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Salmonella pathogenicity island (SPI) 2 type three secretion system (T3SS)-mediated effector molecules facilitate bacterial survival in phagocytes but their role in the intestinal epithelium in vivo remains ill-defined. Using our neonatal murine infection model in combination with SPI2 reporter technology and RNA-Seq of sorted primary enterocytes, we demonstrate expression of SPI2 effector molecules by intraepithelial Salmonella Typhimurium (S. Typhimurium). Contrary to expectation, immunostaining revealed that infection with SPI2 T3SS-mutants resulted in significantly enlarged intraepithelial Salmonella-containing vacuoles (SCV) with altered cellular positioning, suggesting impaired apical to basolateral transmigration. Also, infection with isogenic tagged S. Typhimurium strains revealed a reduced spread of intraepithelial SPI2 T3SS mutant S. Typhimurium to systemic body sites. These results suggest that SPI2 T3SS effector molecules contribute to enterocyte apical to basolateral transmigration of the SCV during the early stage of the infection.

Salmonella pathogenicity island (SPI) 2 type three secretion system (T3SS)-mediated effector molecules facilitate bacterial survival in phagocytes but their role in the intestinal epithelium in vivo remains ill-defined. Using our neonatal murine infection model in combination with SPI2 reporter technology and RNA-Seq of sorted primary enterocytes, we demonstrate expression of SPI2 effector molecules by intraepithelial Salmonella Typhimurium (S. Typhimurium). Contrary to expectation, immunostaining revealed that infection with SPI2 T3SS-mutants resulted in significantly enlarged intraepithelial Salmonella-containing vacuoles (SCV) with altered cellular positioning, suggesting impaired apical to basolateral transmigration. Also, infection with isogenic tagged S. Typhimurium strains revealed a reduced spread of intraepithelial SPI2 T3SS mutant S. Typhimurium to systemic body sites. These results suggest that SPI2 T3SS effector molecules contribute to enterocyte apical to basolateral transmigration of the SCV during the early stage of the infection.

Rapid urbanization poses huge challenges to people's daily lives, such as traffic congestion, environmental pollution, and public safety. Mobile Internet of things (MIoT) applications serving smart cities bring the promise of innovative and enhanced public services such as air pollution monitoring, enhanced road safety and city resources metering and management. These applications rely on a number of energy constrained MIoT units (MUs) (e.g., robots and drones) to continuously sense, capture and process data and images from their environments to produce immediate adaptive actions (e.g., triggering alarms, controlling machinery and communicating with citizens). In this thesis, we consider a scenario where a battery constrained MU executes a number of time-sensitive data processing tasks whose arrival times and sizes are stochastic in nature. These tasks can be executed locally on the device, offloaded to one of the nearby edge servers or to a cloud data center within a mobile edge computing (MEC) infrastructure. We first formulate the problem of making optimal offloading decisions that minimize the cost of current and future tasks as a constrained Markov decision process (CMDP) that accounts for the constraints of the MU battery and the limited reserved resources on the MEC infrastructure by the application providers. Then, we relax the CMDP problem into regular Markov decision process (MDP) using Lagrangian primal-dual optimization. We then develop advantage actor-critic (A2C) algorithm, one of the model-free deep reinforcement learning (DRL) method to train the MU to solve the relaxed problem. The training of the MU can be carried-out once to learn optimal offloading policies that are repeatedly employed as long as there are no large changes in the MU environment. Simulation results are presented to show that the proposed algorithm can achieve performance improvement over offloading decisions schemes that aim at optimizing instantaneous costs.

Benefited from the efficiency of hydraulic fracturing and horizon drilling, the production of unconventional oil and gas resources, such as shale gas and tight oil, has grown quickly in 21th century and contributed to the North America oil and gas production. Although the new enhancing oil recover (EOR) technologies and strong demand spike the production of unconventional resources, there are still unknowns in recovery mechanisms and phase behavior in tight rock reservoirs. In such environment, the phase behavior is altered by high capillary pressure owing to the nanoscale pore throats of shale rocks and it may also influence minimum miscibility pressure (MMP), which is an important parameter controlling gas floods for CO2 injection EOR. To investigate this influence, flash calculation is modified with considering capillary pressure and this work implements three different method to calculate MMP: method of characteristics (MOC); multiple mixing cell (MMC); and slim-tube simulation. The results show that CO2 minimum miscibility pressure in nanopore size reservoirs are affected by gas-oil capillary pressure owing to the alternation of key tie lines in displacement. The values of CO2-MMP from three different methods match well. Moreover, in tight rock reservoirs, the heterogeneous pore size distribution, such as the ones seen in fractured reservoirs, may affect the recovery mechanisms and MMP. This work also investigates the effect of pore size heterogeneity on multicomponent multiphase hydrocarbon fluid composition distribution and its subsequent influence on mass transfer through shale nanopores. According to the simulation results, compositional gradient forms in heterogeneous nanopores of tight reservoirs because oil and gas phase compositions depend on the pore size. Considering that permeability is small in tight rocks and shales, we expect that mass transfer within heterogeneous pore size porous media to be diffusion-dominated. Our results imply that there can be a selective matrix-fracture component mass transfer during both primary production and gas injection secondary recovery in fractured shale rocks. Therefore, molecular diffusion should not be neglected from mass transfer equations for simulations of gas injection EOR or primary recovery of heterogeneous shale reservoirs with pore size distribution. Master of Science The new technologies to recover unconventional resources in oil and gas industry, such as fracturing and horizontal drilling, boosted the production of shale gas and tight oil in 21st century and contributed to the North America oil and gas production. Although the new technologies and strong demand spiked the production of tight oil resources, there are still unknowns of oil and gas flow mechanisms in tight rock reservoirs. As we know, the oil and gas resources are stored in the pores of reservoir formation rock. During production process, the oil and gas are pushed into production wells by formation pressure. However, the pore radius of shale rock is extremely small (around nanometers), which reduces the flow rate of oil and gas and raises capillary pressure in pores. The high capillary pressure will alter the oil and gas phase behavior and it may influence the value of minimum miscibility pressure (MMP), which is an important design parameter for CO2 injection (an important technology to raise production). To investigate this influence, we changed classical model with considering capillary pressure and this modified model is implemented in different methods to calculate MMP. The results show that CO2 -MMP in shale reservoirs are affected by capillary pressure and the results from different methods match well. Moreover, in tight rock reservoirs, the heterogeneous pore size distribution, such as fractures in reservoirs, may affect the flow of oil and gas and MMP value. So, this work also investigates the effect of pore size heterogeneity on oil and gas flow mechanisms. According to the simulation results, compositional gradient forms in heterogeneous nanopores of tight reservoirs and this gradient will cause diffusion which will dominate the other fluid flow mechanisms. Therefore, we always need to consider molecular diffusion in the simulation model for shale reservoirs.