Shenzhen City in Southeast China has developed from a small fishing village into a modern metropolis since China adopted an open-door policy in 1978. In accordance with its national plan and ...strategy, China has been striving to develop its international Guangdong–Hong Kong–Macau Greater Bay Area (GBA). Owing to its rapidly developing economy, industries and innovative technologies, Shenzhen is an important city in the GBA. Shenzhen’s higher education (HE) is supposedly crucial for its advancement as an innovation hub. However, the HE in Shenzhen is reportedly not adept with the city’s economic development. Although some Chinese studies have focused on Shenzhen’s HE-related issues, such as integration of and co-operation with the GBA’s policies, not many international studies have assessed how universities can help to ensure overall regional development. Thus, in this study, using Shenzhen’s case in the GBA, we explore the roles of universities in regional development. We review several policy documents and literature based on the glonacal framework to collect relevant data in text and generated themes. The study findings address the critical roles of Shenzhen universities in regional development such as promoting research capacity, fostering international collaboration and upgrading the GBA’s HE sector.
Autism Spectrum Disorders (ASDs) are a heterogeneous group of neurodevelopmental disorders that are diagnosed solely on the basis of behaviour. A large body of work has reported neuroanatomical ...differences between individuals with ASD and neurotypical controls. Despite the huge clinical and genetic heterogeneity that typifies autism, some of these anatomical features appear to be either present in most cases or so dramatically altered in some that their presence is now reasonably well replicated in a number of studies. One such finding is the tendency towards overgrowth of the frontal cortex during the early postnatal period. Although these reports have been focused primarily on the presumed pathological anatomy, they are providing us with important insights into normal brain anatomy and are stimulating new ideas and hypotheses about the normal trajectory of brain development and the function of specific anatomical brain structures. The use of model systems that include genetic model organisms such as the mouse and, more recently, human induced pluripotent stem cell‐derived brain organoids to model normal and pathological human cortical development, is proving particularly informative. Here we review some of the neuroanatomical alterations reported in autism, with a particular focus on well‐validated findings and recent advances in the field, and ask what these observations can tell us about normal and abnormal brain development.
•Daily rainfall-runoff models can calibrate successfully to monthly streamflow data.•Monthly and daily calibration perform similarly except for daily pattern metrics.•Parameter regionalisation ...reduces performance loss of monthly calibration.•Findings are robust with respect to choice of objective function.
Development of robust approaches for calibrating daily rainfall-runoff models to monthly streamflow data is of major practical interest. Such approaches would enable widely used hydrological modelling platforms that operate at daily time step to be applied in practical situations where precipitation is available at the daily scale, but observed streamflow is available only at the monthly scale (e.g. predicting inflows into large dams). This study compares the performance of a hydrological model running at daily time step (GR4J) that is calibrated against daily and monthly streamflow data using a wide range of metrics: fit of the daily and monthly flow duration curve, daily and monthly pattern metrics, and long-term bias. The comparison is undertaken for 508 Australian catchments, two evaluation periods and four objective functions (including sum-of-squared-errors of Box-Cox transformed streamflow and the Kling-Gupta efficiency). Monthly calibration performs similar or better than daily calibration in a majority of sites and periods in terms of bias and fit of the flow duration curve. This result holds even when the flow duration curve is computed at the daily time step, which constitutes a major finding of this study. However, performance of monthly calibration is worse than daily calibration for daily pattern metrics such as Nash-Sutcliffe efficiency in a majority of sites and periods. This performance loss can be reduced significantly by using regionalised values for the flow-timing parameter of GR4J. Similar results are obtained for other pattern metrics and all objective functions. These findings suggest that monthly calibration of rainfall-runoff models to daily-rainfall/monthly-streamflow is a viable alternative to daily calibration when no daily streamflow data are available.
Impacts associated with land use are increasingly recognized as important aspects to consider when conducting Life Cycle Assessment (LCA). Across the existing models accounting for land use ...activities in life cycle impact assessment, a balance is yet to be found between complexity and comprehensiveness on one hand, and applicability on the other hand. This work builds on the LANd use indicator value CAlculation (LANCA®) model, assessing the impacts of land use activities on five soil properties, and aims at developing an aggregated index to improve its applicability. First a statistical analysis is conducted, leading to the shortlisting of the four most significant soil quality indicators. Then two options for aggregating the selected indicators are presented: the soil quality index (SQI), based on linear aggregation, and the normalisation–based soil quality index (NSQI), where the aggregation process involves normalisation integrated into the characterisation step. Country-specific and global average characterisation factors (CFs) are calculated for 57 land use types considering both land occupation and land transformation interventions with the two suggested approaches. The two indices present similar ranking of land use types but the relative contribution of the separate indicators to the aggregated index varies according to the approach adopted. The differences between the aggregation approaches suggested are discussed, together with the limitations related to both the LANCA® model and the aggregation approaches. This work represents a first step towards the widespread application of a comprehensive and robust land use model at midpoint level in LCA. Finally, a number of recommendations for the future development of the LANCA® model and of the related soil quality models are provided.
•Soil quality needs to be evaluated considering different drivers of impacts.•LANCA® model is assessing land use impacts on five soil properties and could be used in LCA.•An updated version of the LANCA® model is presented.•Two aggregated multidimensional indices based on LANCA® model are proposed.•Characterisation factors are provided for both land occupation and transformation.
Regional input-output tables and trade flows: an integrated and interregional non-survey approach. Regional Studies. Regional analyses require detailed and accurate information about dynamics ...happening within and between regional economies. However, regional input-output tables and trade flows are rarely observed and they must be estimated using up-to-date information. Common estimation approaches vary widely but consider tables and flows independently. By using commonly used economic assumptions and available economic information, this paper presents a method that integrates the estimation of regional input-output tables and trade flows across regions. Examples of the method implementation are presented and compared with other approaches, suggesting that the integrated approach provides advantages in terms of estimation accuracy and analytical capabilities.
•Positive precipitation trends are found in Mid-North California during winter.•Negative precipitation trends are noted in Mid-South California most of the year.•ENSO, NAO and AAO are highly ...correlated with rainfall in the first 4 months of the year.•PDO and PNA shown high correlations with precipitation in December.•ENSO is the pattern that might modulate precipitation in Mojave Climate Region.
The aim of this research is to enlarge knowledge of space-time evolution of precipitation in California over the last decade on a monthly, seasonal and annual time-scale. This study also analyses the relationship between precipitation and teleconnection patterns with most influence on Californian climate. The homogeneity of the data from the selected stations was verified and finally 165 meteorological stations were used with an observation period that ranged from 1980 to 2019. In order to evaluate trends and statistical significance, both the non-parametric Mann-Kendall test and modified Sen’s slope method were used. Correlation analysis using the partial non-parametric Spearman Test (95% confidence level) was performed to find out relationships between precipitation and nine teleconnection patterns in the State of California. Spatial analysis was achieved using Empirical Bayesian Kriging (EBK). Finally, this research, as a novelty, shows regionalisation of California State as a function of significance in the correlation of precipitation with teleconnection patterns. To achieve this, Principal Component Analysis (PCA) and Agglomerative Hierarchical Cluster analysis (HCA) was performed. Results show a positive precipitation trend in winter and negative precipitation trend in late summer and autumn. The teleconnection patterns more correlated with precipitation are El Niño along Southern Oscillation (ENSO), Antarctic Oscillation (AAO) and North Atlantic Oscillation (NAO). Four areas were discerned outlining the Mojave Climate Region (Area 4) by having ENSO as the teleconnection pattern that best account precipitation.
Scientific publications are no longer practised by only a few established countries. The scholarly literature increasingly acknowledges that global science is pluralising. However, the existing ...literature mostly focuses on the national and global scales of science and overlooks the regional scale, especially regions in the Global South. This paper investigates the regionalisation of science of the Association of South-East Asian Nations (ASEAN), a ten-nation entity. It envisions science space to be multi-scalar, consisting of individual, institutional, local, national, regional and global scales. Specifically, it develops an agential approach to analyse patterns of intra-ASEAN scientific collaborations and funding in a multi-scalar science space, with a particular focus on the actors in this space and the structure in which these actors are embedded. The analyses of the bibliometric data of ASEAN countries in the last twenty years indicate an increasingly integrated regional science space in ASEAN. The intra-region collaborative publications grew faster than the total publications. The countries have increasingly funded their own and each other’s research, amidst the pluralisation of research funding. Malaysia emerges as a central actor in the regional scientific connectivity, despite Singapore having the most scientific publications to date.
•Global science is pluralising, but existing scholarship overlooks the regional scale of science, especially regions in the Global South.•ASEAN has become increasingly integrated as a regional science space in the last two decades.•The intra-region collaborative publications grew faster than total publications.•ASEAN countries have increasingly funded their own and each other’s research amidst the pluralisation of research funding.•The paper proposes an agential approach to analyse ASEAN science regionalisation.
•Precipitation station sensitivity analysis to determine important stations.•Regional sensitivity analysis of distributed J2000 model.•Identify precipitation stations which impact simulated peak and ...low flows.•Identify sub-basins important for overall runoff generation.•Optimized precipitation station weights can account for microclimates.
Understanding flow regime dynamics is important for the management and conservation of river systems and their related ecosystems under current and future pressures like climate and land use change. For this reason, the accuracy and detail with which hydrological models are able to replicate streamflow and other spatially distributed processes is critical for global and regional water management programs. One of the most critical factors for model performance is the spatial and temporal representation of precipitation data, a procedure known as regionalisation. It is therefore imperative to evaluate the sensitivity of models to data from different stations in order to identify locations that exert the strongest control on simulated streamflow. In this study, a spatially distributed rainfall/runoff model, the J2000, calibrated under near natural river flow conditions, was used to analyse the overall precipitation station impact on simulated streamflow and its flow components. For this purpose, different analysis methods including Regional Sensitivity Analysis (RSA) were used. The study was applied to the Berg River catchment, a water stressed region in the Western Cape, South Africa that was recently affected by serious drought conditions. The results show that during peak flows precipitation stations in the headwater part of the basin had the largest systematic impact, often controlling the data input for only a small proportion of the overall spatial extent of the model, but still having the largest impact on the overall modelled streamflow. In contrast, precipitation stations in lowland areas showed to be more important during low-flow periods, although they often control the data input for a larger part of the modelled catchment. The study highlights the importance of good overall data coverage for improved low-flow simulations, as well as identification of critical areas in regions responsible for peak runoff generation processes. The inclusion of systematic station weights has the potential to improve the ecohydrological representation of rainfall/runoff models in data scarce regions, as well as precipitation regionalisation approaches. The results are indicative of known microclimatic variability in semi-arid Southern Africa, highlighting the significance of catchment heterogeneity and areas of dominant sub-basins for overall runoff generation.
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