Photoelectron Emission from Metal Surfaces Induced by VUV-emission of Filament Driven Hydrogen Arc Discharge Plasma

Photoelectron emission measurements have been performed using a filament-driven multi-cusp arc discharge volume production H^- ion source (LIISA). It has been found that photoelectron currents obtained with Al, Cu, Mo, Ta and stainless steel (SAE 304) are on the same order of magnitude. The photoelectron currents depend linearly on the discharge power. It is shown experimentally that photoelectron emission is significant only in the short wavelength range of hydrogen spectrum due to the energy dependence of the quantum efficiency. It is estimated from the measured data that the maximum photoelectron flux from plasma chamber walls is on the order of 1 A per kW of discharge power

An Experimental Study of Waveguide Coupled Microwave Heating with Conventional Multicusp Negative Ion Source

Negative ion production with conventional multicusp plasma chambers utilizing 2.45 GHz microwave heating is demonstrated. The experimental results were obtained with the multicusp plasma chambers and extraction systems of the RFdriven RADIS ion source and the filament driven arc discharge ion source LIISA. A waveguide microwave coupling system, which is almost similar to the one used with the SILHI ion source, was used. The results demonstrate that at least one third of negative ion beam obtained with inductive RF-coupling (RADIS) or arc discharge (LIISA) can be achieved with 1 kW of 2.45 GHz microwave power in CW mode without any modification of the plasma chamber. The co-extracted electron to H^- ratio and the optimum pressure range were observed to be similar for both heating methods. The behaviour of the plasma implies that the energy transfer from the microwaves to the plasma electrons is mainly an off-resonance process

Effects of insect harassment on weight gain and survival in reindeer calves

Relationships between insect harassment and the weight gain and survival of reindeer calves were studied in two areas in Finland north of the Arctic Circle. The level of insect harassment explained a significant amount of the yearly variation in calf weights determined in autumn or early winter in both areas and directly influenced calf mortality in one of them. The lowest weights and calf percents were experienced in years when a bad winter was followed by a warm summer with severe insect harassment.Råkån vaikutus poronvasojen painonlisåykseen ja eloonjååmiseen.Abstract in Finnish / Tiivistelmd: Rakan (vertaimevat ja porossa loisivat hyonteiset) vaikutusta vasojen painoon ja vasaprosenttiin tutkittiin Alakylan paliskunnassa sekå Kaldoaivi - Paistunturin alueella. Kummallakin alueella rakka selitti huomattavan osan vasojen syyspainojen vuosivaihtelusta ja Kaldoaivi - Paistunturissa se vaikutti suoraan myos vasaprosenttiin. Vasojen painot ja vasaprosentit olivat alhaisimmat vuosina, joina vaikeaa talvea seurasi kuuma, hyonteisille suotuisa kesa.Effekter av insektforstyrrelser på vektøkning og overlevelse av reinkalver.Abstract in Swedish / Sammendrag: Effekter av insektforstyrrelser på vektøkning og overlevelse av reinkalver er studert i to områder av Finland nord for Polarsirkelen. Graden av insektforstyrrelser forklarte en signifikant andel av variasjonene fra år til år i kalvevekter bestemt høst eller tidlig vinter for begge områder. Den virket også direkte inn på kalvedødeligheten i et av områdene. De laveste vekter og kalveprosenter fant man i år der en dårlig vinter ble etterfulgt av en varm sommer med alvorlige insektforstyrrelser

Evaluation of temporal moments and Fourier transformed data in time-domain diffuse optical tomography

Time-domain diffuse optical tomography (TD-DOT) uses near-infrared pulsed lasers as light sources to measure time-varying exitance on the boundary of the target. These are used to estimate optical properties of the imaged target. Several integral-transform-based moments of the time-resolved data have been utilized in TD-DOT, the most common being the mean time of flight and variance. Recently, it has been shown that Fourier transforming the time-domain data to frequency domain enables utilization of these data at one or several frequencies, producing equally as good estimates as the whole time-domain data. In this work, we present a systematic comparison of the usage of the temporal moments and Fourier transformed data in TD-DOT. Both absolute and difference imaging are evaluated using numerical simulations. The simulations show that utilizing temporal moments and Fourier transformed data in TD-DOT provides good quality reconstructions with a good estimation accuracy. These estimates are improved if more than one data type is used. Furthermore, the simulations show that the frequency-domain computations enable computationally cheaper and straightforward implementation of the inverse solver when compared to the temporal moments

Time-domain diffuse optical tomography utilizing truncated Fourier series approximation

Diffuse optical tomography (DOT) uses near infrared light for in vivo imaging of spatially varying optical parameters in biological tissues. It is known that time-resolved measurements provide the richest information on soft tissues, among other measurement types in DOT such as steady-state and intensity-modulated measurements. Therefore, several integral-transform-based moments of the time-resolved DOT measurements have been considered to estimate spatially distributed optical parameters. However, the use of such moments can result in low-contrast images and cross-talks between the reconstructed optical parameters, limiting their accuracy. In this work, we propose to utilize a truncated Fourier series approximation in time-resolved DOT. Using this approximation, we obtained optical parameter estimates with accuracy comparable to using whole time-resolved data that uses low computational time and resources. The truncated Fourier series approximation based estimates also displayed good contrast and minimal parameter cross-talk, and the estimates further improved in accuracy when multiple Fourier frequencies were used

Bayesian approach to image reconstruction in photoacoustic tomography

Photoacoustic tomography is a hybrid imaging method that has a variety of biomedical applications. In photoacoustic tomography, the image reconstruction problem (inverse problem) is to resolve the initial pressure distribution from detected ultrasound waves generated within an object due to an illumination of a short light pulse. In this work, this problem is approached in Bayesian framework. Image reconstruction is investigated with numerical simulations in different detector geometries, including limited view setup, and utilizing different prior information. Furthermore, assessing the reliability of the estimates is investigated. The simulations show that the Bayesian approach can produce accurate estimates of the initial pressure distribution and uncertainty information even in a limited view setup if proper prior information is utilized

The D-bar Method for Diffuse Optical Tomography: a computational study

The D-bar method at negative energy is numerically implemented. Using the method we are able to numerically reconstruct potentials and investigate exceptional points at negative energy. Subsequently, applying the method to Diffusive Optical Tomography, a new way of reconstructing the diffusion coefficient from the associated Complex Geometrics Optics solution is suggested and numerically validated

Modelling of errors due to speed of sound variations in photoacoustic tomography using a Bayesian framework

Inverse problem of estimating initial pressure in photoacoustic tomography is ill-posed and thus sensitive to errors in modelling and measurements. In practical experiments, accurate knowledge of the speed of sound of the imaged target is commonly not available, and therefore an approximate speed of sound is used in the computational model. This can result in errors in the solution of the inverse problem that can appear as artefacts in the reconstructed images. In this paper, the inverse problem of photoacoustic tomography is approached in a Bayesian framework. Errors due to uncertainties in the speed of sound are modelled using Bayesian approximation error modelling. Estimation of the initial pressure distribution together with information on the reliability of these estimates are considered. The approach was studied using numerical simulations. The results show that uncertainties in the speed of sound can cause significant errors in the solution of the inverse problem. However, modelling of these uncertainties improves the accuracy of the solution