of muons as they traverse a toroidal field of approximately 0.5 (1.0) T in the central (endcap) regions of the detector. A three-level trigger system selects events to be recorded for offline analysis. Signal and the background sources that contain prompt same-signleptons or trileptons are modelled using Monte Carlo (MC) simulations. The remaining background sources are
Simulated samples of heavy down-type quark pair production and decay have been generated by pythia using the MRST2007 LO* PDF set  for several mass values, between 300 and 600 GeV; the cross section is normalized to NNLO .
Several background processes contribute to the final state of same-signleptons with associated jets. The largest backgrounds (including top-quark pair production, W +jets and single top quark production) are estimated from data, as described in detail below (thereafter referred to as ‘data-driven’). Additional background estimates are described using simulated Monte Carlo samples as listed here:
Abstract A data sample of events from proton–proton col- lisions with two isolated same-signleptons, missing trans- verse momentum, and jets is studied in a search for signa- tures of new physics phenomena by the CMS Collaboration at the LHC. The data correspond to an integrated luminos- ity of 35.9 fb −1 , and a center-of-mass energy of 13 TeV. The properties of the events are consistent with expectations from standard model processes, and no excess yield is observed. Exclusion limits at 95% confidence level are set on cross sections for the pair production of gluinos, squarks, and same-sign top quarks, as well as top-quark associated pro- duction of a heavy scalar or pseudoscalar boson decaying to top quarks, and on the standard model production of events with four top quarks. The observed lower mass limits are as high as 1500 GeV for gluinos, 830 GeV for bottom squarks. The excluded mass range for heavy (pseudo)scalar bosons is 350–360 (350–410) GeV. Additionally, model-independent limits in several topological regions are provided, allowing for further interpretations of the results.
Since the Standard Model only explains about 5% of our universe and leaves us with a lot of open questions in fundamental particle physics, a new theory called Supersymmetry is studied as a complementary model to the Standard Model. A search for Supersymmetry with the ATLAS detector and using ﬁnal states with same-signleptons or three leptons is presented in this master thesis. The data used for this analysis were produced in 2015 by the Large Hadron Collider (LHC) using proton-proton collisions at 13 TeV of center-of-mass energy. No excess was found above the Standard Model expectations but we were able to set new limits on the mass of some supersymmetric particles. This thesis describes in detail the topic of the electron charge-ﬂip background, which arises when the electric charge of an electron is mis-measured by the ATLAS detector. This is an important background to take into account when searching for Supersymmetry with same-signleptons. The extraction of charge-ﬂip probabilities, which is needed to determine the number of charge-ﬂip events among our same-sign selection, was performed and found to vary from less than a percent to 8 − 9% depending on the transverse momentum and the pseudorapidity of the electron. The last part of this thesis consists in a study for the potential of rejection of charge-ﬂip electrons. It was performed by identifying and discriminating those electrons based on a multi-variate analysis with a boosted decision tree method using distinctive properties of charge-ﬂip electrons. It was found that we can reject the wide majority of mis-measured electrons (90-93%) while keeping a very high level of eﬃciency for well-measured ones (95%).
2 Related Work
Segmentation of human motion is the process of breaking a continuous sequence of movement data into smaller and meaningful components, that range from actions to movement primitives. It is important here to emphasize that the segmentation may de- pend on its further use; in particular, this process is more constraining when the motion primitives relate to movement generation. The segmentation process consists in iden- tifying the starting and ending frames for each segment corresponding to a movement primitive. The definition of the segments themselves is challenging due to the high- dimensional nature of human movement data and the variability of movement. For sign language movements, this is even more challenging since the segments depend on how the linguistic element boundaries are defined, according to phonetic, phonological and semantic rules, as well as coarticulation between signs. We review hereafter some seg- mentation work applied on general motion capture data and on sign language motion.
Figure 1. M. tuberculosis pénétre dans les cellules dentritiques (CD) par DC-SIGN. Après s’être attachée à la pro- téine DC-SIGN (rouge) qui se concentre au point de contact entre la CD (pointillé) et la bactérie (vert), cette der- nière est rapidement phagocytée (flèche sur le panel supérieur). Lorsque le phagosome est formé (panel infé- rieur), la protéine DC-SIGN recircule à la surface cellulaire et est exclue de la vacuole.
51) Thus, an automatic variable can be initialized to a trap representation without causing undefined behavior, but the value of the variable cannot be used until a proper value is stored in it.
52) Thus, for example, structure assignment need not copy any padding bits.
53) It is possible for objects x and y with the same effective type T to have the same value when they are accessed as objects of type T , but to have different values in other contexts. In particular, if == is defined for type T , then x == y does not imply that memcmp (& x , & y , sizeof ( T ))== 0 . Furthermore, x == y does not necessarily imply that x and y have the same value; other operations on values of type T might distinguish between them.
We consider a class of eigenvalue problems involving coefficients changing sign on the domain of interest. We describe the main spectral properties of these problems according to the features of the coefficients. Then, under some assumptions on the mesh, we explain how one can use classical finite element methods to approximate the spectrum as well as the eigenfunctions while avoiding spurious modes. We also prove localisation results of the eigenfunctions for certain sets of coefficients. To cite this article: C. Carvalho, L. Chesnel, P. Ciarlet Jr., C. R. Acad. Sci. Paris, Ser. I xxx (2017).
The number N P is calculated from events in this background region for which the elec- tron satisfies the same electron selection criteria as applied in the signal region. The value of N F is based on electron candidates satisfying the signal selection criteria but passing less stringent electron identification cuts (“medium”) and failing to meet the calorimeter-based or track-based isolation requirements, or both. The numbers are corrected for the small remaining contribution from prompt electrons (see equation ( 6.1 )). The measured factor f is 0.18 at p T = 20 GeV and increases to around 0.3 for p T ≈ 100 GeV. The main systematic uncertainty is due to the jet requirements in the event selection. This effect is estimated by varying the jet p T between 30 GeV and 50 GeV, which leads to an uncertainty rang- ing between 10% and 30% depending on the electron p T . Other systematic uncertainties arise from a possible difference in the heavy-flavour fraction in the signal and background region, and the prompt background subtraction. The total uncertainty varies between ap- proximately 40% at p T ≈ 20 GeV and 13% for p T ≈ 100 GeV. Due to a lack of statistics to calculate f for electrons with p T > 100 GeV, the value of f for 60 < p T < 100 GeV electrons is used, and the uncertainty is increased to 100%.
We hypothesize that facial traits are under strong selection to facilitate kin recognition among PHS. We first predict that, all else being equal, PHS show more differentiated social relationships than nonkin (NK): They should, for example, associate and affiliate more with each other. Second, we predict that facial traits are under kin selection: PHS should resemble each other more than expected given their genetic resemblance. Thus, they should resemble each other more than NK do but, more importantly, also more than MHS do, even though PHS and MHS share, on average, the same degree of genetic relatedness (r = 0.25). For the past 8 years, we have collated a photobank of about 16,000 facial pictures on a total of 276 indi- viduals, some of which are represented with regular portraits from birth to adulthood. This unique long-term resource allowed us to control for confounding effects of age difference (MHS are neces- sarily at least 1 year apart whereas PHS are generally age mates) on mandrill’s faces.
In C17, the widths of corresponding signed and unsigned may differ by one, in particular an unsigned may be realized by just masking out the sign bit of the signed type. This possibility does not seem to be used in the field, complicates arguing about integers and adds potential case analysis to programs.
Sign Language (SL) linguistics is dependent on the expensive task of annotation. Some automation is already available for low-level information (eg. body part tracking) and the lexical level has shown significant progresses. The syntactic level lacks annotated corpora as well as complete and consistent models. This article presents a solution for the automatic annotation of SL syntactic elements. It exposes a formalism able to represent both constituency-based and dependency-based models. The first enables the representation of structures one may want to annotate, the second aims at fulfilling the holes of the first. A parser is presented and used to conduct two experiments to test the solution. One experiment is on a real corpus, the other is on a synthetic corpus.
measure the cost of doing so, we first observe the score obtained by different im- plementations (sequential, parallel) at the same iteration (i.e. regardless of the execution times). The result of these experiments are presented in Figure 3 (left) and Figure 3 (right) for parallelization strategy 1 (shared policy) and 2 (thread- local policy) respectively. Note that for a single run, the score can only increase with time. However, the average score can occasionally drop if the best perform- ing run finishes early (as in Figure 3 right).
The patterns are described in terms of constituents as shown in figure 2. Their internal arrangement is then described with constraints (section 2.1.4.).
The first described pattern is a buoy (Liddell, 2003). It is visible in figure 1, the left hand of the bi-manual sign TO- VISIT (fig. 1(a)) is maintained all along the excerpt. The pattern is decomposed into three sub-elements: two signs and one locution. The second pattern is an acknowledg- ment. It happens in figure 1 (g). It is decomposed into two sub-elements: a head node and a sign. The third pattern is a question. It also happens in figure 1 (g), but is less clear on this snapshot. It is decomposed as a marker (eyebrows up) and a locution. The “sign check” is a question and an acknowledgment.
III. U SE OF AN ORACLE ON THE SIGN OF x
For real-valued signals, convergence is observed for orders k for which building and solving the corresponding SDP problems is highly demanding in terms of computation and memory storage. However, when x is a positive signal, we observe  convergence at a lower order k. This thus sug- gests a method yielding similar results for real-valued signals using an oracle. Instead of (1), we minimize
Figure 24: AD8203 Phase detector (a) Transfer Curve (b) Control circuitry to set conversion ratio
The AD8302 is an analog ASIC explicitly designed to compare high-frequency waves and detect phase and gain changes. The output of the chip makes it very easy to be acquired by the ADC of the CPU since it is a time-varying DC signal that depends on the phase/gain shift/difference of the inputs. We only make use of the phase shift detection feature of this chip as to maximize data integrity. Gain detection would provide the same results but with much more interferences from surrounding sources.
After imposing that the three charged lepton masses be reproduced correctly, which fixes three of the six parameters in λ l,e , we remove all points where one of the heavy mass
eigenstates violates the direct LEP bound of 100 GeV. We also impose the LEP bounds on modified Z couplings to charged lepton pairs [ 52 ] that constrain the relative modification to the per mille level. This constraint is particularly relevant for the τ , that has the largest mixing with the vector-like leptons. For the points surviving these constraints, we compute the cross section times branching ratio for the pair production and decay to W or Z and leptons and impose the LHC bounds as discussed in section 3.2 . Points that are in violation of this bound are shown in light gray in the following plots, while allowed points are shown in blue.
disrupt national well-being. For Donald Trump and his advisors, “Make America Great Again” puts our time of greatness firmly in the past, clearly back beyond Obama, Clinton, and the Bushes, but refers to no specific moment in American history as the great one. For progressive and Left-wing thinkers and politicians, the Golden Age is New Deal and post-war America, an economy and society structured by Roosevelt’s reforms in the 1930s, a world that lasted into the 1960s. Robert Kuttner’s powerful new book, Can Democracy Survive Global Capitalism? is the latest in a stream of works that use the New Deal to show that government once was able to tame and constrain the very same pathologies of unregulated capitalism that today generate huge inequality in wealth and opportunity, a collapse of social mobility, and a general climate of anxious insecurity. In Kuttner’s account, the New Deal is a kind of existence proof of the possibility of striking a better balance between capitalism, equality, and democracy. Much in Kuttner’s scorching account of the inequities and dangers for democracy in today’s society is on target. Could we, though, as he suggests, just go back to New Deal institutions and policies? Kuttner dates the end of the New Deal world and