99 research outputs found
Inter-municipal relations in city-region governance
City-regions have received increasing attention from both scholars and policy-makers as an ideal functional space for economic development and subnational governance. The discourses of city-region governance predominantly focus on city-regions' capacity to achieve agglomerative growth and compete in the global economy. Given that consensus-building and joint working is central to city-regions' success, the inter-municipal relations and territorial politics within a city-region warrant research attention. This study investigates such relations in urban regeneration and place marketing policy areas through a case study of an inner-city waterfront district in Greater Manchester, North-West England. The nuanced findings of this study show the relationships between the local authorities were path-dependent and were often driven by self-interest, competition and rivalry. The study encourages scholars to take into account internal territorial politics when assessing the evolution of city-region governance for a more context specific analysis
Boundaries and boundary crossing in tourism: A study of policy work for tourism and urban regeneration
The paper argues for a research focus on understanding varied boundary relations in
society, including social, political, geographical and discursive relations. Analytical
themes are established for the study of tourism’s boundary relations: the salience
and permeability of boundaries, discursive boundaries, power relations associated
with boundaries, and learning within and across boundaries. Particular attention is
14 given to concepts of learning: identification, reflection, coordination and
transformation. These themes and concepts are employed to explore boundary
relations of the tourism and other urban regeneration policy sectors in two city
districts. Cross-boundary learning across the tourism and urban regeneration policy
sectors occurred through the identification of, and reflection about, tourism's role in
urban regeneration and led to coordination and possibly some transformation. Yet
this was within significant limitations and barriers. There was perhaps scope for
more regular and comprehensive boundary crossing between the tourism and urban
regeneration policy sectors
An Analysis of First Time and Repeat-Visitor Destination Images through the Prism of the Three Factor Theory of Consumer Satisfaction
The study examines first time and repeat visitor primary destination images through the prism
of the factor theory of consumer satisfaction to expose the positive-negative asymmetry of
their relationship with overall visitor satisfaction and word-of-mouth recommendation, and
the differential impact of factor type on first time visitors and repeaters. It also subdivides
repeat visitors on the basis of revisit frequency to reveal significant differences between
repeater subgroups and between first time visitors and high frequency repeaters, which have
been overlooked in previous research. Combining this theoretical approach with the
examination of repeater heterogeneity has revealed the criticality of the destination's basic
and performance factors; the former are potentially critical constraints on re-visitation for the
large majority of visitors, while many of the latter have a positive impact on satisfaction and
visitor recommendation but also have a disproportionately greater negative impact when their
performance is poor. Recommendations are made for the management and marketing of the
destination's image attributes in line with first time visitor and repeater requirements
Listeria motility increases the efficiency of epithelial invasion during intestinal infection
Listeria monocytogenes (Lm) is a food-borne pathogen that causes severe bacterial gastroenteritis, with high rates of hospitalization and mortality. Lm is ubiquitous in soil, water and livestock, and can survive and proliferate at low temperatures. Following oral ingestion of contaminated food, Lm crosses the epithelium through intestinal goblet cells in a mechanism mediated by Lm InlA binding host E-cadherin. Importantly, human infections typically occur with Lm growing at or below room temperature, which is flagellated and motile. Even though many important human bacterial pathogens are flagellated, little is known regarding the effect of Lm motility on invasion and immune evasion. Here, we used complementary imaging and computer modeling approaches to test the hypothesis that bacterial motility helps Lm locate and engage target cells permissive for invasion. Imaging explanted mouse and human intestine, we showed that Lm grown at room temperature uses motility to scan the epithelial surface and preferentially attach to target cells. Furthermore, we integrated quantitative parameters from our imaging experiments to construct a versatile layered cellular Potts model (L-CPM) that simulates host-pathogen dynamics. Simulated data are consistent with the hypothesis that bacterial motility enhances invasion by allowing bacteria to search the epithelial surface for their preferred invasion targets. Indeed, our model consistently predicts that motile bacteria invade twice as efficiently over the first hour of infection. We also examined how bacterial motility affected interactions with host cellular immunity. In a mouse model of persistent infection, we found that neutrophils migrated to the apical surface of the epithelium 5 hours post infection and interacted with Lm. Yet in contrast to the view that neutrophils hunt for bacteria, we found that these interactions were driven by motility of Lm-which moved at least ~50x faster than neutrophils. Furthermore, our L-CPM predicts that motile bacteria maintain their invasion advantage even in the presence of host phagocytes, with the balance between invasion and phagocytosis governed almost entirely by bacterial motility. In conclusion, our simulations provide insight into host pathogen interaction dynamics at the intestinal epithelial barrier early during infection
Machine learning approaches for detecting tropical cyclone formation using satellite data
This study compared detection skill for tropical cyclone (TC) formation using models based on three different machine learning (ML) algorithms-decision trees (DT), random forest (RF), and support vector machines (SVM)-and a model based on Linear Discriminant Analysis (LDA). Eight predictors were derived from WindSat satellite measurements of ocean surface wind and precipitation over the western North Pacific for 2005-2009. All of the ML approaches performed better with significantly higher hit rates ranging from 94 to 96% compared with LDA performance (~77%), although false alarm rate by MLs is slightly higher (21-28%) than that by LDA (~13%). Besides, MLs could detect TC formation at the time as early as 26-30 h before the first time diagnosed as tropical depression by the JTWC best track, which was also 5 to 9 h earlier than that by LDA. The skill differences across MLs were relatively smaller than difference between MLs and LDA. Large yearly variation in forecast lead time was common in all models due to the limitation in sampling from orbiting satellite. This study highlights that ML approaches provide an improved skill for detecting TC formation compared with conventional linear approaches
Multivalent electrostatic pi–cation interaction between synaptophysin and synapsin is responsible for the coacervation
We recently showed that synaptophysin (Syph) and synapsin (Syn) can induce liquid–liquid phase separation (LLPS) to cluster small synaptic-like microvesicles in living cells which are highly reminiscent of SV cluster. However, as there is no physical interaction between them, the underlying mechanism for their coacervation remains unknown. Here, we showed that the coacervation between Syph and Syn is primarily governed by multivalent pi–cation electrostatic interactions among tyrosine residues of Syph C-terminal (Ct) and positively charged Syn. We found that Syph Ct is intrinsically disordered and it alone can form liquid droplets by interactions among themselves at high concentration in a crowding environment in vitro or when assisted by additional interactions by tagging with light-sensitive CRY2PHR or subunits of a multimeric protein in living cells. Syph Ct contains 10 repeated sequences, 9 of them start with tyrosine, and mutating 9 tyrosine to serine (9YS) completely abolished the phase separating property of Syph Ct, indicating tyrosine-mediated pi-interactions are critical. We further found that 9YS mutation failed to coacervate with Syn, and since 9YS retains Syphs negative charge, the results indicate that pi–cation interactions rather than simple charge interactions are responsible for their coacervation. In addition to revealing the underlying mechanism of Syph and Syn coacervation, our results also raise the possibility that physiological regulation of pi–cation interactions between Syph and Syn during synaptic activity may contribute to the dynamics of synaptic vesicle clustering.This work was supported by grants from the National Research Foundation of Korea (Grants 2019R1A2C2089182 to S.C.). This work was also supported by the Education and Research Encouragement Fund of Seoul National University Hospital
Downscaling GLDAS Soil Moisture Data in East Asia through Fusion of Multi-Sensors by Optimizing Modified Regression Trees
Soilmoisture is a key part of Earth's climate systems, including agricultural and hydrological cycles. Soil moisture data from satellite and numerical models is typically provided at a global scale with coarse spatial resolution, which is not enough for local and regional applications. In this study, a soil moisture downscaling model was developed using satellite-derived variables targeting Global Land Data Assimilation System (GLDAS) soil moisture as a reference dataset in East Asia based on the optimization of a modified regression tree. A total of six variables, Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced SCATterometer (ASCAT) soil moisture products, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and MODerate resolution Imaging Spectroradiometer (MODIS) products, including Land Surface Temperature, Normalized Difference Vegetation Index, and land cover, were used as input variables. The optimization was conducted through a pruning approach for operational use, and finally 59 rules were extracted based on root mean square errors (RMSEs) and correlation coefficients (r). The developed downscaling model showed a good modeling performance (r = 0.79, RMSE = 0.056 m(3)center dot m(3), and slope = 0.74). The 1 km downscaled soil moisture showed similar time series patterns with both GLDAS and ground soil moisture and good correlation with ground soil moisture (average r = 0.47, average RMSD = 0.038 m(3)center dot m(3)) at 14 ground stations. The spatial distribution of 1 km downscaled soil moisture reflected seasonal and regional characteristics well, although the model did not result in good performance over a few areas such as Southern China due to very high cloud cover rates. The results of this study are expected to be helpful in operational use to monitor soil moisture throughout East Asia since the downscaling model produces daily high resolution (1 km) real time soil moisture with a low computational demand. This study yielded a promising result to operationally produce daily high resolution soil moisture data from multiple satellite sources, although there are yet several limitations. In future research, more variables including Global Precipitation Measurement (GPM) precipitation, Soil Moisture Active Passive (SMAP) soil moisture, and other vegetation indices will be integrated to improve the performance of the proposed soil moisture downscaling model.ope
Phagocytes produce prostaglandin E2 in response to cytosolic Listeria monocytogenes
Listeria monocytogenes is an intracellular bacterium that elicits robust CD8+ T-cell responses. Despite the ongoing development of L. monocytogenes-based platforms as cancer vaccines, our understanding of how L. monocytogenes drives robust CD8+ T-cell responses remains incomplete. One overarching hypothesis is that activation of cytosolic innate pathways is critical for immunity, as strains of L. monocytogenes that are unable to access the cytosol fail to elicit robust CD8+ T-cell responses and in fact inhibit optimal T-cell priming. Counterintuitively, however, activation of known cytosolic pathways, such as the inflammasome and type I IFN, lead to impaired immunity. Conversely, production of prostaglandin E2 (PGE2) downstream of cyclooxygenase-2 (COX-2) is essential for optimal L. monocytogenes T-cell priming. Here, we demonstrate that vacuole-constrained L. monocytogenes elicit reduced PGE2 production compared to wild-type strains in macrophages and dendritic cells ex vivo. In vivo, infection with wild-type L. monocytogenes leads to 10-fold increases in PGE2 production early during infection whereas vacuole-constrained strains fail to induce PGE2 over mock-immunized controls. Mice deficient in COX-2 specifically in Lyz2+ or CD11c+ cells produce less PGE2, suggesting these cell subsets contribute to PGE2 levels in vivo, while depletion of phagocytes with clodronate abolishes PGE2 production completely. Taken together, this work demonstrates that optimal PGE2 production by phagocytes depends on L. monocytogenes access to the cytosol, suggesting that one reason cytosolic access is required to prime CD8+ T-cell responses may be to facilitate production of PGE2
Fe@N-Graphene Nanoplatelet-Embedded Carbon Nanofibers as Efficient Electrocatalysts for Oxygen Reduction Reaction
An activated carbon nanofiber (CNF) is prepared with incorporated Fe-N-doped graphene nanoplatelets (Fe@NGnPs), via a novel and simple synthesis approach. The activated CNF-Fe@NGnP catalysts exhibit substantially improved activity for the oxygen reduction reaction compared to those of commercial carbon blacks and Pt/carbon catalysts.clos
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