An electropenetrography waveform library for the probing and ingestion behaviors of Culex tarsalis on human hands

Culex tarsalis Coquillett(Diptera:Culicidae)mosquitoes are capable of vectoring numerous pathogens affecting public and animal health.Unfortunately,the probing behaviors of mosquitoes are poorly understood because they occur in opaque tissues.Electropenetrography(EPG)has the potential to elucidate these behaviors by recording the electrical signals generated during probing.We used an AC–DC EPG with variable input resistors(Ri levels)to construct a waveform library for Cx.tarsalis feeding on human hands.Biological events associated with mosquito probing were used to characterize waveforms at four Ri levels and with two electrical current types.The optimal settings for EPG recordings of Cx.tarsalis probing on human hands was an Ri level of 10^(7)Ohms using an applied signal of 150 millivolts alternating current.Waveforms for Cx.tarsalis included those previously observed and associated with probing behaviors in Aedes aegypti L.(Diptera:Culicidae):waveform families J(surface salivation),K(stylet penetration through the skin),L(types 1 and 2,search for a blood vessel/ingestion site),M(types 1 and 2,ingestion),N(type 1,an unknown behavior which may be a resting and digestion phase),and W(withdrawal).However,we also observed variations in the waveforms not described in Ae.aegypti,which we named types L3,M3,M4,and N2.This investigation enhances our understanding of mosquito probing behaviors.It also provides a new tool for the automated calculation of peak frequency.This work will facilitate future pathogen acquisition and transmission studies and help identify new pest and disease management targets.

Adaptive Robust Waveform Selection for Unknown Target Detection in Clutter

A basic assumption of most recently proposed waveform design algorithms is that the target impulse response is a known deterministic function or a stochastic process with a known power spectral density （PSD）. However, it is well-known that a target impulse response is neither easily nor accurately obtained; besides it changes sharply with attitude angles. Both of the aforementioned cases complicate the waveform design process. In this paper, an adaptive robust waveform selection method for unknown target detection in clutter is proposed. The target impulse response is considered to be unknown but belongs to a known uncertainty set. An adaptive waveform library is devised by using a signal-to-clutter-plus-noise ratio （SCNR）- based optimal waveform design method. By applying the minimax robust waveform selection method, the optimal robust waveform is selected to ensure the lowest performance bound of the unknown target detection in clutter. Results show that the adaptive waveform library outperforms the predefined linear frequency modulation （LFM） waveform library on the SCNR bound.