Global nonlinear optimization for the interpretation of source parameters from total gradient of gravity and magnetic anomalies caused by thin dyke

An efficient approach to estimate model parameters from total gradient of gravity and magnetic data based on Very Fast simulated Annealing (VFSA) has been presented. This is the first time of applying VFSA in interpreting total gradient of potential field data with a new formulation estimation caused due to isolated causative sources embedded in the subsurface. The model parameters interpreted here are the amplitude coefficient (k), exact origin of causative source (x0) depth (z0) and the shape factors (q). The results of VFSA optimization show that it can uniquely determine all the model parameters when shape factor is constrained. The model parameters estimated by the present method, mostly the shape and depth of the buried structures were found to be in excellent agreement with the actual parameters. The method has also the proficiency of evading highly noisy data points and improves the interpretation results. Study of histogram and cross-plot analysis also suggests the interpretation within the estimated uncertainty.  Inversion of noise-free and noisy synthetic data for single structures as well as field data demonstrates the efficacy of the approach. The technique has been warily and effectively applied to real data examples (Leona Anomaly, Senegal for gravity and Pima copper deposit, USA for magnetic) with the presence of ore bodies. The present method can be extremely applicable for mineral exploration or ore bodies of dyke-like structure embedded in the shallow and deeper subsurface. The computation time for the whole process is very short

Delineation of partial melts and crustal heterogeneities within the crust beneath Kumaon Himalaya, India from Lg wave attenuation

Abstract The crustal seismic attenuation or the Q structure is studied by using the Fourier spectra of Lg-wave along the Tanakpur- Dharchula- Dharma transect in the Kumaon Himalaya. The 1 Hz Lg Q (Q0) values are computed between different pairs of two stations and the observed values are later utilized to calculate the lateral variation in the Q0 values by following a back projection algorithm. This computation of Q0 values utilizes five regional distance earthquakes having moment magnitude (Mw) ≥ 4.0, which lie along the great circle path of the transect. Three of the five earthquakes occurred in the Tibetan plateau and the and the others occurred to the southwest on the Indian shield and are well recorded at all the 32 broadband seismographs operated between September 2018 and March 2022. The estimate Qo values range from 63 ± 2 and 203 ± 25, with the lowest value in the Lesser Himalaya and the highest across part of the Indo Gangetic Plain and Siwalik Himalaya. The Q0 model has low values ∼200 along the profile in the Indo Gangetic Plain and the Siwalik Himalaya, and are correlated with 2–5 km thick sedimentary layers below the Himalaya and the adjoining Indo-Gangetic Plain. We observe two distinctly different Q0 values to the northeast in the Lesser Himalaya tectonic unit. The region lying between the South Almora Thrust (SAT) and the Berinag Thrust (BT) shows extremely low Q0 values (∼60) but increases further north towards the Vaikrita Thrust (VT) to ∼200. The possible explanation for observing such huge variation of the Q0 values within a single tectonic unit may be the presence of fluid rich ramp structures, which introduces crustal heterogeneities and traps the aqueous fluids or partial melts lying within the crust. The Lg Q0 values decrease to the North and become ∼166 for station pairs in the Higher Himalaya and Tethys Himalaya tectonic units. The low Q0 values observed in this region may be correlated with low viscous partial melts in the form of Miocene leucogranite plutons, which resulted out of the Indo-Asian collision. The attenuation structure along the profile in the Kumaon Himalaya can be used to estimate ground motions of future earthquakes in the area and can contribute to seismic hazard assessment in the Himalaya and neighbouring regions

Estimation of tuberculosis incidence at subnational level using three methods to monitor progress towards ending TB in India, 2015–2020

Objectives We verified subnational (state/union territory (UT)/district) claims of achievements in reducing tuberculosis (TB) incidence in 2020 compared with 2015, in India.Design A community-based survey, analysis of programme data and anti-TB drug sales and utilisation data.Setting National TB Elimination Program and private TB treatment settings in 73 districts that had filed a claim to the Central TB Division of India for progress towards TB-free status.Participants Each district was divided into survey units (SU) and one village/ward was randomly selected from each SU. All household members in the selected village were interviewed. Sputum from participants with a history of anti-TB therapy (ATT), those currently experiencing chest symptoms or on ATT were tested using Xpert/Rif/TrueNat. The survey continued until 30 Mycobacterium tuberculosis cases were identified in a district.Outcome measures We calculated a direct estimate of TB incidence based on incident cases identified in the survey. We calculated an under-reporting factor by matching these cases within the TB notification system. The TB notification adjusted for this factor was the estimate by the indirect method. We also calculated TB incidence from drug sale data in the private sector and drug utilisation data in the public sector. We compared the three estimates of TB incidence in 2020 with TB incidence in 2015.Results The estimated direct incidence ranged from 19 (Purba Medinipur, West Bengal) to 1457 (Jaintia Hills, Meghalaya) per 100 000 population. Indirect estimates of incidence ranged between 19 (Diu, Dadra and Nagar Haveli) and 788 (Dumka, Jharkhand) per 100 000 population. The incidence using drug sale data ranged from 19 per 100 000 population in Diu, Dadra and Nagar Haveli to 651 per 100 000 population in Centenary, Maharashtra.Conclusion TB incidence in 1 state, 2 UTs and 35 districts had declined by at least 20% since 2015. Two districts in India were declared TB free in 2020