Browsing by Author "Triambak, S"
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Item Investigation of pair-correlated 0+ states in Ba 134 via the Ba 136 (p,t) reaction(American Physical Society, 2021) Nzobadila Ondze, J.C; Rebeiro, B.M; Triambak, SWe performed a high resolution study of 0 + states in 134 Ba using the 136 Ba ( p , t ) two-neutron transfer reaction. Our experiment shows a significant portion of the L = 0 pair-transfer strength concentrated at excited 0 + levels in 134 Ba . Potential implications in the context of 136 Xe → 136 Ba neutrinoless double beta decay matrix element calculations are briefly discussed.Item Modern African nuclear detector laboratory: Development of state-of-the-art in-house detector facility at the University of the Western Cape(SpringerLink, 2021) Kapoor, K.; Orce, J.N; Abrahams, K; Akakpo, E; Bester, Z; Jenkins, D.G; Jordaan, K.L; Jones, M.Y.; Kamedien, M.A.; Lindsay, R.; Lomberg, B; Masango, S.; Ngwetsheni, C.; Ntshangase, S.S.; Radebe, N.; Triambak, S; Zyl, J.J. van,The upcoming detector facility aims at developing new state-of-the-art particle detectors as well as providing hands-on training to postgraduate students using both analog and digital signal processing from nuclear radiation detectors. The project is two-fold and aims at developing: 1) ancillary detectors to be coupled with the new GAMKA array at iThemba LABS. Of particular interest to our group is the determination of nuclear shapes, which depend on the hyperfine splitting of magnetic substates; 2) PET scanners for cancer imaging using a cheaper technology. Performance of NaI(Tl) inorganic scintillator detectors has been evaluated using PIXIE-16 modules from XIA digital electronics. Gamma-ray energy spectra were acquired from 60Co and 137Cs radioactive sources to calculate the detector resolution as well as to optimize the digital parameters. The present study focuses on improving and optimizing the slow and fast filter parameters for NaI(Tl) detectors which can eventually be used in the list mode of data aquisition.Item A new logistic growth model applied to COVID-19 fatality data(Elsevier, 2021) Triambak, S; Mahapatra, D P; Mallick, N; Sahoo, Rfollows a sub-exponential power-law scaling whenever effective control interventions are in place. Taking this into consideration, we present a new phenomenological logistic model that is well-suited for such power-law epidemic growth. Methods: We empirically develop the logistic growth model using simple scaling arguments, known boundary conditions and a comparison with available data from four countries, Belgium, China, Denmark and Germany, where (arguably) effective containment measures were put in place during the first wave of the pandemic. A non-linear least-squares minimization algorithm is used to map the parameter space and make optimal predictions. Results: Unlike other logistic growth models, our presented model is shown to consistently make accurate predictions of peak heights, peak locations and cumulative saturation values for incomplete epidemic growth curves. We further show that the power-law growth model also works reasonably well when containment and lock down strategies are not as stringent as they were during the first wave of infections in 2020. On the basis of this agreement, the model was used to forecast COVID-19 fatalities for the third wave in South Africa, which was in progress during the time of this work. Conclusion: We anticipate that our presented model will be useful for a similar forecasting of COVID-19 induced infections/deaths in other regions as well as other cases of infectious disease outbreaks, particularly when power-law scaling is observed.