Discovering preferential patterns in sectoral trade networks

We analyze the patterns of import/export bilateral relations, with the aim of assessing the relevance and shape of preferentiality in countries trade decisions. Preferentiality here is defined as the tendency to concentrate trade on one or few partners. With this purpose, we adopt a systemic approach through the use of the tools of complex network analysis. In particular, we apply a pattern detection approach based on community and pseudocommunity analysis, in order to highlight the groups of countries within which most of members trade occur. The method is applied to two intra-industry trade networks consisting of 221 countries, relative to the low-tech Textiles and Textile Articles and the high-tech Electronics sectors for the year 2006, to look at the structure of world trade before the start of the international financial crisis. It turns out that the two networks display some similarities and some differences in preferential trade patterns: they both include few significant communities that define narrow sets of countries trading with each other as preferential destinations markets or supply sources, and they are characterized by the presence of similar hierarchical structures, led by the largest economies. But there are also distinctive features due to the characteristics of the industries examined, in which the organization of production and the destination markets are different. Overall, the extent of preferentiality and partner selection at the sector level confirm the relevance of international trade costs still today, inducing countries to seek the highest efficiency in their trade patterns

Tracking people across disjoint camera views by an illumination-tolerant appearance representation

Tracking single individuals as they move across disjoint camera views is a challenging task since their appearance may vary significantly between views. Major changes in appearance are due to different and varying illumination conditions and the deformable geometry of people. These effects are hard to estimate and take into account in real-life applications. Thus, in this paper we propose an illumination-tolerant appearance representation, which is capable of coping with the typical illumination changes occurring in surveillance scenarios. The appearance representation is based on an online k-means colour clustering algorithm, a data-adaptive intensity transformation and the incremental use of frames. A similarity measurement is also introduced to compare the appearance representations of any two arbitrary individuals. Post-matching integration of the matching decision along the individuals' tracks is performed in order to improve reliability and robustness of matching. Once matching is provided for any two views of a single individual, its tracking across disjoint cameras derives straightforwardly. Experimental results presented in this paper from a real surveillance camera network show the effectiveness of the proposed method. © Springer-Verlag 2007

On the Invertibility of Storage Systems

The invertibility of single-input single output storage systems (network of reservoirs) is considered in this paper. The analysis shows that cascade and feedback connections of invertible subsystems give rise to invertible systems, and that parallel connections are invertible provided that the network is not too diversified topologically and that the reservoirs have comparable dynamics. These results often allow one to ascertain the invertibility of a complex storage system by direct inspection of a graph

Dyslexia and Comorbid Dyscalculia: rate of comorbidity and underlying cognitive and learning profile

PURPOSE OF THE STUDY. Children diagnosed with a specific learning disorder (SLD) have four to five times higher chances of developing a comorbid condition. In particular, the high prevalence of comorbid dyscalculia (MD) in children with dyslexia (RD) has been documented. Nevertheless, the exact rate of MD comorbidity and the causes underlying the overlap remain unclear since most research has focused on studying them in isolation. Given the relevance of early identification and evidence-based interventions for further compensation of SLD, there is a need for studies on this matter. The study intended to fill this gap. METHOD. The study was a secondary data analysis of the standardised test scores of 215 neuropsychological assessments administered to grade 1 to 3 schoolchildren in Argentina who had a prior diagnosis of RD. For the purposes of the study, they were classified into 2 groups (RD only and comorbid RDMD). Scores were analyzed using SPSS Statistics to (i) explore the rate of MD comorbidity in children with RD; (ii) contrast the cognitive and learning profiles of the RD and the RDMD group; and (iii) assess the predictive value of each cognitive factor to the development of the RDMD comorbidity. RESULTS AND CONCLUSION. The study found that children with RD developed RDMD at a frequency of 33.5%. There was a significant difference in the two groups' learning and cognitive factors scores, with the comorbid group worst affected in all domains. Among these, verbal working memory, spatial skills, semantic long-term memory and phonological awareness were the most sensitive predictors; together they could account for 35% of the MD comorbidity. These findings are evidence of the high incidence of MD comorbidity in the population with RD and highlight the predictive value of specific cognitive markers

Reshaping the structure of the World Trade Network: a pivotal role for China?

In recent years, the global trade landscape has undergone significant changes, particularly in the aftermath of the 2008 financial crisis and more recently as a consequence of Covid-19 pandemic. To understand the structure of international trade and the impact of these changes, this study applies a combination of network analysis and causal inference techniques to the most extensive coverage of available data in terms of time span and spatial extension. The study is conducted in two phases. The first one explores the structure of international trade by providing a comprehensive analysis of the World Trade Network (WTN) from various perspectives, including the identification of key players and clusters of strongly interacting countries. The second phase investigates the impact of the rising role of China on the global structure of the WTN. Overall, the results highlight a structural change in the WTN, evidenced by a variety of network metrics, around China's rapid growth years. Additionally, the reshaping of the WTN is not only accompanied by a significant increase in trade flows between China and its partners, but also by a corresponding decline in trade among non-China-partner countries. These results suggest that China played a pivotal role in the restructuring of the WTN in the first decades of this century. The findings of this study shed light on the interpretation of the rapidly changing landscape of global trade

Patterns of variability in the structure of global value chains: a network analysis

Global Value Chains (GVCs) are a feature of the organization of production in many sectors and countries and they deeply affect international trade patterns. How far the separation of production stages—generating increasingly widespread GVCs—can go, is currently a matter of debate. The main focus of this paper is to investigate GVCs at the country-industry level by modelling them through the construction of a specific network and using network analysis tools. In particular, the aim is to propose a network-based measure of GVCs length to assess whether the structure of GVCs has stretched or shrank over time. Analyzing the evolution of these structures is important to better understand the role played by countries in the production chain, with implications also for their fragility or resilience in presence of external shocks. Our measure allows to consider differently shaped GVCs, and the results show that there are relevant differences among sectors and countries in terms of the evolution of GVCs, especially considering direct or indirect links. Overall, we find a general stability over time of GVCs, confirming the importance of the “relational approach” in GVCs. But the shifts in the geographical patterns of the connections also support the view that firms organizing this complex form of production are ready to grasp better opportunities when they appear in the global markets

Topographical working memory in children and adolescents with motor disabilities

Aim: The aim of the present study was to investigate topographical working memory in individuals with motor disabilities. Methods: Topographical working memory was investigated using the Walking Corsi Test in 89 participants with motor disability, mean age 11.5 years, of which 40 with cerebral palsy, 31 with spina bifida, and 18 with orthopaedic or peripheral symptoms. The participants were grouped according to everyday mobility, i.e. walking outdoors, walking indoors, and using wheelchair. A control group constituted 120 typically developing participants, mean age 9.9 years. Results: Individuals with spina bifida, orthopaedic or peripheral symptoms as well as typically developing participants performed significantly larger walking spans than the cerebral palsy group. With respect to mobility, those walking outdoors had significantly larger span than those walking indoors and those using wheelchair for mobility. Conclusions: Participants with outdoor walking in the community, apart from type of motor disability, seem to have improved topographic memory compared to individuals who don’t walk outside and individuals who are mobile through wheelchair. The results highlight the question of development of spatial cognition to enhance participation in social environments. Future research should focus on prematurity in the cerebral palsy group, and on hydrocephalus in the spina bifida group

Profiling core-periphery network structure by random walkers

Disclosing the main features of the structure of a network is crucial to understand a number of static and dynamic properties, such as robustness to failures, spreading dynamics, or collective behaviours. Among the possible characterizations, the core-periphery paradigm models the network as the union of a dense core with a sparsely connected periphery, highlighting the role of each node on the basis of its topological position. Here we show that the core-periphery structure can effectively be profiled by elaborating the behaviour of a random walker. A curve—the core-periphery profile—and a numerical indicator are derived, providing a global topological portrait. Simultaneously, a coreness value is attributed to each node, qualifying its position and role. The application to social, technological, economical, and biological networks reveals the power of this technique in disclosing the overall network structure and the peculiar role of some specific nodes