Search results

This study aims to develop a simplified bioink preparation method that can be applied to most hydrogel bioinks used in extrusion-based techniques.

The parameters of the bioprinting process significantly affect the printability of the bioink and the viability of cells. In turn, the bioink formulation and its physicochemical properties may influence the appropriate range of printing parameters. In extrusion-based bioprinting, the rheology of the bioink affects the printing pressure, cell survival and structural integrity. Three concentrations of alginate-gelatin hydrogel were prepared and printed at three different flow rates and nozzle gauges to investigate the print parameters. Other characterizations were performed to evaluate the hydrogel structure, printability, gelation time, swelling and degradation rates of the bioink and cell viability. An experimental design was used to determine optimal parameters. The analyses included live/dead assays, rheological measurements, swelling and degradation.

The experimental design results showed that the hydrogel flow rate substantially influenced printing accuracy and pressure. The best hydrogel flow rate in this study was 10 ml/h with a nozzle gauge of 18% and 4% alginate. Three different concentrations of alginate-gelatin hydrogels were found to exhibit shear-thinning behavior during printing. After seven days, 46% of the structure in the 4% alginate-5% gelatin sample remained intact. After printing, the viability of skin fibroblast cells for the optimized sample was 91%.

This methodology offers a straightforward bioink preparation method applicable to the majority of hydrogels used in extrusion-based procedures. This can also be considered a prerequisite for cell printing.

In urban planning, sustainability is closely linked to the quality of urban public spaces (UPS). However, some UPS encounter issues of low attractiveness and underutilisation. Vitality serves as a crucial measure in this context. The research perspective on the vitality of UPS centres on the balance between human activities and the built environment. Therefore, this article aims to systematically review critical aspects of UPS vitality evaluation system, including research objects, vitality components and research methods, from the dimensions of crowd activity and the built environment.

A systematic literature review using PRISMA analysed English-language publications from 2008 to 2023 in Scopus and Web of Science (WOS) databases, employing keywords related to UPS and vitality, with defined inclusion and exclusion criteria.

(1) Research objects, including parks, squares, waterfronts, blocks and streets. (2) The factors contributing to crowd activity characteristics originate from five dimensions, namely spatial, temporal, visitor, activity and feedback. Environmental factors, both external (accessibility, surrounding function mix and population density) and internal (service facility mix and water presence), significantly impact vitality. (3) The study primarily relies on quantitative data, including traditional surveys and emerging significant data sources like dynamic location and traffic, social media, geospatial and point of interest (POI) data. Data analysis methods commonly used include correlation analysis and comprehensive evaluation techniques.

The findings contribute to a comprehensive understanding of the vitality evaluation system for UPS from multiple perspectives for urban planners, aiding in identifying key factors and research methods in the vitality evaluation of various types of UPS.

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city interest points to construct urban security risk indicators. This paper combines traffic data and urban alarm data to analyze the safe travel characteristics of the urban population. The research results are helpful to explore the diversity of human group behavior, grasp the temporal and spatial laws and reveal regional security risks. It provides a reference for optimizing resource deployment and group intelligence analysis in emergency management.

Based on the dynamics index of group behavior, this paper mines the data of large shared bikes and ride-hailing in a big city of China. We integrate the urban interest points and travel dynamic characteristics, construct the urban traffic safety index based on alarm behavior and further calculate the urban safety index.

This study found significant differences in the travel power index among ride-sharing users. There is a positive correlation between user shared bike trips and the power-law bimodal phenomenon in the logarithmic coordinate system. It is closely related to the urban public security index.

Based on group-shared dynamic index integrated alarm, we innovatively constructed an urban public safety index and analyzed the correlation of travel alarm behavior. The research results fully reveal the internal mechanism of the group behavior safety index and provide a valuable supplement for the police intelligence analysis.

The purpose of this study is to provide the location of natural disasters that are poured into maps by extracting Twitter data. The Twitter text is extracted by using named entity recognition (NER) with six classes hierarchy location in Indonesia. Moreover, the tweet then is classified into eight classes of natural disasters using the support vector machine (SVM). Overall, the system is able to classify tweet and mapping the position of the content tweet.

This research builds a model to map the geolocation of tweet data using NER. This research uses six classes of NER which is based on region Indonesia. This data is then classified into eight classes of natural disasters using the SVM.

Experiment results demonstrate that the proposed NER with six special classes based on the regional level in Indonesia is able to map the location of the disaster based on data Twitter. The results also show good performance in geocoding such as match rate, match score and match type. Moreover, with SVM, this study can also classify tweet into eight classes of types of natural disasters specifically for the Indonesian region, which originate from the tweets collected.

This study implements in Indonesia region.

(a)NER with six classes is used to create a location classification model with StanfordNER and ArcGIS tools. The use of six location classes is based on the Indonesia regional which has the large area. Hence, it has many levels in its regional location, such as province, district/city, sub-district, village, road and place names. (b) SVM is used to classify natural disasters. Classification of types of natural disasters is divided into eight: floods, earthquakes, landslides, tsunamis, hurricanes, forest fires, droughts and volcanic eruptions.

This paper aims to investigate the formation of an inter-organizational collaboration network that made it possible to repair 2,516 mechanical respirators that were inoperative in Brazil during the first wave of the COVID-19 pandemic.

A qualitative approach was used in a single case study with semi-structured interviews. The interviewee selection process was non-probabilistic through snowball sampling.

The results suggest that society, through different social groups with their different roles, can organize itself quickly through the formation of collaborative networks, and this organizational configuration can be an alternative for facing crises where actions isolated would be insufficient or slow to urgently address complex situations.

This paper aims to (1) demonstrate that society, through different social groups with their different roles, can organize itself quickly through the formation of collaborative networks; (2) favor the understanding and dynamics of the formation of a network; and (3) contribute to a possible replication of this initiative in future contexts.

The case portrays an unprecedented formation of a collaboration network involving more than 144 organizations that mobilized quickly in a complex context of a pandemic and that generated remarkable results through the reintroduction of equipment that were responsible for the preservation of thousands of lives during the year from 2020.

Micro-regeneration can effectively enhance a neighborhood’s commercial vitality and serve as a viable approach to boost economic benefits. However, the small scale of micro-regeneration efforts and the fragmented nature of information currently limit the availability of strong empirical evidence demonstrating its impact on neighborhood commercial vitality. The aim of the study was to examine the link between micro-regeneration and neighborhood commercial vitality, focusing on the average, time-lag, spatial spillover, and spatial heterogeneity effects.

Using the panel data set of 1,755 neighborhoods in Chongqing from 2016 to 2021 as the research sample, the difference-in-differences (DID) method was employed in this study to explore the impact micro-regeneration has on neighborhood commercial vitality.

The results illustrate that: (1) micro-regeneration can promote neighborhood commercial vitality in terms of the number and types of local consumption amenities by 27.76 and 5.89%, respectively, with no time-lag effect; (2) the positive spillovers can exist within the range of 5,000 meters–5,500 meters of regenerated neighborhoods; and (3) the effect of micro-regeneration on neighborhood commercial vitality can be greater in peripheral areas than in core areas of the city.

The findings fill the knowledge gap on the relationship between micro-regeneration and neighborhood commercial vitality. Additionally, the results on the time-lag effect, spatial spillover effects, and spatial heterogeneity provide practical implications that can support the government and private sector in developing temporal and spatial arrangements for micro-regeneration projects.

Government primary schools in Australia increasingly take up the International Baccalaureate's Primary Years Programme (IB-PYP) to supplement government-mandated curriculum and governance expectations. The purpose of this paper is to explore how teachers navigate and contest dual policy-practice expectations in the Victorian Government IB-PYP context.

This study used a narrative inquiry approach. The narratives of two teachers were generated through a narrative interview and then re-storied with participants through a set of conceptual lenses drawn out of the policy assemblage and affect studies theoretical spaces.

The stories participants told show that competing mandatory local policy expressions are experienced and contested both to stabilize a technocratic rationality and produce alternative critical-political educational futures.

There a few accounts of teachers' policy experience in government school settings implementing the IB-PYP. In addressing this gap, this paper directly responds to prior claims of the IB's failure to promote an emancipatory pedagogy, showing instead that when teachers who bring a more critical understanding of educational purpose to their work take up the IB-PYP policy to support the enactment of that purpose.

This paper introduces a methodology to identify, analyse and represent heritage site attributes, emphasizing their impact on value, authenticity, integrity and management, with a case study on Ghadames, Libya. Inscribed in 1986 and moved to the In-Danger List in 2016 due to conflict, this work seeks to update the site's attributes and values for improved management.

This methodology, focusing on Ghadames, leverages recent heritage management advancements to monitor conflict-induced changes, aiming to enhance decision-making through a detailed analysis of the site's natural and cultural attributes.

Our findings highlight the need for systematic and holistic assessments of heritage site attributes and values, crucial for managing sites of both local and global significance. This approach is a key to understanding their identity, guiding interpretation, management and preserving cultural significance.

Developed for Ghadames, the methodology requires adaptation for other sites, underscoring the importance of identifying core tangible and intangible attributes that define a site's uniqueness.

Our developed methodology offers a replicable framework that can be modified by local heritage professionals to map attributes and assess the direct and indirect impact of conflict on heritage sites.

The detailed assessment provides a foundation for crafting informed policies and effective management strategies. It specifically targets minimizing the adverse effects of conflict on heritage sites' attributes. This effort is instrumental in preparing the necessary documentation to support the delisting of these sites from the UNESCO World Heritage Site In-Danger List, promoting their preservation and recovery.

The purpose of this paper is to investigate the vehicle-based sensor effect and pavement temperature on road condition assessment, as well as to compute a threshold value for the classification of pavement conditions.

Four sensors were placed on the vehicle’s control arms and one inside the vehicle to collect vibration acceleration data for analysis. The Analysis of Variance (ANOVA) tests were performed to diagnose the effect of the vehicle-based sensors’ placement in the field. To classify road conditions and identify pavement distress (point of interest), the probability distribution was applied based on the magnitude values of vibration data.

Results from ANOVA indicate that pavement sensing patterns from the sensors placed on the front control arms were statistically significant, and there is no difference between the sensors placed on the same side of the vehicle (e.g., left or right side). A reference threshold (i.e., 1.7 g) was computed from the distribution fitting method to classify road conditions and identify the road distress based on the magnitude values that combine all acceleration along three axes. In addition, the pavement temperature was found to be highly correlated with the sensing patterns, which is noteworthy for future projects.

The paper investigates the effect of pavement sensors’ placement in assessing road conditions, emphasizing the implications for future road condition assessment projects. A threshold value for classifying road conditions was proposed and applied in class assignments (I-17 highway projects).

Studies on developed economies showed that imposing taxes on animal-based foods could effectively reduce agricultural greenhouse gas emissions (AGHGEs), while this taxation may not be appropriate in developing countries due to the complex nutritional status across income classes. Hence, this study aims to explore optimal tax rate levels considering both emission reduction and nutrient intake, and examine the heterogenous effects of taxation across various income classes in urban and rural China.

The authors estimated the Quadratic Almost Ideal Demand System model to calculate the price elasticities for eight food groups, and performed three simulations to explore the relative optimal tax regions via the relationships between effective animal protein intake loss and AGHGE reduction by taxes.

The results showed that the optimal tax rate bands can be found, depending on the reference levels of animal protein intake. Designing taxes on beef, mutton and pork could be a preliminary option for reducing AGHGEs in China, but subsidy policy should be designed for low-income populations at the same time. Generally, urban residents have more potential to reduce AGHGEs than rural residents, and higher income classes reduce more AGHGEs than lower income classes.

This study fills the gap in the literature by developing the methods to design taxes on animal-based foods from the perspectives of both nutrient intake and emission reduction. This methodology can also be applied to analyze food taxes and GHGE issues in other developing countries.