Total Cross Sections

A unified approach to total cross-sections, based on the QCD contribution to the rise with energy, is presented for the processes $pp$, $p{\bar p}$, $\gamma p, \gamma \gamma, e^+e^- \to hadrons$. For proton processes, a discussion of the role played by soft gluon summation in taming the fast rise due to mini-jets is presented. For photon-photon processes, a comparison with other models indicates the need for precision measurements in both the low and high energy region, likely only with measurements at future Linear Colliders.Comment: 15 pages, 9 figures, LaTeX, uses hsproc.sty and art10.sty. Talk given by G. Pancheri at 'International Hadron Structure-2000', October 1-6, Staralesn

On the variability and increasing trends of heat waves over India

Over India, heat waves occur during the summer months of April to June. A gridded daily temperature data set for the period, 1961–2013 has been analyzed to examine the variability and trends in heat waves over India. For identifying heat waves, the Excess Heat Factor (EHF) and 90th percentile of maximum temperatures were used. Over central and northwestern parts of the country, frequency, total duration and maximum duration of heat waves are increasing. Anomalous persistent high with anti-cyclonic flow, supplemented with clear skies and depleted soil moisture are primarily responsible for the occurrence of heat waves over India. Variability of heat waves over India is influenced by both the tropical Indian Ocean and central Pacific SST anomalies. The warming of the tropical Indian Ocean and more frequent El Nino events in future may further lead to more frequent and longer lasting heat waves over India

QCD predictions for total cross-sections and the Froissart Bound

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The current status and future prospects for therapeutic targeting of KEAP1-NRF2 and β-TrCP-NRF2 interactions in cancer chemoresistance

Drug resistance is one of the biggest challenges in cancer treatment and limits the potential to cure patients. In many tumors, sustained activation of the protein NRF2 makes tumor cells resistant to chemo- and radiotherapy. Thus, blocking inappropriate NRF2 activity in cancers has been shown to reduce resistance in models of the disease. There is a growing scientific interest in NRF2 inhibitors. However, the compounds developed so far are not target-specific and are associated with a high degree of toxicity, hampering clinical applications. Compounds that can enhance the binding of NRF2 to its ubiquitination-facilitating regulator proteins, either KEAP1 or β-TrCP, have the potential to increase NRF2 degradation and may be of value as potential chemosensitising agents in cancer treatment. Approaches based on molecular glue-type mechanisms, in which ligands stabilise a ternary complex between a protein and its binding partner have shown to enhance β-catenin degradation by stabilising its interaction with β-TrCP. This strategy could be applied to rationally discover degradative β-TrCP-NRF2 and KEAP1-NRF2 protein-protein interaction enhancers. We are proposing a novel approach to selectively suppress NRF2 activity in tumors. It is based on recent methodology and has the potential to be a promising new addition to the arsenal of anticancer agents

Total and inelastic cross-sections at LHC at CM energy of 7 TeV and beyond

We discuss expectations for the total and inelastic cross-sections at LHC CM energies $\sqrt{s}\ =\ 7\ TeV$ {and $14\ TeV$} obtained in an eikonal minijet model augmented by soft gluon $k_t$-resummation, which we describe in some detail. We present a band of predictions which encompass recent LHC data and suggest that the inelastic cross-section described by two channel eikonal models include only uncorrelated processes. We show that this interpretation of the model is supported by the LHC data.Comment: 32 pages, 6 figures, Version to appear in Physical Review

Soft Gluon kt-Resummation and the Froissart bound

We study soft gluon kt-resummation and the relevance of zero momentum gluons for the energy dependence of total hadronic cross-sections. We discuss a model in which consistency of the energy dependence of the cross-section with the limitation of the Froissart bound, is directly related to the behaviour of the strong coupling constant in the infrared region. Our predictions for the asymptotic behaviour are shown to be related to the ansatz that the infrared behaviour of the QCD strong coupling constant follows an inverse power law.Comment: To be published in Physics Letters B. This version is 25% shorter than the previous one, as requested by the restrictions on the number of pages for this Journal. Some equations have been skipped, some text has been summarized. The earliest version may be useful for a better understanding of some of the materia

Total cross-section and rapidity gap survival probability at the LHC through an eikonal with soft gluon resummation

New results are presented for total ${\rm pp}/ {\rm \bar p p}$ cross-sections, in the framework of our QCD based model (GGPS). This is an improved eikonal mini-jet model, where soft gluon radiation tames the fast energy rise normally present in mini-jet models. We discuss the variability in our predictions and provide a handy parametrization of our results for the LHC. We find that our model predictions span the range $\sigma_{tot}^{LHC}=100 ^{+10}_{-13} mb$. While this matches nicely with the range of most other models, it does not agree with recent ones which include a "hard" Pomeron, even though our model does include hard scattering. We compute the survival probability for Large Rapidity Gap (LRG) events at the LHC and at the Tevatron. These events are relevant, for example, for Higgs signal in the $WW$ fusion process. We also explore whether measurements of the total cross-sections at the LHC can help us sharpen the model parameters and hence estimates for these survival probabilities, further.Comment: 15 pages, 3 figures, LaTe

Theoretical expectations for total cross-sections at the large hadron collider

In this note, we summarize and compare various model predictions for $pp$ total cross-section $\sigma_{\rm tot}^{pp}$, giving an estimate of the range of predictions for the total cross-section, $\sigma_{\rm tot}^{pp}$ expected at the LHC. We concentrate on the results for \sigma_{\tot}^{pp} obtained in a particular QCD based model of the energy dependence of the total cross-section, including the effect of soft gluon radiation. We obtain the range of predictions in this model by exploring the allowed range of model parameters. We further give a handy parametrisation of these results which incidentally spans the range of various other available predictions at the LHC as well.Comment: 12 pages, 6 figures, laTeX, requires ias.cls, ias.sty include

Combined docking and machine learning identify key molecular determinants of ligand pharmacological activity on β2 adrenoceptor

G protein-coupled receptors (GPCRs) are valuable therapeutic targets for many diseases. A central question of GPCR drug discovery is to understand what determines the agonism or antagonism of ligands that bind them. Ligands exert their action via the interactions in the ligand binding pocket. We hypothesized that there is a common set of receptor interactions made by ligands of diverse structures that mediate their action and that among a large dataset of different ligands, the functionally important interactions will be over-represented. We computationally docked ~2700 known β2AR ligands to multiple β2AR structures, generating ca 75 000 docking poses and predicted all atomic interactions between the receptor and the ligand. We used machine learning (ML) techniques to identify specific interactions that correlate with the agonist or antagonist activity of these ligands. We demonstrate with the application of ML methods that it is possible to identify the key interactions associated with agonism or antagonism of ligands. The most representative interactions for agonist ligands involve K972.68×67 , F194ECL2 , S2035.42×43 , S2045.43×44 , S2075.46×641 , H2966.58×58 , and K3057.32×31 . Meanwhile, the antagonist ligands made interactions with W2866.48×48 and Y3167.43×42 , both residues considered to be important in GPCR activation. The interpretation of ML analysis in human understandable form allowed us to construct an exquisitely detailed structure-activity relationship that identifies small changes to the ligands that invert their pharmacological activity and thus helps to guide the drug discovery process. This approach can be readily applied to any drug target