Optimal Incentive Contract with Endogenous Monitoring Technology

Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer's strategic planning. In otherwise standard principal-agent models with moral hazard, we allow the principal to partition agents' performance data into any finite categories and to pay for the amount of information the output signal carries. Through analysis of the trade-off between giving incentives to agents and saving the monitoring cost, we obtain characterizations of optimal monitoring technologies such as information aggregation, strict MLRP, likelihood ratio-convex performance classification, group evaluation in response to rising monitoring costs, and assessing multiple task performances according to agents' endogenous tendencies to shirk. We examine the implications of these results for workforce management and firms' internal organizations

New perspectives in mesospheric wave dynamics and oxygen photochemistry

The mesosphere is the region of the atmosphere between 50km to 100km, where both dynamical and photochemical aspects play important roles for the thermal balance. This thesis focuses on the following three areas for mesospheric studies: wave dynamics, oxygen photochemistry and retrieval using the optimal estimation method. Atmospheric gravity waves are internal disturbances in the medium that propagate horizontally and vertically. Based on linear wave theory, this thesis attempts to enhance our understanding of the relationships between the wave characteristics, the mean flow and the sources. We try to emphasise the frequency change due to the Doppler effect in several reference frames. This thesis proposes a consistent framework for deriving those wave parameters that cannot be obtained from a single type of instrument due to their particular observational geometry. Finally, a plausible interpretation of a readily available ground-based lidar observation is given as an example. Oxygen photochemistry is another important aspect in this thesis. The underlying chemical reactions are affected by disturbances in the local temperature and density, which in turn changes the distribution of the excited oxygen species. In this work, a photochemical model has been implemented, which describes most of the important processes such as O3 photolysis that are related to the production and loss of O(1D), O2(b1Σg+ ) and O2(a1∆g). The observation of airglow emissions provides an opportunity to explore the chemical composition and wave dynamics in the upper mesosphere. The Odin satellite has been routinely measuring O2(a1∆g) airglow emissions since 2001. In this thesis, data collected by OSIRIS are explored. Inversions are carried out in order to retrieve the volume emission rate of O2(a1∆g) as well as the mesospheric ozone density. The resulting ozone profiles are shown to be consistent with other independent ozone datasets collected by instruments aboard the same spacecraft as well as ACE-FTS and MIPAS, despite intrinsically different measurement principles. The overall good agreement between them illustrates the good performance of the retrieval technique. Furthermore, these investigations serve well as a preparatory activity for the upcoming satellite mission MATS, set for launch later this year

Investigating the origin of gas flows at the disc-halo interface of local galaxies

The evolution of galaxies is largely affected by interactions with the surrounding environment. For example, galaxies are believed to sustain their star formation, a process which consumes clouds of cold gas, by accreting gas from their external environment. On the other hand, stellar feedback processes, such as stellar winds and supernova explosions, can expel gas from the galaxy to large distances. The disc-halo interface (the region relatively close to the galactic discs but still thousands of light years from the disc plane) is the crucial transition point of the stellar feedback and gas accretion, and therefore a window to the complicated gas exchange processes. The gas layer located at the disc-halo interface is known as extraplanar gas. Understanding the origin of this gas layer is essential for a complete view of the gas cycle between galaxies and their surrounding environment, and is the main focus of this thesis. In this thesis, I have presented a detailed investigation of the extraplanar gas in a sample of four spiral galaxies, including the Milky Way. Both radio and optical data have been obtained to trace extraplanar gas at different temperatures. We found that the motion of extraplanar gas is similar to the rotating disc, although with a slower rotation velocity. The properties are broadly consistent with an internal origin of the galactic fountain (gas cycle triggered by stellar feedback) combined with gas accretion. For the galaxy NGC 2403, in particular, the above scenario predicted a gas accretion rate to support the star formation activity of this galaxy

O2 and OH airglow in the mesosphere through the lens of Odin/OSIRIS Infrared Imager

Observing airglow emissions allows us to explore the chemical composition and dynamics of the upper mesosphere. The Odin satellite has routinely measured O2(a1∆g) and OH Meinel band airglow emissions from 2001 until 2015. In this thesis, the Odin/OSIRIS infrared imager data have been studied in some depth for the first time. Numerical inversions of the observed radiances have been carried out to retrieve the volume emission rates and, thereafter, the mesospheric ozone density. This resulted in a new, long-term high-resolution airglow and ozone datasets of the middle atmosphere. The photolysis reactions are affected by periodic changes in solar irradiance. Thus, the OHv emission should vary with the solar cycle. In terms of the 11-year solar cycle, as expected, we observed that the vertically integrated intensity of OHv correlates positively with the Lyman-α flux and that the emission height correlates negatively at most latitudes except near the equator. Employing a time-dependent photochemical model, we showed that the changing local time sampling of the Odin satellite was the cause of the observed distortion of the solar cycle signature near the equator. We also observed the episodic signatures in the two airglow emissions of sudden stratospheric warming (SSW) events. With the aid of the temperature and H2O measured from Odin-SMR, we qualitatively assessed the events that occurred in 2009, 2012, and 2013. Using analytical expressions, we derived proxy O and OHv number densities. A significant amount of atomic oxygen-rich air descends into the mesosphere a few days after the SSW onsets, resulting in unusually intense airglow emissions at a much lower altitude than average. The modelled OHv largely resembles the temporal evolution of the observed OHv. The synchronous structure of the two airglow emissions indicates that the vertical transport of O plays a dominant role in the observed changes. This thesis work has set a valuable foundation as part of the preparations for the future MATS mission

MSIQ: Joint Modeling of Multiple RNA-seq Samples for Accurate Isoform Quantification

Next-generation RNA sequencing (RNA-seq) technology has been widely used to assess full-length RNA isoform abundance in a high-throughput manner. RNA-seq data offer insight into gene expression levels and transcriptome structures, enabling us to better understand the regulation of gene expression and fundamental biological processes. Accurate isoform quantification from RNA-seq data is challenging due to the information loss in sequencing experiments. A recent accumulation of multiple RNA-seq data sets from the same tissue or cell type provides new opportunities to improve the accuracy of isoform quantification. However, existing statistical or computational methods for multiple RNA-seq samples either pool the samples into one sample or assign equal weights to the samples when estimating isoform abundance. These methods ignore the possible heterogeneity in the quality of different samples and could result in biased and unrobust estimates. In this article, we develop a method, which we call "joint modeling of multiple RNA-seq samples for accurate isoform quantification" (MSIQ), for more accurate and robust isoform quantification by integrating multiple RNA-seq samples under a Bayesian framework. Our method aims to (1) identify a consistent group of samples with homogeneous quality and (2) improve isoform quantification accuracy by jointly modeling multiple RNA-seq samples by allowing for higher weights on the consistent group. We show that MSIQ provides a consistent estimator of isoform abundance, and we demonstrate the accuracy and effectiveness of MSIQ compared with alternative methods through simulation studies on D. melanogaster genes. We justify MSIQ's advantages over existing approaches via application studies on real RNA-seq data from human embryonic stem cells, brain tissues, and the HepG2 immortalized cell line