197 research outputs found
Searching for SUSY with multijets and missing trasnverse momentum
No full textThe proton-proton collisions at =13 TeV at the LHC, CERN provide an unique opportunity to search for new particles. An inclusive search for supersymmetry is performed in final states containing multiple jets and missing transverse momentum using 12.9 \fbinv data collected by the CMS experiment in the year 2016. The main backgrounds originating from standard model processes are estimated using data driven methods. The results are interpreted in a variety of simplified models of pair production of supersymmetric particles
Search for Supersymmetry in proton-proton collisions at = 13 TeV with jets, b-jets and missing transverse momentum
No full textStandard Model of elementary particles (SM) explains various physical phenomena occurring in the world around us in the terms of participating fundamental particles and interactions among these particles. The particle family of the model is completed with the long sought Higgs boson of mass 125 GeV by the CMS and ATLAS experiments at the Large Hadron Collider in 2012. The SM, however, is largely accepted to be incomplete as it does not explain theoretical stability of the Higgs boson mass, or explain observed dark matter in the universe, or incorporate gravity to name a few. Many beyond SM theories are postulated to overcome limitations of the SM. One of such theories is Supersymmetry (SUSY). SUSY models predict a partner to every SM particle, which differs by spin half from the SM counterpart.These particles are expected to be more massive than their SM cousins.This thesis presents a search for SUSY in a final state with multiple jets, b-jets and large missing transverse momentum. The search is performed using 137 fb data collected by CMS experiment at LHC, over the years 2016, 2017 and 2018 using proton-proton collisions at centre of mass energy of 13 TeV. The SM events and different SUSY topologies which also give the same final state are considered. No signature for SUSY is found based on this analysis. The limits are put on different SUSY scenarios with squark and gluino pair production. Depending on model,gluinos with mass up to 2-2.3 TeV and squarks with mass 1.1-1.6 TeV are probed at 95% confidence level
Isoflurane Preserves Viability of Highly Metabolic Renal Epithelial Cells Exposed to Anoxia
No full textThe general metadata -- e.g., title, author, abstract, subject headings, etc. -- is publicly available, but access to the submitted files is restricted to UT Southwestern campus access and/or authorized UT Southwestern users.BACKGROUND: Cells subjected to ischemia, whether in the context of hypoxia, hypovolemia, or circulatory collapse, undergo damage and death as a result of oxygen deprivation. Previous studies have shown that general anesthetics can protect cells from ischemic injury by lowering their aerobic metabolism and decreasing production of toxic metabolites, among other mechanisms (1, 2, 3). This very preliminary study investigated the potential protective effect of isoflurane on the survival of cells that have a fairly high baseline metabolic rate, human renal proximal tubular epithelial cells (HK-2) and human microvascular endothelial cells (HMEC), in an anoxic environment.
METHODS: Cultured HK-2 and HMEC cells were incubated in a Forma Scientific Anaerobic System at 37C either in the absence (control) or presence (experimental) of 5% isoflurane for 0, 24, 48, 72, and 96 hours. Cell viability and metabolic activity were then assessed using live/dead fluorescence imaging and an MTT cell metabolism assay, respectively.
RESULTS: In vitro exposure of cells to anoxia without isoflurane over a period of 96 hours, resulted in a reduction of viability of HK-2 cells from a baseline of 98%, to approximately 8-9%. Over the same period of time, viability of cells exposed to isoflurane and anoxia decreased to 35%. This represented a fourfold increase in survival of HK-2 cells exposed to isoflurane at 96 hours. At earlier time points, both cell death in anoxia, and the protective effect of isoflurane were less dramatic. HMECs did not undergo significant cell death upon exposure to either anoxia or anoxia with isoflurane, with 98% of the cells surviving the exposure to anoxia in both cases. The net metabolic activity, as assessed by absorbance using the MTT assay, decreased in HK-2 cells over increasing periods of anoxia, a trend that did not change with the addition of isoflurane. Metabolic activity of HMECs remained intact and relatively stable throughout the course of anoxic exposure.
CONCLUSION: In this preliminary study, continuous exposure of HK-2 cells to 5% isoflurane during anoxic incubation had a protective effect on cell viability over a period of 96 hours. Whether this effect was also present in the less metabolically active HMECs, was not determined, as anoxia over the time period of the study had little effect on cell viability in either the experimental group or in the control group. The protective effect observed for HK-2 cells will likely vary with differences in metabolic requirements of different cell types, types and concentrations of anesthetic agents, and duration of anesthetic exposure. Anesthetic treatment may need to be tailored specifically to a cell type to confer the protective effects desired
A Study on Behavioural Finance Psychology in Investment Decisions of Investors
No full textThis research paper delves into the realm of behavioral finance psychology and its profound implications for investment decision-making. Drawing upon a quantitative research methodology, the study examines the influence of psychological biases, emotional factors, and cognitive processes on individuals\u27 investment behaviors. A comprehensive survey was conducted among a diverse sample of 186 investors, yielding valuable insights into their tendencies and preferences. The findings underscore the significant impact of psychological biases on investment decisions. Participants exhibited a tendency to rely on past experiences, be influenced by peers, and face challenges in deviating from initial opinions. Emotional factors emerged as key drivers, shaping choices and contributing to risk preferences. Moreover, the study highlights the prevalence of loss aversion and status quo bias, shedding light on the cognitive underpinnings of investment behaviors. Additionally, the influence of media framing and the role of presentation in investment decisions were evident, emphasizing the relevance of behavioral cues in shaping perceptions. These insights carry important implications for investors, practitioners, and policymakers. Increased awareness of these biases and tendencies can empower investors to make more informed decisions. Practitioners can tailor financial advice to better align with investors\u27 cognitive processes and emotional responses. Policymakers can design educational programs that address behavioral biases and promote rational decision-making. The study suggests avenues for future research, including longitudinal studies and interventions to mitigate biases.
Keywords: behavioral finance, psychological biases, investment decision-making, emotional factors, cognitive processes, loss aversion, status quo bias, media framing, investor education, quantitative research
Misuse of the phytoplankton-zooplankton dichotomy: the need to assign organisms as mixotrophs within plankton functional types
No full textThe classic portrayal of plankton is dominated by phytoplanktonic primary producers and zooplanktonic secondary producers. In reality, many if not most plankton traditionally labelled as phytoplankton or microzooplankton should be identified as mixotrophs, contributing to both primary and secondary production. Mixotrophic protists (i.e. single-celled eukaryotes that perform photosynthesis and graze on particles) do not represent a minor component of the plankton, as some form of inferior representatives of the past evolution of protists; they represent a major component of the extant protist plankton, and one which could become more dominant with climate change. The implications for this mistaken identification, of the incorrect labelling of mixotrophs as " phytoplankton" or "microzooplankton", are great. It extends from the (mis)use of photopigments as indicators of primary production performed by strict photoautotrophs rather than also (co)locating mixotrophic activity, through to the inadequacy of plankton functional type descriptions in models (noting that mixotrophic production in the individual organism is not a simple sum of phototrophy and heterotrophy). We propose that mixotrophy should be recognized as a major contributor to plankton dynamics, with due effort expended in field and laboratory studies, and should no longer be side-lined in conceptual food webs or in mathematical models. © 2012 The Author 2012. Published by Oxford University Press. All rights reserved
A deep neural network to search for new long-lived particles decaying to jets
No full textA tagging algorithm to identify jets that are significantly displaced from the proton-proton (pp) collision region in the CMS detector at the LHC is presented. Displaced jets can arise from the decays of long-lived particles (LLPs), which are predicted by several theoretical extensions of the standard model. The tagger is a multiclass classifier based on a deep neural network, which is parameterised according to the proper decay length of the LLP. A novel scheme is defined to reliably label jets from LLP decays for supervised learning. Samples of pp collision data, recorded by the CMS detector at a centre-of-mass energy of 13 TeV, and simulated events are used to train the neural network. Domain adaptation by backward propagation is performed to improve the simulation modelling of the jet class probability distributions observed in pp collision data. The potential performance of the tagger is demonstrated with a search for long-lived gluinos, a manifestation of split supersymmetric models. The tagger provides a rejection factor of 10 000 for jets from standard model processes, while maintaining an LLP jet tagging efficiency of 30-80% for gluinos with 1 mm 10 m. The expected coverage of the parameter space for split supersymmetry is presented.A tagging algorithm to identify jets that are significantly displaced from the proton-proton (pp) collision region in the CMS detector at the LHC is presented. Displaced jets can arise from the decays of long-lived particles (LLPs), which are predicted by several theoretical extensions of the standard model. The tagger is a multiclass classifier based on a deep neural network, which is parameterised according to the proper decay length of the LLP. A novel scheme is defined to reliably label jets from LLP decays for supervised learning. Samples of pp collision data, recorded by the CMS detector at a centre-of-mass energy of 13 TeV, and simulated events are used to train the neural network. Domain adaptation by backward propagation is performed to improve the simulation modelling of the jet class probability distributions observed in pp collision data. The potential performance of the tagger is demonstrated with a search for long-lived gluinos, a manifestation of split supersymmetric models. The tagger provides a rejection factor of 10 000 for jets from standard model processes, while maintaining an LLP jet tagging efficiency of 30-80% for gluinos with 1 mm 10 m. The expected coverage of the parameter space for split supersymmetry is presented
A new calibration method for charm jet identification validated with proton-proton collision events at √s = 13 TeV
No full textMany measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb-1 at √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses
Observation of Forward Neutron Multiplicity Dependence of Dimuon Acoplanarity in Ultraperipheral Pb-Pb Collisions at =5.02 TeV
No full textPublikacja bezkosztow
Search for dark matter particles produced in association with a Higgs boson in proton-proton collisions at 13 TeV
No full textA search for dark matter (DM) particles is performed using events with a Higgs boson candidate and large missing transverse momentum. The analysis is based on proton-proton collision data at a center-of-mass energy of 13 TeV collected by the CMS experiment at the LHC in 2016, corresponding to an integrated luminosity of 35.9 fb. The search is performed in five Higgs boson decay channels: , , , , and and the results from the individual channels are combined to maximize the sensitivity of the analysis. No significant excess over the expected standard model background is observed in any of the five channels or in their combination. Limits are set on DM production in the context of two simplified models. The results are also interpreted in terms of a spin-independent DM-nucleon scattering cross section and compared to those from direct-detection DM experiments. This is the first search for DM particles produced in association with a Higgs boson decaying to a pair of W or Z bosons, and the first statistical combination based on five Higgs boson decay channels.A search for dark matter (DM) particles is performed using events with a Higgs boson candidate and large missing transverse momentum. The analysis is based on proton- proton collision data at a center-of-mass energy of 13 TeV collected by the CMS experiment at the LHC in 2016, corresponding to an integrated luminosity of 35.9 fb. The search is performed in five Higgs boson decay channels: , γγ, ττ, WW, and ZZ. The results from the individual channels are combined to maximize the sensitivity of the analysis. No significant excess over the expected standard model background is observed in any of the five channels or in their combination. Limits are set on DM production in the context of two simplified models. The results are also interpreted in terms of a spin-independent DM-nucleon scattering cross section and compared to those from direct-detection DM experiments. This is the first search for DM particles produced in association with a Higgs boson decaying to a pair of W or Z bosons, and the first statistical combination based on five Higgs boson decay channels.[graphic not available: see fulltext]A search for dark matter (DM) particles is performed using events with a Higgs boson candidate and large missing transverse momentum. The analysis is based on proton-proton collision data at a center-of-mass energy of 13 TeV collected by the CMS experiment at the LHC in 2016, corresponding to an integrated luminosity of 35.9 fb. The search is performed in five Higgs boson decay channels: h , , , WW, and ZZ. The results from the individual channels are combined to maximize the sensitivity of the analysis. No significant excess over the expected standard model background is observed in any of the five channels or in their combination. Limits are set on DM production in the context of two simplified models. The results are also interpreted in terms of a spin-independent DM-nucleon scattering cross section and compared to those from direct-detection DM experiments. This is the first search for DM particles produced in association with a Higgs boson decaying to a pair of W or Z bosons, and the first statistical combination based on five Higgs boson decay channels
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