Publications by authors named "A Vamsi Krishna"

Resource availability dictates how fast and how much microbial populations grow. Quantifying the relationship between microbial growth and resource concentrations makes it possible to promote, inhibit, and predict microbial activity. Microbes require many resources, including macronutrients (e.

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  • The study focuses on detecting multijet signatures from proton-proton collisions at a high energy of 13 TeV, analyzing a dataset totaling 128 fb^{-1}.
  • A special data scouting method is utilized to pick out events with low combined momentum in jets.
  • This research is pioneering in its investigation of electroweak particle production in R-parity violating supersymmetric models, particularly examining hadronically decaying mass-degenerate higgsinos, and it broadens the limits on the existence of R-parity violating top squarks and gluinos.
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  • Long-term stability poses a significant challenge for commercializing perovskite solar cells, made worse by a lack of consistent outdoor testing data.
  • This study involved two years of outdoor testing on perovskite mini-modules, analyzing their performance changes throughout each day, including both degradation during the day and recovery overnight.
  • Using the XGBoost regression model, the researchers successfully predicted the power output of the mini-modules, achieving a low error rate, which shows promise for estimating the lifespan of perovskite devices based on environmental factors.
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The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.

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Shared autonomous vehicles (SAVs) can help older adults maintain mobility and independence throughout the later stages of life. However, research is critically needed to assess the design of SAV interior features and quantify potential mobility challenges for older populations. This paper presents a study that adopted a mixed-methods approach to evaluate the needs and perceptions of adults aged 65 years and older regarding interior features of SAVs during user enactment, and offers data-driven insights on task performance to inform design decisions.

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