Virus infection and host antiviral defense, a story between Israeli acute paralysis virus (IAPV) and bumblebees (Bombus terrestris)

The recent emerging of RNA viruses in bumblebees (Bombus spp.) caught scientific attention for its notorious reputation in another well-known pollinator species Apis mellifera. This calls for a comprehensive understanding of the interactions between these viruses and the bumblebee host. In this thesis, we investigated: 1) the symptom and tissue infection pattern of Israeli acute paralysis virus (IAPV) in bumblebee Bombus terrestris, 2) the involvement of the host innate immune system in the antiviral defense. 1) Systemic IAPV infection can be induced after both injecting and feeding of IAPV stock. During systemic infection, multiple B. terrestris tissues were infected and obvious paralysis symptoms (e.g. fore-legs paralysis) were observed. However, the occurrence of this paralysis symptoms cannot be explained by the virus tissue specific infections. 2) A single von Willebrand factor C-domain protein (SVC) was found to be involved in the antiviral defense of B. terrestris, which function is mediated by Dicer-2, a key component of the small interfering RNA (siRNA) pathway. Lower expression of antimicrobial peptides (AMP) genes were observed after SVC silencing, suggesting a potential links of SVC with AMPs. However, SVC does not seem to interact with AMPs induction upon IAPV infection. Besides, evidence of hemocytes necrosis but not apoptosis can be observed after IAPV infection in B. terrestris. Future studies towards understanding the role that cellular immunity plays in the host antiviral defense is needed

Animal stay region detection and behavior analysis based on GPS trajectories

Nowadays, GPS technology is becoming an important tool in tracking and understanding wild animal behaviors. For example, Missouri Department of Conservation (MDC) has put GPS collars on more than 80 black bears and more than 150 deer and collected a large amount of GPS data. In this project, several semantic analysis methods have been implemented and applied to GPS data provided by MDC. After the raw data are cleaned using outlier detection methods, stay regions in each GPS trajectory are detected using the SeqScan algorithm. Based on the stay regions, various statistics of individual animals and among different groups of animals, such as male and female, are generated to provide insights of animal behaviors and help answer questions that biologists are interested in. Multidimensional scaling technique is used to analyze and visualize relationships between different animals in terms of the overlaps of their stay regions. A software pipeline has been implemented to apply the proposed methods and a website has been created to show the results on Google map, which give the biologists a convenient tool to perform some quick analysis of raw GPS trajectories

Sex Mortality Differentials in the United States: The Role of Cohort Smoking Patterns

This paper demonstrates that, over the period 1948-2003, sex differentials in mortality in the age range 50-54 to 85+ widened and then narrowed on a cohort rather than on a period basis. The cohort with the maximum excess of male mortality was born shortly after the turn of the century. Three independent sources suggest that the turnaround in sex mortality differentials is consistent with sex differences in cigarette smoking by cohort. An age/period/cohort model reveals a highly significant effect of smoking histories on men’s and women’s mortality. This model suggests that improvements in mortality at older ages are likely to accelerate in the future

Generalized transfer matrix theory on electronic transport through graphene waveguide

In the effective mass approximation, electronic property in graphene can be characterized by the relativistic Dirac equation. Within such a continuum model we investigate the electronic transport through graphene waveguides formed by connecting multiple segments of armchair-edged graphene nanoribbons of different widths. By using appropriate wavefunction connection conditions at the junction interfaces, we generalize the conventional transfer matrix approach to formulate the linear conductance of the graphene waveguide in terms of the structure parameters and the incident electron energy. In comparison with the tight-binding calculation, we find that the generalized transfer matrix method works well in calculating the conductance spectrum of a graphene waveguide even with a complicated structure and relatively large size. The calculated conductance spectrum indicates that the graphene waveguide exhibits a well-defined insulating band around the Dirac point, even though all the constituent ribbon segments are gapless. We attribute the occurrence of the insulating band to the antiresonance effect which is intimately associated with the edge states localized at the shoulder regions of the junctions. Furthermore, such an insulating band can be sensitively shifted by a gate voltage, which suggests a device application of the graphene waveguide as an electric nanoswitch.Comment: 11 pages, 5 figure

Supply interruption supply chain network model with uncertain demand: an application of chance-constrained programming with fuzzy parameters

The downstream supply interruption of manufacturers is a disaster for the company when the demand is uncertain in the market; a fuzzy programming with fuzzy parameters model of supply interruption supply chain network is established by simulating market operation rules. The aim of the current study is to build a fuzzy chance-constrained programming method which is developed for supporting the uncertainty of demand. This method ensured that the fuzzy constraints can be satisfied at specified confidence levels, leading to cost-effective solutions under acceptable risk magnitudes. Finally, through the case of the electronic product manufacturing enterprise, the feasibility and effectiveness of the proposed model are verified by adopting a sensitivity analysis of capacity loss level and minimizing objective function. Numerical simulation shows that selecting two manufacturing centers can effectively reduce the supply chain cost and maintain business continuity

Quantum hypothesis testing via robust quantum control

Quantum hypothesis testing plays a pivotal role in quantum technologies, making decisions or drawing conclusions about quantum systems based on observed data. Recently, quantum control techniques have been successfully applied to quantum hypothesis testing, enabling the reduction of error probabilities in the task of distinguishing magnetic fields in presence of environmental noise. In real-world physical systems, such control is prone to various channels of inaccuracies. Therefore improving the robustness of quantum control in the context of quantum hypothesis testing is crucial. In this work, we utilize optimal control methods to compare scenarios with and without accounting for the effects of signal frequency inaccuracies. For parallel dephasing and spontaneous emission, the optimal control inherently demonstrates a certain level of robustness, while in the case of transverse dephasing with an imperfect signal, it may result in a higher error probability compared to the uncontrolled scheme. To overcome these limitations, we introduce a robust control approach optimized for a range of signal noise, demonstrating superior robustness beyond the predefined tolerance window. On average, both the optimal control and robust control show improvements over the uncontrolled schemes for various dephasing or decay rates, with the robust control yielding the lowest error probability.Comment: 20 pages, 6 figure