Finding a needle in Auditory Brainstem Responses

In this thesis we look at data where sedated patients have been pinpricked with a needle during an Auditory Brainstem Response recording. By looking at this data set with different statistical methods some butterfly pattern emerged and peaks appeared in the spectrum around the time where the needle pinpricking should have occurred. With this results a model was developed and evaluated. Future investigations is needed to interpret the results

Submillimetre galaxies in a hierarchical universe: number counts, redshift distribution and implications for the IMF

High-redshift submillimetre galaxies (SMGs) are some of the most rapidly star-forming galaxies in the Universe. Historically, galaxy formation models have had difficulty explaining the observed number counts of SMGs. We combine a semi-empirical model with 3D hydrodynamical simulations and 3D dust radiative transfer to predict the number counts of unlensed SMGs. Because the stellar mass functions, gas and dust masses, and sizes of our galaxies are constrained to match observations, we can isolate uncertainties related to the dynamical evolution of galaxy mergers and the dust radiative transfer. The number counts and redshift distributions predicted by our model agree well with observations. Isolated disc galaxies dominate the faint (S_(1.1) ≲ 1 or S_(850) ≲ 2 mJy) population. The brighter sources are a mix of merger-induced starbursts and galaxy-pair SMGs; the latter subpopulation accounts for ∼30–50 per cent of all SMGs at all S_(1.1) ≳ 0.5 mJy (S_(850) ≳ 1 mJy). The mean redshifts are ∼3.0–3.5, depending on the flux cut, and the brightest sources tend to be at higher redshifts. Because the galaxy-pair SMGs will be resolved into multiple fainter sources by the Atacama Large Millimeter/submillimeter Array (ALMA), the bright ALMA counts should be as much as two times less than those observed using single-dish telescopes. The agreement between our model, which uses a Kroupa initial mass function (IMF), and observations suggests that the IMF in high-redshift starbursts need not be top heavy; if the IMF were top heavy, our model would overpredict the number counts. We conclude that the difficulty some models have reproducing the observed SMG counts is likely indicative of more general problems – such as an underprediction of the abundance of massive galaxies or a star formation rate and stellar mass relation normalization lower than that observed – rather than a problem specific to the SMG population

Submillimetre galaxies in a hierarchical universe: number counts, redshift distribution and implications for the IMF

High-redshift submillimetre galaxies (SMGs) are some of the most rapidly star-forming galaxies in the Universe. Historically, galaxy formation models have had difficulty explaining the observed number counts of SMGs. We combine a semi-empirical model with 3D hydrodynamical simulations and 3D dust radiative transfer to predict the number counts of unlensed SMGs. Because the stellar mass functions, gas and dust masses, and sizes of our galaxies are constrained to match observations, we can isolate uncertainties related to the dynamical evolution of galaxy mergers and the dust radiative transfer. The number counts and redshift distributions predicted by our model agree well with observations. Isolated disc galaxies dominate the faint (S_(1.1) ≲ 1 or S_(850) ≲ 2 mJy) population. The brighter sources are a mix of merger-induced starbursts and galaxy-pair SMGs; the latter subpopulation accounts for ∼30–50 per cent of all SMGs at all S_(1.1) ≳ 0.5 mJy (S_(850) ≳ 1 mJy). The mean redshifts are ∼3.0–3.5, depending on the flux cut, and the brightest sources tend to be at higher redshifts. Because the galaxy-pair SMGs will be resolved into multiple fainter sources by the Atacama Large Millimeter/submillimeter Array (ALMA), the bright ALMA counts should be as much as two times less than those observed using single-dish telescopes. The agreement between our model, which uses a Kroupa initial mass function (IMF), and observations suggests that the IMF in high-redshift starbursts need not be top heavy; if the IMF were top heavy, our model would overpredict the number counts. We conclude that the difficulty some models have reproducing the observed SMG counts is likely indicative of more general problems – such as an underprediction of the abundance of massive galaxies or a star formation rate and stellar mass relation normalization lower than that observed – rather than a problem specific to the SMG population

The Formation of High Redshift Submillimeter Galaxies

We describe a model for the formation of \zsim 2 Submillimeter Galaxies (SMGs) which simultaneously accounts for both average and bright SMGs while providing a reasonable match to their mean observed spectral energy distributions (SEDs). By coupling hydrodynamic simulations of galaxy mergers with the high resolution 3D polychromatic radiative transfer code Sunrise, we find that a mass sequence of merger models which use observational constraints as physical input naturally yield objects which exhibit black hole, bulge, and H2 gas masses similar to those observed in SMGs. The dominant drivers behind the 850 micron flux are the masses of the merging galaxies and the stellar birthcloud covering fraction. The most luminous (S850 ~ 15 mJy) sources are recovered by ~10^13 Msun 1:1 major mergers with a birthcloud covering fraction close to unity, whereas more average SMGs ~5-7 mJy) may be formed in lower mass halos ~5x10^12 Msun. These models demonstrate the need for high spatial resolution hydrodynamic and radiative transfer simulations in matching both the most luminous sources as well as the full SEDs of SMGs. While these models suggest a natural formation mechanism for SMGs, they do not attempt to match cosmological statistics of galaxy populations; future efforts along this line will help ascertain the robustness of these models.Comment: MNRAS Accepted; Revised version includes expanded discussion of simulated radio properties of SMG

Modeling Mid-infrared Diagnostics of Obscured Quasars and Starbursts

We analyze the link between active galactic nuclei (AGNs) and mid-infrared flux using dust radiative transfer calculations of starbursts realized in hydrodynamical simulations. Focusing on the effects of galaxy dust, we evaluate diagnostics commonly used to disentangle AGN and star formation in ultraluminous infrared galaxies (ULIRGs). We examine these quantities as a function of time, viewing angle, dust model, AGN spectrum, and AGN strength in merger simulations representing two possible extremes of the ULIRG population: one is a typical gas-rich merger at z ~ 0, and the other is characteristic of extremely obscured starbursts at z ~ 2-4. This highly obscured burst begins star-formation-dominated with significant polycyclic aromatic hydrocarbon (PAH) emission, and ends with a ~10^9 yr period of red near-IR colors. At coalescence, when the AGN is most luminous, dust obscures the near-infrared AGN signature, reduces the relative emission from PAHs, and enhances the 9.7 μm absorption by silicate grains. Although generally consistent with previous interpretations, our results imply none of these indicators can unambiguously estimate the AGN luminosity fraction in all cases. Motivated by the simulations, we show that a combination of the extinction feature at 9.7 μm, the PAH strength, and a near-infrared slope can simultaneously constrain the AGN fraction and dust grain distribution for a wide range of obscuration. We find that this indicator, accessible to the James Webb Space Telescope, may estimate the AGN power as tightly as the hard X-ray flux alone, thereby providing a valuable future cross-check and constraint for large samples of distant ULIRGs

Finite Element Simulation Combination to Predict the Distortion of Thin Walled Milled Aluminum Workpieces as a Result of Machining Induced Residual Stresses

Machining induced residual stresses (MIRS) are a main driver for distortion of monolithic thin walled aluminum workpieces. A typical machining process for manufacturing such geometries for the aerospace industry is milling. In order to avoid high costs due to remanufacturing or part rejection, a simulation combination, consisting of two different finite element method (FEM) models, is developed to predict the part distortion due to MIRS. First, a 3D FEM cutting simulation is developed to predict the residual stresses due to machining. This simulation avoids cost intensive residual stress measurements. The milling process of the aluminum alloy AA7050-T7451 with a regular end mill is simulated. The simulation output, MIRS, forces and temperatures, is validated by face milling experiments on aluminum. The model takes mechanical dynamic effects, thermomechanical coupling, material properties and a damage law into account. Second, a subsequent finite element simulation, characterized by a static, linear elastic model, where the simulated MIRS from the cutting model are used as an input and the distortion of the workpiece is calculated, is presented. The predicted distortion is compared to an additional experiment, where a 1 mm thick wafer was removed at the milled surface of the aluminum workpiece. Furthermore, a thin walled component that represents a down scaled version of an aerospace component is manufactured and its distortion is analyzed. The results show that MIRS could be forecasted with moderate accuracy, which leads to the conclusion that the FEM cutting model needs to be improved in order to use the MIRS for a correct prediction of the distortion with the help of the linear elastic FEM model. The linear elastic model on the other hand is able to predict the part distortion with higher accuracy when using measured data instead of MIRS from the cutting simulation

The Internet of Things enhancing animal welfare and farm operational efficiency

The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further insights of economic value into the wellbeing of the animal, thus an enhanced range of welfare related services have been provisioned. The integration of the information from neck-mounted collars with the compositional analysis data of milk measured at a robotic milking station facilitates the early diagnosis of specific illnesses such as mastitis. The combination of different data streams also serves to eliminate the generation of false alarms, improving the decision making capability. The principle of integrating more data streams from deployed on-farm systems, for example, with feed composition data measured at the point of delivery using instrumented feeding wagons, supports the optimisation of feeding strategies and identification of the most productive animals. Optimised feeding strategies reduce operational costs and minimise waste whilst ensuring high welfare standards. These IoT-inspired solutions, made possible through Internet-enabled cloud data exchange, have the potential to make a major impact within farming practices. This paper gives illustrative examples and considers where new sensor technology from the automotive industry may also have a role

Contrasting effects of high-starch and high-sugar diets on ruminal function in cattle

The experiment reported in this research paper aimed to determine whether clinical and subclinical effects on cattle were similar if provided with isoenergetic and isonitrogenous challenge diets in which carbohydrate sources were predominantly starch or sugar. The study was a 3 × 3 Latin square using six adult Jersey cows with rumen cannulae, over 9 weeks. In the first 2 weeks of each 3 week experimental period cows were fed with a maintenance diet and, in the last week, each animal was assigned to one of three diets: a control diet (CON), being a continuation of the maintenance diet; a high starch (HSt) or a high sugar (HSu) diet. Reticuloruminal pH and motility were recorded throughout the study period. Blood and ruminal samples were taken on day-1 (TP-1), day-2 (TP-2) and day-7 (TP-7) of each challenge week. Four clinical variables were recorded daily: diarrhoea, inappetence, depression and ruminal tympany. The effects of treatment, hour of day and day after treatment on clinical parameters were analysed using linear mixed effects (LME) models. Although both challenge diets resulted in a decline in pH, an increase in the absolute pH residuals and an increase in the number of minutes per day under pH 5.8, systemic inflammation was only detected with the HSt diet. The challenge diets differentially modified amplitude and period of reticuloruminal contractions compared with CON diet and both were associated with an increased probability of diarrhoea. The HSu diet reduced the probability of an animal consuming its complete allocation. Because the challenge diets were derived from complex natural materials (barley and molasses respectively), it is not possible to assign all the differential effects to the difference in starch and sugar concentration: non-starch components of barley or non-sugar components of molasses might have contributed to some of the observations. In conclusion, substituting much of the starch with sugar caused no substantial reduction in the acidosis load, but inflammatory response was reduced while feed rejection was increased

The Kennicutt-Schmidt Star Formation Relation at z~2

Recent observations of excited CO emission lines from z~2 disc galaxies have shed light on the Kennicutt-Schmidt relation at high-z via observed SFR-CO (J=2-1) and (J=3-2) relations. Here, we describe a novel methodology for utilising these observations of high-excitation CO to derive the underlying Schmidt (SFR-rho^N) relationship. To do this requires an understanding of the potential effects of differential CO excitation with SFR. If the most heavily star-forming galaxies have a larger fraction of their gas in highly excited CO states than the lower SFR galaxies, then the observed molecular SFR-CO^alpha index, alpha, will be less than the underlying (volumetric) Schmidt index, N. Utilising a combination of SPH models of galaxy evolution and molecular line radiative transfer, we present the first calculations of CO excitation in z~2 disc galaxies with the aim of developing a mapping between various observed SFR-CO relationships and the underlying Schmidt relation. We find that even in relatively luminous z~2 discs, differential excitation does indeed exist, resulting in alpha < N for highly excited CO lines. This means that an observed (e.g.) SFR-CO (J=3-2) relation does not map linearly to SFR-H2 relation. We utilise our model results to provide a mapping from alpha to N for the range of Schmidt indices N=1-2. By comparing to recent observational surveys, we find that the observed SFR-CO (J=2-1) and SFR-CO (J=3-2) relations suggest that an underlying SFR rho^1.5 relation describes z~2 disc galaxies.Comment: Accepted by MNRAS, a few figure additions in response to referee repor