A GIS approach towards estimating tourist's off-road use in a mountainous protected area of Northwest Yunnan, China

To address the environmental impacts of tourism in protected areas, park managers need to understand the spatial distribution of tourist use. Standard monitoring measures (tourist surveys and counting and tracking techniques) are not sufficient to accomplish this task, in particular for off-road travel. This article predicts tourists' spatial use patterns through an alternative approach: park accessibility measurement. Naismith's rule and geographical information system's anisotropic cost analysis are integrated into the modeling process, which results in a more realistic measure of off-road accessibility than that provided by other measures. The method is applied to a mountainous United Nations Educational, Scientific and Cultural Organization (UNESCO) World Heritage Site in northwest Yunnan Province, China, where there is increasing concern about potential impacts of unregulated tourist use. Based on the assumption that accessibility tends to attract more tourists, a spatial pattern of predicted off-road use by tourists is derived. This pattern provides information that can help park managers develop strategies that are effective for both tourism management and species conservation

The spin-down accretion regime of Galactic ultra-luminous X-ray pulsar Swift J0243.6+6124

The relative high fluxes of the Galactic ultra-luminous X-ray pulsar Swift J0243 allow a detailed study of its spin-down regime in quiescence state, for a first time. After the 2017 giant outburst, its spin frequencies show a linear decreasing trend with some variations due to minor outbursts. The linear spin-down rate is $\sim-1.9\times10^{-12}$ Hz/s during the period of lowest luminosity, from which one can infer a dipole field $\sim1.75\times10^{13}$ G. The $\dot{\nu}-L$ relation during the spin-down regime is complex, and the $\dot{\nu}$ is close to 0 when the luminosity reaches both the high end ($L_{38}\sim0.3$) and the lowest value ($L_{38}\sim0.03$). The luminosity of zero-torque is different for the giant outburst and other minor outbursts. It is likely due to different accretion flows for different types of outburst, as evidenced by the differences of the spectra and pulse profiles at a similar luminosity for different types of outburst (giant or not). The pulse profile changes from double peaks in the spin-up state to a single broad peak in the low spin-down regime, indicating the emission beam/region is larger in the low spin-down regime. These results show that accretion is still ongoing in the low spin-down regime for which the neutron star is supposed to be in a propeller state.Comment: 7 pages, 7 figs, to appear in ApJ, comments welcom

Designing Gunslinger: An Intermodal Large Display Interaction

In this thesis, we introduce Gunslinger, a mid-air barehand interaction technique using hand postures to trigger command modes and small finger and hand movements for events and parameter control. Unlike past work, Gunslinger uses an 'arms down' body stance where both sets of fingers are tracked in mid-air with thigh-mounted sensors. This stance not only makes input more subtle and less fatiguing, but two-handed input and the reduced physical space needed to perform gestures makes it more compatible with large display touch input. The design of Gunslinger follows guidelines for relaxed barehand input that ensure that users can interact comfortably in mid-air without sacrificing the expressiveness of the interaction technique. We also provide continuous feedback about the hand sensing and posture recognition to ensure that the user never has to switch his visual attention to understanding the system's responses. An implemented interaction vocabulary is described for map navigation which demonstrates how Gunslinger can be combined with touch input supported by a touch hand inference method leveraging the arms-down form factor. And we show how this can be achieved with an input vocabulary that is equivalent, coherent, and compatible across mid-air and touch input modalities. We conducted a four-part study to evaluate Gunslinger for resilience to Midas Touch, posture recognition quality with hand cursor feedback, distant pointing and clicking performance, and general usability for Gunslinger alone and when mixed with touch input. We present the results of the study which show that Gunslinger has little Midas touch, reliable posture detection, good pointing throughput, and acceptable usability, even compared to faster touch input. In addition, we implemented and evaluated a rollback mechanism in order to address a stability issue arising from the study. Finally, we summarize our findings and describe extended studies to work on in the future

A gaussian process-based multi-sensor metrology system for precision measurement of freeform surfaces

Nowadays, precision freeform surfaces play an important role since they have superior performance and indispensable functionalities. Due to their geometrical complexity, high form accuracy and low surface roughness, precision freeform surfaces introduce a lot of research challenges in precision manufacturing and measurement processes. This is particularly true when the measurement is performed on traditional off-line single-sensor instruments such as white light interferometers (WLIs) and coordinate measuring machines (CMMs) whose measurement abilities are limited. For a single-sensor instrument, the measurement range and measurement resolution always need to strike a balance since the two terms appear to be contradictory. Moreover, when the workpiece is extremely large and error compensation procedure is needed to correct the form error of the workpiece, it is necessary to perform the measurement on machining facilities since repositioning error is unacceptable. However, off-line based measurement instruments cannot fulfil the in-situ measurement requirement. To address the above issues, this research firstly established a generic Gaussian process data modelling and image registration-based stitching method for the measurement of precision freeform surfaces based on traditional single-sensor surface measurement instruments using multiple measurement methods. With the proposed method, a dataset with a large measurement range and high resolution can be obtained. The proposed stitching method provides a turn-key solution for high dynamic range measurement using single-sensor instruments with a multiple measurement method. For multi-sensor instruments such as multi-sensor coordinate measuring machines (CMMs), this study proposes a Gaussian process-based data modelling and maximum likelihood data fusion method for the measurement of freeform surfaces for multi-sensor CMMs. The method utilizes an optical sensor such as laser sensor and a touch trigger probe mounted on the multi-sensor coordinate measuring machine for the measurement of freeform surfaces, and the measurement data are modelled using the Gaussian process modelling method. The combination of different kinds of sensors balances the measurement efficiency and accuracy since most optical sensors have a fast measurement speed and high density but low accuracy while contact sensors have an accurate measurement result but low efficiency. The measurement datasets from the laser sensor and touch trigger probe were fused with a maximum likelihood method so as to reduce the overall measurement uncertainty. To address the in-situ measurement issue, this thesis proposes an autonomous multi-sensor in-situ metrology system for high dynamic range measurement of freeform surfaces for precision machine tools. The system utilizes a laser scanner and a motion sensor together with a designed trajectory so as to perform in-situ measurement on the machining facilities. The proposed system is independent of the machining facilities which makes it extendable to a wide range of industrial applications. Based on the theory developed for the autonomous multi-sensor in-situ metrology system, a homogeneous multi-sensor in-situ measurement metrology system was developed equipped with a laser line sensor and laser point sensor. The laser line sensor provides high lateral resolution data while the laser point sensor gives accurate data. The measurement data from these two kinds of sensors are fused to obtain a more accurate result without losing the high lateral resolution. The present study has very large potential applications in industry. The successful development of the Gaussian process and image registration-based stitching method provides an important means for high dynamic range measurement, while the Gaussian process-based data modelling and maximum likelihood-based data fusion method establishes a generic measurement strategy for multi-sensor coordinate measuring machines so as to improve the measurement accuracy for precision freeform surfaces. The proposed in-situ multi-sensor high dynamic range measurement method and hence the homogeneous multi-sensor in-situ metrology system enable the measurement ability of machine tools so as to improve the efficiency and accuracy of the precision manufacture of complex freeform surfaces. The outcome of the research contributes significantly to the measurement science and technology, especially in the field of multi-sensor measurement and in-situ measurement of precision freeform surfaces

AI-powered in-process surface measurement based on light scattering

Surface measurement using scattered light has attracted much attention as it has many advantages, such as high speed, robustness and long working distances. However, the inverse problem to determine the surface geometry from the scattering signal is complex and it is difficult to find solution with complex surfaces. To address this issue, we propose a novel method powered by artificial intelligence (AI), combining a rigorous light scattering model, which can address the reverse problem effectively. We demonstrate the method with a prototype system. In the system, a machine learning platform based on a densely connected neural network was designed and trained by simulating thousands of surfaces and their associated far-field scattering signals with different combinations of parameters. Thus, the machine learning model can recognise any unseen scattering signal that falls within the range of the simulation parameters. Laser light was projected onto the surface and was scattered and recorded by a sensor. The scattering signal was fed into the machine learning model and the characteristics of the surface being measured can be output directly. Experimental results show that the proposed method can measure surfaces with high accuracy, robustness and efficiency. We expect the method will be widely adapted in various in-process industrial applications

Gene regulation and function of ICP0 in herpes simplex virus infected cells

Herpes simplex virus (HSV) is a clinically important virus, whose life cycle alternates between productive replication and latency. Infected cell protein 0 (ICP0) is generally believed to play a key role in determining the outcome of HSV infections. Synthesis of ICP0 promotes the productive replication of HSV, whereas absence of ICP0 renders HSV prone to establish latent infections. In the first part of the dissertation, I attempt to address the question how is ICP0 gene regulated. To tackle this question, we constructed recombinant HSV that encodes GFP-tagged ICP0 so that the regulation of ICP0 gene can be visualized in real time. Using this reagent, we found that ICP0 gene was subject to potent repression immediately following infection. Surprisingly, HSV\u27s major transcriptional regulator, ICP4, was necessary and sufficient to repress ICP0 gene, and did so in an ICP4-binding-site dependent manner. Synthesis of ICP0 alleviated the ICP4-dependent repression of ICP0 gene. ICP4 co-immunoprecipitated with FLAG-tagged ICP0, thus, a physical interaction between ICP0 and ICP4 likely explains how ICP0 antagonizes ICP4\u27s capacity to silence the ICP0 gene. Therefore, our findings suggest that ICP0 gene is differentially regulated by virus-encoded repressor ICP4 and virus-encoded antirepressor ICP0. In the second part of the dissertation, I attempt to address the question what function does ICP0 assume. Since the discovery of ICP0, the nuclear function of ICP0 has been the focal point of studies, whereas the cytoplasmic function of ICP0 is unknown. While pursuing our first study, we unexpectedly found that GFP-tagged ICP0 was predominantly localized to the cytoplasm during infections. Taking advantage of live-cell imaging, we found that ICP0 translocated from nucleus to cytoplasm during early phase of HSV infections, where it bundled and dispersed microtubules. Synthesis of ICP0 was proved to be necessary and sufficient to dismantle microtubules in HSV-infected and transfected cells. Therefore, our findings suggest ICP0 might play a previously unrecognized role in the cytoplasm through dismantling microtubule networks of the host cells. Furthermore, our study represents the first report showing a virus-encoded E3 ligase disrupts host cell microtubule networks, thus suggests a general function of many other viral E3 ligases

C algebraic Higher Signatures on Non-Witt Spaces

Signature plays an important role in geometry and topology. In the space with singularity, Goresky and MacPherson extend the signatures to oriented pseudomanifolds with only even codimensional stratums by using generalized Poincare duality of intersection homology. After that Siegel extended the signature on Witt spaces. Higson and Xie study the C ∗ - higher signature on Witt space. Non-Witt spaces need a refined intersection homology to hold Poincare duality. Followed by the combinatorial framework developed by Higson and Roe, this dissertation construct the C ∗ -signature on non Witt space with noncommutative geometric methods. In conical singular case, we compare analytical signature of smooth stratified non Witt space by Albin, Leichtnam, Mazzeo and Piazza

A fiducial-aided data fusion method for the measurement of multiscale complex surfaces

Multiscale complex surfaces, possessing high form accuracy and geometric complexity, are widely used for various applications in fields such as telecommunications and biomedicines. Despite the development of multi-sensor technology, the stringent requirements of form accuracy and surface finish still present many challenges in their measurement and characterization. This paper presents a fiducial-aided data fusion method (FADFM), which attempts to address the challenge in modeling and fusion of the datasets from multiscale complex surfaces. The FADFM firstly makes use of fiducials, such as standard spheres, as reference data to form a fiducial-aided computer-aided design (FA-CAD) of the multiscale complex surface so that the established intrinsic surface feature can be used to carry out the surface registration. A scatter searching algorithm is employed to solve the nonlinear optimization problem, which attempts to find the global minimum of the transformation parameters in the transforming positions of the fiducials. Hence, a fused surface model is developed which takes into account both fitted surface residuals and fitted fiducial residuals based on Gaussian process modeling. The results of the simulation and measurement experiments show that the uncertainty of the proposed method was up to 3.97 × 10 −5 μm based on a surface with zero form error. In addition, there is a 72.5% decrease of the measurement uncertainty as compared with each individual sensor value and there is an improvement of more than 36.1% as compared with the Gaussian process-based data fusion technique in terms of root-mean-square (RMS) value. Moreover, the computation time of the fusion process is shortened by about 16.7%. The proposed method achieves final measuring results with better metrological quality than that obtained from each individual dataset, and it possesses the capability of reducing the measurement uncertainty and computational cost