Study of epidemiological behaviour of malaria and its control in the Purulia district of West Bengal, India (2016–2020)

Purulia is a malaria-prone district in West Bengal, India, with approximately half of the blocks defined as malaria endemic. We analyzed the malaria case in each block of the Purulia district from January 1, 2016, to December 31, 2020. As per the API, 20 blocks of Purulia were assigned to four different categories (0–3) and mapped using ArcGIS software. An exponential decay model was fitted to forecast the trend of malaria cases for each block of Purulia (2021–2025). There was a sharp decrease in total malaria cases and API from 2016 to 2020 due to the mass distribution of LLINs. The majority of cases (72.63%) were found in ≥ 15-year age group. Males were more prone to malaria (60.09%). Malaria was highly prevalent among Scheduled Tribes (48.44%). Six blocks were reported in Category 3 (high risk) and none in Category 0 (no risk) in 2016, while no blocks were determined to be in Category 3, and three blocks were in Category 0 in 2020. The exponential decay model prediction is oriented towards gaining malaria-free status in thirteen blocks of Purulia by 2025. This study will incite the government to uphold and strengthen the current efforts to meet the malaria elimination goals.

Decomposition of d = 9 short-range 0νββ decay operators at one-loop level

We perform a systematical study of the dimension-9 short-range 0νββ decay operators at one-loop level. There are only six genuine topologies which generate eight diagrams, and the recipe to identify the possible one-loop realizations of the 0νββ decay operators is sketched. Certain hypercharge assignments are excluded by the absence of tree-level diagrams in a genuine one-loop model. The mediators of each decomposition can generate Majorana neutrino masses which are discussed up to two-loop level. We present an example of 0νββ decay model in which the neutrino masses are generated at two-loop level, and the short-range contribution can be comparable with the mass mechanism in some region of parameter space.

Exploring the role of snow metamorphism on the isotopic composition of the surface snow at EastGRIP

Stable water isotopes from polar ice cores are invaluable high-resolution climate proxy records. Recent studies have aimed to improve knowledge of how the climate signal is stored in the water isotope record by addressing the influence of post-depositional processes on the surface snow isotopic composition. In this study, the relationship between changes in surface snow microstructure after precipitation/deposition events and water isotopes is explored using measurements of snow specific surface area (SSA). Continuous daily SSA measurements from the East Greenland Ice Core Project site (EastGRIP) situated in the accumulation zone of the Greenland Ice Sheet during the summer seasons of 2017, 2018 and 2019 are used to develop an empirical decay model to describe events of rapid decrease in SSA, driven predominantly by vapour diffusion in the pore space and atmospheric vapour exchange. The SSA decay model is described by the exponential equation SSA(t) = (SSA0 −26.8) e−0.54t + 26.8. The model performance is optimal for daily mean values of surface temperature in the range 0 °C to −25 °C and wind speed < 6 m s−1. The findings from the SSA analysis are used to explore the influence of surface snow metamorphism on altering the isotopic composition of surface snow. It is found that rapid SSA decay events correspond to decreases in d-excess over a 2-day period in 72 % of the samples. Detailed studies using Empirical Orthogonal Function (EOF) analysis revealed a coherence between the dominant mode of variance of SSA and d-excess during periods of low spatial variability of surface snow over the sampling transect, suggesting that processes driving change in SSA also influence d-excess. Our findings highlight the need for future studies to decouple the processes driving surface snow metamorphism in order to quantify the fractionation effect of individual processes on the snow isotopic composition.

Spatial variations of North Atlantic landfalling tropical cyclone wind speed decay over the continental United States

Understanding tropical cyclone wind speed decay during the post-landfall stage is critical for inland hazard preparation. This paper examines the spatial variation of wind speed decay of tropical cyclones over the continental United States. We find that tropical cyclones making landfall over the Gulf Coast decay faster within the first 24 hours after landfall than those making landfall over the Atlantic East Coast. The variation of the decay rate over the Gulf Coast remains larger than that over the Atlantic East Coast for tropical cyclones that had made landfall more than 24 hours prior. Besides an average weaker tropical cyclone landfall intensity, the near-parallel trajectory and the proximity of storms to the coastline also help to explain the slower post-landfall wind speed decay for Atlantic East Coast landfalling tropical cyclones. Tropical cyclones crossing the Florida peninsula only slowly weaken after landfall, with an average of less than 20% post-landfall wind speed drop while transiting the state. The existence of these spatial variations also brings into question the utility of a uniform wind decay model. While weak intensity decay over the Florida peninsula is well estimated by the uniform wind decay model, the error from the uniform wind decay model increases with tropical cyclones making direct landfall more parallel to the Atlantic East Coast. The underestimation of inland wind speed by the uniform wind decay model found over the western Gulf Coast brings attention to the role of land-air interactions in the decay of inland tropical cyclones.

A volumetric prediction model for postoperative cyst shrinkage

Objectives With only limited information available on dimensional changes after jaw cyst surgery, postoperative cyst shrinkage remains largely unpredictable. We aimed to propose a model for volumetric shrinkage based on time elapsed since cyst surgery. Material and methods We used data from patients that underwent cyst enucleation or decompression between 2007 and 2017 and had at least three computed tomography (CT) scans per patient. We fitted one simple exponential decay model [V(t) = V0 · e−ɑt] and one model with a patient-specific decay rate [Vk(t) = V0 · e−βt + γkt]. Results Based on 108 CT scans from 36 patients (median age at surgery: 45.5 years, IQR: 32.3–55.3, 44% female), our simple exponential decay model is V(t) = V0· e−0.0035t where V(t) is the residual cyst volume after time t elapsed since surgery, V0 is the initial cyst volume, and e is the base of the natural logarithm. Considering a patient-specific decay rate, the model is Vk(t) = V0· e−0.0049t + γkt where γk is normally distributed, with expectation 0 and standard deviation 0.0041. Conclusions Using an exponential regression model, we were able to reliably estimate volumetric shrinkage after jaw cyst surgery. The patient-specific decay rate substantially improved the fit of the model, whereas adding specific covariates as interaction effects to model the decay rate did not provide any significant improvement. Clinical relevance Estimating postoperative cyst shrinkage is relevant for both treatment planning of jaw cyst surgery as well as evaluating the clinical success of the surgical approach.