A new method to derive the calculation formula of antenna total isotropic sensitivity

In the OTA test of the antenna spatial performance of communication equipment,the total radiated power TRP and the total isotropic sensitivity TIS are two important characterization parameters,representing the overall transmission and reception performance of the antenna in space.In order to gain a deeper understanding of the physical meaning of these two parameters and the calculation method of TIS,this paper proposes a new method for deriving the TIS calculation formula.This method uses the reciprocity principle of the transmitting antenna and the receiving antenna.By comparing the transmitting process,two corresponding receiving antenna parameters are newly defined in the receiving process analysis.Combining the relationship between the antenna pattern and the receiving intensity,the relationship formula between TIS and equivalent isotropic sensitivity EIS is obtained after a simple deduction.This formula is consistent with the calculation formula given in the reference,but the derivation method in the reference is to use the ideal omnidirectional antenna as a reference,calculate the received power at the receiver input,and combine factors such as the actual antenna gain to derive the TIS calculation formula;the method proposed in this paper is to first derive the expression of the receiving directivity coefficient by definition,introduce the receiving strength parameter,calculate the full-space receiving power at the antenna,and derive the TIS calculation formula.In comparison,the derivation process in this paper calculates the received power from the input end of the receiving antenna,so there is no need to consider the efficiency of the antenna itself.The received power calculation starts directly from the receiving intensity.The entire derivation process is intuitive and easy to understand,avoiding complex concepts and formulas.

Accurate, fully-automated NMR spectral profiling for metabolomics

Many diseases cause significant changes to the concentrations of small molecules (aka metabolites) that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile". This information can be extracted from a biofluid's NMR spectrum. Today, this is often done manually by trained human experts, which means this process is relatively slow, expensive and error-prone. This paper presents a tool, Bayesil, that can quickly, accurately and autonomously produce a complex biofluid's (e.g., serum or CSF) metabolic profile from a 1D1H NMR spectrum. This requires first performing several spectral processing steps then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. Many of these steps are novel algorithms and our matching step views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures, show that Bayesil can autonomously find the concentration of all NMR-detectable metabolites accurately (~90% correct identification and ~10% quantification error), in <5minutes on a single CPU. These results demonstrate that Bayesil is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively -- with an accuracy that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of NMR in clinical settings. Available at http://www.bayesil.ca.