Delineating Intra-Urban Spatial Connectivity Patterns by Travel-Activities: A Case Study of Beijing, China

Travel activities have been widely applied to quantify spatial interactions between places, regions and nations. In this paper, we model the spatial connectivities between 652 Traffic Analysis Zones (TAZs) in Beijing by a taxi OD dataset. First, we unveil the gravitational structure of intra-urban spatial connectivities of Beijing. On overall, the inter-TAZ interactions are well governed by the Gravity Model $G_{ij} = {\lambda}p_{i}p_{j}/d_{ij}$, where $p_{i}$, $p_{j}$ are degrees of TAZ $i$, $j$ and $d_{ij}$ the distance between them, with a goodness-of-fit around 0.8. Second, the network based analysis well reveals the polycentric form of Beijing. Last, we detect the semantics of inter-TAZ connectivities based on their spatiotemporal patterns. We further find that inter-TAZ connections deviating from the Gravity Model can be well explained by link semantics.Comment: 6 pages, 4 figure

Dynamic multi-resource monitoring for predictive job scheduling.

Standard job schedulers rely on either the user\u27s estimation, or a few approaches that use performance databases to keep information about job runtimes to predict future runs. Co-scheduling for improved resource utilization, however, requires more detailed information as regards behavior on multiple resources to make predictions about slowdowns. Thus, information about communication, I/O, and computation at application level is needed but hard to estimate by the user. Furthermore, dynamic adaptive resource allocation requires information about the different processes on different machine nodes. We present an intelligent monitoring tool, ScoPro, which provides such information. To make monitoring more feasible, ScoPro harnesses the dynamic instrument techniques, which postpone insertion of instrumentation code until the application is executing. To keep intrusion low, we limit monitoring to short test phases. (Abstract shortened by UMI.)Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .L586. Source: Masters Abstracts International, Volume: 44-03, page: 1407. Thesis (M.Sc.)--University of Windsor (Canada), 2005

Clinicopathological investigations of the cholinergic basal forebrain in Lewy body disorders and ageing

Cholinergic dysfunction has long been associated with cognitive impairment in Alzheimer’s disease (AD). However, neuropathological and functional imaging studies have also found significant cortical cholinergic deficit in Lewy body disorders (LBD), but in a different pattern from that in AD. There is topographical cholinerigic innervation to the cortex and the hippocampus from the basal forebrain. In light of differences in cognitive deficits seen in LBD and AD, I hypothesised that cholinergic basal forebrain subregions are differentially affected in these disorders. In this thesis, novel tissue techniques have been developed for the visualisation of pathology in human post-mortem brain tissue in three-dimensions. Based on a thorough review of the literature and my personal observations, I have established a simplified subdivisional scheme of the nucleus basalis of Meynert (nbM) in the human brain. Using this scheme, a quantification of nbM cholinergic neurons and assessment of neuropathological burden were performed in a large cohort of LBD and AD cases. Severe neuronal depletion across the entire nbM was observed in LBD with cognitive impairment and relative sparing of the anterior nbM was found in AD, supporting findings from previous neuropathological and imaging studies. Further investigation was carried out in the more rostral, hippocampal-projecting cholinergic group in the vertical limb of the nucleus of the diagonal band of Broca. Significant neurodegeneration in this area was identified in LBD with cognitive impairment, but not AD, suggesting its possible role in retrieval memory function via projection to the hippocampal CA2 subfield. In the final section, it was demonstrated that lactacystin injection into the rat nbM can replicate certain pathological and clinical features of LBD with dementia and this may be a useful model for the disease. Results from these studies support my initial hypothesis regarding differential susceptibility of the basal forebrain subregions in LBD and AD.Open Acces

GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking

Large language models~(LLM) like ChatGPT have become indispensable to artificial general intelligence~(AGI), demonstrating excellent performance in various natural language processing tasks. In the real world, graph data is ubiquitous and an essential part of AGI and prevails in domains like social network analysis, bioinformatics and recommender systems. The training corpus of large language models often includes some algorithmic components, which allows them to achieve certain effects on some graph data-related problems. However, there is still little research on their performance on a broader range of graph-structured data. In this study, we conduct an extensive investigation to assess the proficiency of LLMs in comprehending graph data, employing a diverse range of structural and semantic-related tasks. Our analysis encompasses 10 distinct tasks that evaluate the LLMs' capabilities in graph understanding. Through our study, we not only uncover the current limitations of language models in comprehending graph structures and performing associated reasoning tasks but also emphasize the necessity for further advancements and novel approaches to enhance their graph processing capabilities. Our findings contribute valuable insights towards bridging the gap between language models and graph understanding, paving the way for more effective graph mining and knowledge extraction