Development of Regenerative Tea Cultivation Models through Dual Approach of Soil and Plant Health Management towards Crop Sustainability, Soil Quality Development, Pesticide Reduction and Climate Change Mitigation: A Case Study from Lakhipara Tea Estate, Dooars, West Bengal, India (PART-II)

The first part of this research article documents the impact of the studied Regenerative Agriculture models in tea in respect of crop sustainability, pesticide load reduction and reduction of pest management cost. The findings indicated an increase (78 kg/ha) in crop productivity in the project area as against crop loss of 118 kg/ha in the non- project area during the same period. The finding also indicated a 52 to 77% reduction in the accumulated toxicity potential of the applied pesticides, improvement of soil quality indices and a 6.72% increase in the soil organic carbon stock. Most importantly, carbon assessment in terms of kg CO2 equivalent/ kg made tea (using ACFA version 1.0) indicated approximately 65 to 70 % lower footprint in the project area. The lowering of carbon footprint was due to a 20 to 30 % reduction in the chemical fertilizers along with improvement in carbon sequestration potential of the soil due to quality compost application and reduction of herbicides. The study indicated that Inhana Rational Farming (IRF) Technology can serve as an effective tool towards development of resource based Regenerative Agriculture Models that can ensure safe and low carbon tea cultivation without compromising crop yield and without increasing the cost of cultivation

FDTD modeling of realistic semicontinuous metal films

We have employed a parallelized 3D FDTD (finite-difference time-domain) solver to study the electromagnetic properties of random, semicontinuous, metal films. The structural features of the simulated geometries are exact copies of the fabricated films and are obtained from SEM images of the films themselves. The simulation results show good agreement with the experimentally observed far-field spectra, allowing us to also study the nonlinear moments of the optical responses for these realistic nanostructures. These results help to further our understanding of the details of the electromagnetic response of randomly structured metal films. Our results can also be applied in the optimization of random metal nanostructures and in the design of surface-enhanced spectroscopies and other plasmonic applications

Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants

Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.Peer reviewe