Signal shapes in multiwire proportional chamber-based TPCs

A large-volume Time Projection Chamber (TPC) is the main tracking and particle identification (PID) detector of the ALICE experiment at the CERN LHC. PID in the TPC is performed via specific energy-loss measurements (dE/dx), which are derived from the average pulse-height distribution of ionization generated by charged-particle tracks traversing the TPC volume. During Runs 1 and 2, until 2018, the gas amplification stage was based on multiwire proportional chambers (MWPC). Signals from the MWPC show characteristic long negative tails after an initial positive peak due to the long ion drift times in the MWPC amplification region. This so-called ion tail can lead to a significant amplitude loss in subsequently measured signals, especially in the high-multiplicity environment of high-energy Pb-Pb collisions, which results in a degradation of the dE/dx resolution. A detailed study of the signal shapes measured with the ALICE TPC with the Ne-CO2 (90-10) and Ar-CO2 (90-10) gas mixtures is presented, and the results are compared with three-dimensional Garfield simulations. The impact of the ion tail on the PID performance is studied employing the ALICE simulation framework and the feasibility of an offline correction procedure to account for the ion tail is demonstrated.publishedVersio

The upgrade of the ALICE TPC with GEMs and continuous readout

The upgrade of the ALICE TPC will allow the experiment to cope with the high interaction rates foreseen for the forthcoming Run 3 and Run 4 at the CERN LHC. In this article, we describe the design of new readout chambers and front-end electronics, which are driven by the goals of the experiment. Gas Electron Multiplier (GEM) detectors arranged in stacks containing four GEMs each, and continuous readout electronics based on the SAMPA chip, an ALICE development, are replacing the previous elements. The construction of these new elements, together with their associated quality control procedures, is explained in detail. Finally, the readout chamber and front-end electronics cards replacement, together with the commissioning of the detector prior to installation in the experimental cavern, are presented. After a nine-year period of R&D, construction, and assembly, the upgrade of the TPC was completed in 2020.publishedVersio

Investigating strangeness enhancement with multiplicity in pp collisions using angular correlations

A study of strange hadron production associated with hard scattering processes and with the underlying event is conducted to investigate the origin of the enhanced production of strange hadrons in small collision systems characterised by large charged-particle multiplicities. For this purpose, the production of the single-strange meson KS0 and the double-strange baryon Ξ± is measured, in each event, in the azimuthal direction of the highest-pT particle (“trigger” particle), related to hard scattering processes, and in the direction transverse to it in azimuth, associated with the underlying event, in pp collisions at s = 5.02 TeV and s = 13 TeV using the ALICE detector at the LHC. The per-trigger yields of KS0 and Ξ± are dominated by the transverse-to-leading production (i.e., in the direction transverse to the trigger particle), whose contribution relative to the toward-leading production is observed to increase with the event charged-particle multiplicity. The transverse-to-leading and the toward-leading Ξ±/KS0 yield ratios increase with the multiplicity of charged particles, suggesting that strangeness enhancement with multiplicity is associated with both hard scattering processes and the underlying event. The relative production of Ξ± with respect to KS0 is higher in transverse-to-leading processes over the whole multiplicity interval covered by the measurement. The KS0 and Ξ± per-trigger yields and yield ratios are compared with predictions of three different phenomenological models, namely Pythia8.2 with the Monash tune, Pythia8.2 with ropes and EPOS LHC. The comparison shows that none of them can quantitatively describe either the transverse-to-leading or the toward-leading yields of KS0 and Ξ±.publishedVersio

Multiplicity dependence of charged-particle intra-jet properties in pp collisions at √s = 13 TeV

The first measurement of the multiplicity dependence of intra-jet properties of leading charged-particle jets in proton–proton (pp) collisions is reported. Themean chargedparticle multiplicity and jet fragmentation distributions are measured in minimum-bias and high-multiplicity pp collisions at center-of-mass energy √s = 13 TeV using the ALICE detector. Jets are reconstructed from charged particles produced in the midrapidity region (|η| < 0.9) using the sequential recombination anti-kT algorithm with jet resolution parameters R = 0.2, 0.3, and 0.4 for the transverse momentum (pT) interval 5–110 GeV/c. The highmultiplicity events are selected by the forward V0 scintillator detectors. The mean charged-particle multiplicity inside the leading jet cone rises monotonically with increasing jet pT in qualitative agreement with previous measurements at lower energies. The distributions of jet fragmentation function variables zch and ξ ch are measured for different jet-pT intervals. Jet-pT independent fragmentation of leading jets is observed for wider jets except at high- and low-zch values. The observed “hump-backed plateau” structure in the ξ ch distribution indicates suppression of low-pT particles. In high-multiplicity events, an enhancement of the fragmentation probability of low-zch particles accompanied by a suppression of high-zch particles is observed compared to minimum-bias events. This behavior becomes more prominent for low-pT jets with larger jet radius. The results are compared with predictions of QCD-inspired event generators, PYTHIA8 with Monash 2013 tune and EPOS LHC. It is found that PYTHIA8 qualitatively reproduces the jet modification in high-multiplicity events except at high jet pT. These measurements provide important constraints to models of jet fragmentation.publishedVersio

Search for jet quenching effects in high-multiplicity pp collisions at √ s = 13 TeV via di-jet acoplanarity

The ALICE Collaboration reports a search for jet quenching effects in highmultiplicity (HM) proton-proton collisions at √ s = 13TeV, using the semi-inclusive azimuthaldifference distribution Δφ of charged-particle jets recoiling from a high transverse momentum (high-pT,trig) trigger hadron. Jet quenching may broaden the Δφ distribution measured in HM events compared to that in minimum bias (MB) events. The measurement employs a pT,trig-differential observable for data-driven suppression of the contribution of multiple partonic interactions, which is the dominant background. While azimuthal broadening is indeed observed in HM compared to MB events, similar broadening for HM events is observed for simulations based on the PYTHIA 8 Monte Carlo generator, which does not incorporate jet quenching. Detailed analysis of these data and simulations show that the azimuthal broadening is due to bias of the HM selection towards events with multiple jets in the final state. The identification of this bias has implications for all jet quenching searches where selection is made on the event activity.publishedVersio

Exploring the anti-SARS-CoV-2 main protease potential of FDA approved marine drugs using integrated machine learning templates as predictive tools

Since the inception of COVID-19 pandemic in December 2019, socio-economic crisis begins to rise globally and SARS-CoV-2 was responsible for this outbreak. With this outbreak, currently, world is in need of effective and safe eradication of COVID-19. Hence, in this study anti-SAR-Co-2 potential of FDA approved marine drugs (Biological macromolecules) data set is explored computationally using machine learning algorithm of Flare by Cresset Group, Field template, 3D-QSAR and activity Atlas model was generated against FDA approved M-pro SARS-CoV-2 repurposed drugs including Nafamostat, Hydroxyprogesterone caporate, and Camostat mesylate. Data sets were categorized into active and inactive molecules on the basis of their structural and biological resemblance with repurposed COVID-19 drugs. Then these active compounds were docked against the five different M-pro proteins co-crystal structures. Highest LF VS score of Holichondrin B against all main protease co-crystal structures ranked it as lead drug. Finally, this new technique of drug repurposing remained efficient to explore the anti-SARS-CoV-2 potential of FDA approved marine drugs

Fractional order modeling and analysis of dynamics of stem cell differentiation in complex network

&lt;abstract&gt;&lt;p&gt;In this study, a mathematical model for the differentiation of stem cells is proposed to understand the dynamics of cell differentiation in a complex network. For this, myeloid cells, which are differentiated from stem cells, are introduced in this study. We introduce the threshold quantity $\mathcal{R}_{0}$ to understand the population dynamics of stem cells. The local stability analysis of three equilibria, namely $(i)$ free equilibrium points, $(ii)$ absence of stem and progenitor cells, and $(iii)$ endemic equilibrium points are investigated in this study. The model is first formulated in non-fractional order and after that converted into a fractional sense by utilizing the Atangana-Baleanu derivative in Caputo (ABC) sense in the form of a non-singular kernel. The model is solved by using numerical techniques. It is seen that the myeloid cell population significantly affects the stem cell population.&lt;/p&gt;&lt;/abstract&gt;</jats:p