Searching for a Pair-Produced Supersymmetric Top Partner Using Recursive Jigsaw Variables and Boosted Decision Trees with 139 fb⁻¹ of Data From the ATLAS Detector

The Standard Model of Particle Physics is the most comprehensive theory describing how fundamental particles and three of the four fundamental forces are related. However, the Standard Model is known to be an incomplete theory with several limitations. Supersymmetry is an extension of the Standard Model of Particle Physics, introducing supersymmetric partners to every fermion and boson in the Standard Model. Supersymmetry gives a diverse collection of theoretical models providing solutions to these phenomenological inconsistencies. It contains a mechanism for stabilizing the Higgs boson mass while predicting the existence of several new particles, including a suitable Dark Matter candidate. The Large Hadron Collider (LHC) is the world\u27s most powerful particle accelerator, located at the CERN laboratory near Geneva, Switzerland. In the Summer of 2012, the ATLAS and CMS experiments at CERN announced the discovery of a particle,which was later confirmed to be the Higgs boson. This was a massive accomplishment, the discovery of a particle hypothesized in 1964 that has remained elusive until now. However, this is not the end of the experimental effort. ATLAS and CMS are general purpose detectors performing a multitude of measurements, as well as carrying out many searches for Beyond the Standard Model (BSM) physics. In this dissertation, two searches are conducted for a pair-produced stop squark, the supersymmetric partner to the top quark. The stop can decay to a variety of final states, depending upon the hierarchy of the mass eigenstates formed from the linear superposition of the SUSY partners of the Higgs boson and electroweak gauge bosons. In this stop search, the relevant supersymmetric mass eigenstate is the neutralino. The searches for the stop in the 3-body decay channel presented here consist of a b-quark, W-boson, and a neutralino, with both W-bosons decaying to a lepton and a neutrino. In order to discriminate the signal from background two techniques are employed, a cut-and-count technique using recursive jigsaw variables and a technique using Boosted Decision Trees. The recursive jigsaw variables are derived using the Recursive Jigsaw Reconstruction technique, a method for decomposing measured properties event-by-event by approximating the rest frame of each intermediate particle state. These variables are powerful discriminators on their own, as shown in the cut-and-count analysis. Machine learning techniques are also utilized by training boosted decision trees, using the recursive jigsaw variables in tandem with other kinematic variables, to study whether we can enhance our discovery potential. These analyses use 139 inverse fb of 13 TeV data collected at the ATLAS experiment during Run-2 of the LHC from 2015 until 2018. No evidence of an excess beyond the SM background prediction is observed in the Recursive Jigsaw Reconstruction analysis, however, exclusion limits at 95% confidence levels are set far exceeding the previous limits. The potential for an improvement on these limits is demonstrated by training Boosted Decision Trees, a technique I hope is used in future BSM physics searches

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.Postprint (published version

“I was trying to save the world”: delusion-like ideation and associated impacts reported by Western practitioners of Buddhist meditation

Delusional ideation is characteristic of psychopathology (e.g., psychosis, bipolar disorder) and is also found among the general population. Contemporary case studies have documented delusional ideation as a feature of meditation-induced psychosis, and Buddhist literature on the side effects and adverse effects of meditation also includes discussion of transient experiences that could be considered delusional or delusion-like ideation. Drawing upon interviews with more than 100 Buddhist meditation practitioners and meditation experts (teachers and clinicians) in the West, this paper presents a mixed-methods study of delusion-like ideation (DLI) associated with meditation. We establish a typology of eight types of DLI and report their relative frequencies among the sample; we identify impacts and treatment outcomes associated with DLI; and we provide four case studies that illustrate the risk factors, trajectories, outcomes, and appraisals associated with DLI. We show how responses to DLI are shaped not only by the type of DLI but also by their duration, severity, and impact, as well as the associated appraisals made both by meditators and by meditation teachers and psychiatrists. In some cases, the phenomenology of DLI suggests influences from the lived context of Buddhist meditation cultures. Furthermore, although DLI are normalized in Buddhist meditation culture under certain circumstances, meditation experts also noted the potential severity of meditation-related DLI, with some identifying it as a “red flag” meriting close monitoring if not immediate intervention. Finally, we discuss various explanatory models that could account for the presence, content, and impacts of DLI among meditators, drawing upon the environmental conditions and social contexts of meditation retreats, the role of attention and sensory attenuation in meditation practice, and the ways in which meditation-related DLI can function as a cultural and spiritual “idiom of distress.

Quinoa phenotyping methodologies: An international consensus

Quinoa is a crop originating in the Andes but grown more widely and with the genetic potential for significant further expansion. Due to the phenotypic plasticity of quinoa, varieties need to be assessed across years and multiple locations. To improve comparability among field trials across the globe and to facilitate collaborations, components of the trials need to be kept consistent, including the type and methods of data collected. Here, an internationally open-access framework for phenotyping a wide range of quinoa features is proposed to facilitate the systematic agronomic, physiological and genetic characterization of quinoa for crop adaptation and improvement. Mature plant phenotyping is a central aspect of this paper, including detailed descriptions and the provision of phenotyping cards to facilitate consistency in data collection. High-throughput methods for multi-temporal phenotyping based on remote sensing technologies are described. Tools for higher-throughput post-harvest phenotyping of seeds are presented. A guideline for approaching quinoa field trials including the collection of environmental data and designing layouts with statistical robustness is suggested. To move towards developing resources for quinoa in line with major cereal crops, a database was created. The Quinoa Germinate Platform will serve as a central repository of data for quinoa researchers globally.Fil: Stanschewski, Clara S.. King Abdullah University of Science and Technology; Arabia SauditaFil: Rey, Elodie. King Abdullah University of Science and Technology; Arabia SauditaFil: Fiene, Gabriele. King Abdullah University of Science and Technology; Arabia SauditaFil: Craine, Evan B.. Washington State University; Estados UnidosFil: Wellman, Gordon. King Abdullah University of Science and Technology; Arabia SauditaFil: Melino, Vanessa J.. King Abdullah University of Science and Technology; Arabia SauditaFil: Patiranage, Dilan S. R.. King Abdullah University of Science and Technology; Arabia SauditaFil: Johansen, Kasper. King Abdullah University of Science and Technology; Arabia SauditaFil: Schmöckel, Sandra M.. King Abdullah University of Science and Technology; Arabia SauditaFil: Bertero, Hector Daniel. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal. Cátedra de Producción Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Oakey, Helena. University of Adelaide; AustraliaFil: Colque Little, Carla. Universidad de Copenhagen; DinamarcaFil: Afzal, Irfan. University of Agriculture; PakistánFil: Raubach, Sebastian. The James Hutton Institute; Reino UnidoFil: Miller, Nathan. University of Wisconsin; Estados UnidosFil: Streich, Jared. Oak Ridge National Laboratory; Estados UnidosFil: Amby, Daniel Buchvaldt. Universidad de Copenhagen; DinamarcaFil: Emrani, Nazgol. Christian-albrechts-universität Zu Kiel; AlemaniaFil: Warmington, Mark. Agriculture And Food; AustraliaFil: Mousa, Magdi A. A.. Assiut University; Arabia Saudita. King Abdullah University of Science and Technology; Arabia SauditaFil: Wu, David. Shanxi Jiaqi Agri-Tech Co.; ChinaFil: Jacobson, Daniel. Oak Ridge National Laboratory; Estados UnidosFil: Andreasen, Christian. Universidad de Copenhagen; DinamarcaFil: Jung, Christian. Christian-albrechts-universität Zu Kiel; AlemaniaFil: Murphy, Kevin. Washington State University; Estados UnidosFil: Bazile, Didier. Savoirs, Environnement, Sociétés; Francia. Universite Paul-valery Montpellier Iii; FranciaFil: Tester, Mark. King Abdullah University of Science and Technology; Arabia Saudit

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

The ATLAS Tile Calorimeter Phase-II Upgrade Demonstrator Data Acquisition and Software

The Phase-II upgrades will prepare the ATLAS experiment for the High Luminosity LHC (HL-LHC), planned to begin operation in 2026. The HL-LHC is expected to deliver more than ten times the integrated luminosity of LHC Runs 1-3 combined. To achieve this in a reasonable amount of time, an increase in instantaneous luminosity corresponding to up to 200 simultaneous $pp$ interactions per bunch crossing is required. This large luminosisty increase presents significant challenges to the detector, trigger, and data acquisition systems in the form of increased trigger rates and detector occupancy. The results from the tests with beam performed at CERN, as well as the latest results on the development of the on- and off-detector electronics, firmware, data processing, and simulation components of the Tile Calorimeter Demonstrator readout system are presented

The ATLAS Tile Calorimeter Phase-II Upgrade Demonstrator Data Acquisition and Software

The LHC plans a series of upgrades culminating in the High Luminosity LHC (HL-LHC) which will have an average luminosity 5-7 times larger than the design LHC value. The electronics of the hadronic Tile Calorimeter (TileCal) will undergo a substantial upgrade to accommodate to the HL-LHC parameters. In particular, TileCal will undergo a major replacement of its on- and off-detector electronics. The photomultiplier signals will be digitized and transferred off-detector to the TileCal PreProcessors (TilePPr) for every bunch crossing, requiring a data bandwidth of 40 Tbps. The TilePPr will reconstruct, store and send the calorimeter signals to first level of trigger at a rate of 40 MHz. This will provide better precision of the calorimeter signals used by the trigger system and will allow the development of more complex trigger algorithms. In parallel, the data samples will be stored in pipeline memories and the data of the events selected by the ATLAS central trigger system and transferred to the ATLAS global Data AcQuisition (DAQ) system for further processing. Recently extensive tests have been performed recently with beam at the CERN accelerator facilities. External beam detectors have been used to measure the beam position and to generate a trigger signal when the particle beam impinges the calorimeter modules, while a Demonstrator system of the TileCal upgrade electronics has been successfully employed to read-out the calorimeter signals in parallel to the current TileCal electronics. This contribution describes the results from the tests with beam performed at CERN, as well as the latest results on the development of the on- and the off-detector electronics, firmware, data processing and simulation components of the TileCal Demonstrator readout system

Investigation of Wave Propagation Behavior in Magnetically Coupled MEMS Oscillators

This paper investigates the dynamic behavior of a 1D array of magnetically coupled MEMS oscillators. To facilitate future research and innovation, this paper details the model used to predict wave propagation behavior in the microfabricated array. The investigations model the oscillator array as a series of clamped-clamped beams that are coupled via magnetic proof masses. The contributions to system dynamics of the beam and magnetic interactions of each oscillator are theorized. Finally, the dynamic behavior for the entire array is investigated with a series of theoretical trend studies.</jats:p