Short-Term and Long-Term COVID-19 Pandemic Forecasting Revisited with the Emergence of OMICRON Variant in Jordan

Three simple approaches to forecast the COVID-19 epidemic in Jordan were previously proposed by Hussein, et al.: a short-term forecast (STF) based on a linear forecast model with a learning database on the reported cases in the previous 5–40 days, a long-term forecast (LTF) based on a mathematical formula that describes the COVID-19 pandemic situation, and a hybrid forecast (HF), which merges the STF and the LTF models. With the emergence of the OMICRON variant, the LTF failed to forecast the pandemic due to vital reasons related to the infection rate and the speed of the OMICRON variant, which is faster than the previous variants. However, the STF remained suitable for the sudden changes in epi curves because these simple models learn for the previous data of reported cases. In this study, we revisited these models by introducing a simple modification for the LTF and the HF model in order to better forecast the COVID-19 pandemic by considering the OMICRON variant. As another approach, we also tested a time-delay neural network (TDNN) to model the dataset. Interestingly, the new modification was to reuse the same function previously used in the LTF model after changing some parameters related to shift and time-lag. Surprisingly, the mathematical function type was still valid, suggesting this is the best one to be used for such pandemic situations of the same virus family. The TDNN was data-driven, and it was robust and successful in capturing the sudden change in +qPCR cases before and after of emergence of the OMICRON variant

Short-Term and Long-Term COVID-19 Pandemic Forecasting Revisited with the Emergence of OMICRON Variant in Jordan

Three simple approaches to forecast the COVID-19 epidemic in Jordan were previously proposed by Hussein, et al.: a short-term forecast (STF) based on a linear forecast model with a learning database on the reported cases in the previous 5–40 days, a long-term forecast (LTF) based on a mathematical formula that describes the COVID-19 pandemic situation, and a hybrid forecast (HF), which merges the STF and the LTF models. With the emergence of the OMICRON variant, the LTF failed to forecast the pandemic due to vital reasons related to the infection rate and the speed of the OMICRON variant, which is faster than the previous variants. However, the STF remained suitable for the sudden changes in epi curves because these simple models learn for the previous data of reported cases. In this study, we revisited these models by introducing a simple modification for the LTF and the HF model in order to better forecast the COVID-19 pandemic by considering the OMICRON variant. As another approach, we also tested a time-delay neural network (TDNN) to model the dataset. Interestingly, the new modification was to reuse the same function previously used in the LTF model after changing some parameters related to shift and time-lag. Surprisingly, the mathematical function type was still valid, suggesting this is the best one to be used for such pandemic situations of the same virus family. The TDNN was data-driven, and it was robust and successful in capturing the sudden change in +qPCR cases before and after of emergence of the OMICRON variant

Combined search for the standard model Higgs boson decaying to a bb pair using the full CDF data set

We combine the results of searches for the standard model Higgs boson based on the full CDF Run II data set obtained from sqrt(s) = 1.96 TeV p-pbar collisions at the Fermilab Tevatron corresponding to an integrated luminosity of 9.45/fb. The searches are conducted for Higgs bosons that are produced in association with a W or Z boson, have masses in the range 90-150 GeV/c^2, and decay into bb pairs. An excess of data is present that is inconsistent with the background prediction at the level of 2.5 standard deviations (the most significant local excess is 2.7 standard deviations).Comment: To be published in Phys. Rev. Lett (v2 contains minor updates based on comments from PRL

Observation of Exclusive Gamma Gamma Production in p pbar Collisions at sqrt{s}=1.96 TeV

We have observed exclusive \gamma\gamma production in proton-antiproton collisions at \sqrt{s}=1.96 TeV, using data from 1.11 \pm 0.07 fb^{-1} integrated luminosity taken by the Run II Collider Detector at Fermilab. We selected events with two electromagnetic showers, each with transverse energy E_T > 2.5 GeV and pseudorapidity |\eta| < 1.0, with no other particles detected in -7.4 < \eta < +7.4. The two showers have similar E_T and azimuthal angle separation \Delta\phi \sim \pi; 34 events have two charged particle tracks, consistent with the QED process p \bar{p} to p + e^+e^- + \bar{p} by two-photon exchange, while 43 events have no charged tracks. The number of these events that are exclusive \pi^0\pi^0 is consistent with zero and is < 15 at 95% C.L. The cross section for p\bar{p} to p+\gamma\gamma+\bar{p} with |\eta(\gamma)| < 1.0 and E_T(\gamma) > 2.5$ GeV is 2.48^{+0.40}_{-0.35}(stat)^{+0.40}_{-0.51}(syst) pb.Comment: 7 pages, 4 figure

Studying the Underlying Event in Drell-Yan and High Transverse Momentum Jet Production at the Tevatron

We study the underlying event in proton-antiproton collisions by examining the behavior of charged particles (transverse momentum pT > 0.5 GeV/c, pseudorapidity |\eta| < 1) produced in association with large transverse momentum jets (~2.2 fb-1) or with Drell-Yan lepton-pairs (~2.7 fb-1) in the Z-boson mass region (70 < M(pair) < 110 GeV/c2) as measured by CDF at 1.96 TeV center-of-mass energy. We use the direction of the lepton-pair (in Drell-Yan production) or the leading jet (in high-pT jet production) in each event to define three regions of \eta-\phi space; toward, away, and transverse, where \phi is the azimuthal scattering angle. For Drell-Yan production (excluding the leptons) both the toward and transverse regions are very sensitive to the underlying event. In high-pT jet production the transverse region is very sensitive to the underlying event and is separated into a MAX and MIN transverse region, which helps separate the hard component (initial and final-state radiation) from the beam-beam remnant and multiple parton interaction components of the scattering. The data are corrected to the particle level to remove detector effects and are then compared with several QCD Monte-Carlo models. The goal of this analysis is to provide data that can be used to test and improve the QCD Monte-Carlo models of the underlying event that are used to simulate hadron-hadron collisions.Comment: Submitted to Phys.Rev.

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization

Evidence for t\bar{t}\gamma Production and Measurement of \sigma_t\bar{t}\gamma / \sigma_t\bar{t}

Using data corresponding to 6.0/fb of ppbar collisions at sqrt(s) = 1.96 TeV collected by the CDF II detector, we present a cross section measurement of top-quark pair production with an additional radiated photon. The events are selected by looking for a lepton, a photon, significant transverse momentum imbalance, large total transverse energy, and three or more jets, with at least one identified as containing a b quark. The ttbar+photon sample requires the photon to have 10 GeV or more of transverse energy, and to be in the central region. Using an event selection optimized for the ttbar+photon candidate sample we measure the production cross section of, and the ratio of cross sections of the two samples. Control samples in the dilepton+photon and lepton+photon+\met, channels are constructed to aid in decay product identification and background measurements. We observe 30 ttbar+photon candidate events compared to the standard model expectation of 26.9 +/- 3.4 events. We measure the ttbar+photon cross section to be 0.18+0.08 pb, and the ratio of the cross section of ttbar+photon to ttbar to be 0.024 +/- 0.009. Assuming no ttbar+photon production, we observe a probability of 0.0015 of the background events alone producing 30 events or more, corresponding to 3.0 standard deviations.Comment: 9 pages, 3 figure

Precision Top-Quark Mass Measurements at CDF

We present a precision measurement of the top-quark mass using the full sample of Tevatron $\sqrt{s}=1.96$ TeV proton-antiproton collisions collected by the CDF II detector, corresponding to an integrated luminosity of 8.7 $fb^{-1}$. Using a sample of $t\bar{t}$ candidate events decaying into the lepton+jets channel, we obtain distributions of the top-quark masses and the invariant mass of two jets from the $W$ boson decays from data. We then compare these distributions to templates derived from signal and background samples to extract the top-quark mass and the energy scale of the calorimeter jets with {\it in situ} calibration. The likelihood fit of the templates from signal and background events to the data yields the single most-precise measurement of the top-quark mass, \mtop = 172.85 \pm$0.71 (stat)$\pm$0.85 (syst) GeV/c^{2}.$Comment: submitted to Phys. Rev. Let

A search for resonant production of ttˉt\bar{t} pairs in $4.8\ \rm{fb}^{-1}ofintegratedluminosityof of integrated luminosity of p\bar{p}collisionsat collisions at \sqrt{s}=1.96\ \rm{TeV}$

We search for resonant production of tt pairs in 4.8 fb^{-1} integrated luminosity of ppbar collision data at sqrt{s}=1.96 TeV in the lepton+jets decay channel, where one top quark decays leptonically and the other hadronically. A matrix element reconstruction technique is used; for each event a probability density function (pdf) of the ttbar candidate invariant mass is sampled. These pdfs are used to construct a likelihood function, whereby the cross section for resonant ttbar production is estimated, given a hypothetical resonance mass and width. The data indicate no evidence of resonant production of ttbar pairs. A benchmark model of leptophobic Z \rightarrow ttbar is excluded with m_{Z'} < 900 GeV at 95% confidence level.Comment: accepted for publication in Physical Review D Sep 21, 201