Connectedness Relation Research Articles

Freedom through constraint: Young women's embodiment, space and wellbeing during lockdown

Following the emergence of the COVID-19 pandemic and the associated lockdown restrictions in March 2020, young people were suddenly faced with a reduction and reconfiguration of the spaces in which they could ‘be’. This paper explores how in this lockdown context, young women (aged 10–20) experienced their bodies and wellbeing, where traditional social connections (particularly school and physical connections) were not possible. Based on qualitative responses (n = 511) from an online, open-ended survey on wellbeing, physical activity, body image and social media usage, we explore how a reduction and reconfiguration of space, understood relationally, contributes to an individual's wellbeing. Using abductive reasoning and taking a phenomenological approach, we concentrate on the embodied experience of wellbeing and how this links to the spaces in which the body is lived. We suggest that the removal of spaces during lockdown, which on the one hand can be seen as problematic for maintaining wellbeing, also enabled many young women to experience new connections – with their bodies, family, and the environment and nature, that supplemented previous connections and fostered positive relationships and wellbeing. The removal of specific performative modes of judgement associated with the school environment was a positive influence on many young women's relationships with their own bodies and their wider construction of wellbeing, but increased use of social media spaces were found to reconstitute these performative experiences. The benefits of the specific and newly delimited freedoms associated with the forced lockdown have implications for an understanding of embodied wellbeing that is not individual, instead embedded inextricably in relations of connectedness with others in space and the nature of these intersubjective experiences.

Does COVID-19 open a Pandora's box of changing the connectedness in energy commodities?

With the rapid spread of coronavirus, the global financial markets have been undergoing tremendous changes, which bring investors more risks in the short term. Against such background, this study concentrates on the far-reaching energy commodities, aiming to explore the impact of COVID-19 on cross-market linkages. To capture the dynamic nature of interdependence, we applied the TVP-VAR based connectedness index method and individually focused on the total, net, and pairwise connectedness. The empirical results show that there is a dramatic rise in the total connectedness in energy markets following the outbreak of COVID-19, but this change only lasted about two months and then fell back to the prior level. Further analyzing the net spillover conditions, we find that the connectedness structure has also displayed some temporary changes. At last, the spillover networks indicate that there are only three pairwise connectedness relations have changed in direction before and after the outbreak of COVID-19. We also try to discuss the underlying COVID-19 shock propagation mechanism, and the results suggest the significant mediation effect of the financial panic risk. In general, our study offers several urgent and prominent implications to understand the financial impact of COVID-19.

Possible Objects: Topological Approaches to Individuation.

We think of the world around us as divided into physical objects like toasters and daisies, rather than solely as a smear of properties like yellow and smooth. How do we single out these objects? One theory of object concepts uses part-of relations and relations of connectedness. According to this proposal, an object is a connected spatial item of maximal extent: Any other connected item that overlaps (i.e., shares a part with) the object must be a part of that object. This article reports four experiments that test this proposal. Participants see descriptions or diagrams of spatial items that vary across trials in their relative positions. In separate experiments, participants decide whether the items are physical objects, whether they are wholes, or how many objects are present. All experiments find support for connectedness as a contributor to object status, but they find little support for maximality. The results suggest that maximality is not a necessary feature of wholes or of objects.

Solution of the 33rd Palis-Pugh problem for gradient-like diffeomorphisms of a two-dimensional sphere

In the present paper, a solution to the 33rd Palis-Pugh problem for gradient-like diffeomorphisms of a two-dimensional sphere is obtained. It is precisely shown that with respect to the stable isotopic connectedness relation there exists countable many of equivalence classes of such systems. 43 words.

The public loneliness of endurance athletes: Creating ambient affiliation through involvement strategies on Twitter

The accessibility and interactivity of Twitter both facilitate athlete-fan interaction and contribute to the time/space compression between sporting events and communication about them. While numerous studies investigate real-time participatory engagement of fans on Twitter, athletes’ use of Twitter during competition remains underexplored. Using a case study approach, this study brings together computer-mediated discourse analysis and prior work on involvement in discourse to examine tweets posted during competitive events by two endurance athletes (an experienced amateur marathon runner and an elite rock climber). Specifically, it explores how athletes mobilize various linguistic strategies to create relations of connectedness, or ambient affiliation (Zappavigna, 2011), with their respective audiences who are distanced spatially and often temporally. It also demonstrates how the affordances and limitations of technology, and the constraints of the athletic events themselves, shape ambient involvement. In this way, this work adds to our understanding of how ambient affiliation is constructed in a particular context – a competitive athletic event of an endurance athlete practicing a solitary sport – while also shedding light on how involvement is created and maintained with a largely unknown online audience.

Civil Liability of Participants of Corporate Relations

The paper considers general provisions with regard to civil liability as a type of legal responsibility, types of civil liability. The paper scrutinizes the specificity of civil liability of participants of corporate relations. Also, the paper examines the current legislation and jurisprudence of application of provisions concerning civil liability, determination of criteria of actual possibility and legal characteristics of connectedness relations in the field of corporate relations in insolvency (bankruptcy) cases. Based on the results of the study, the author comes to the conclusion that in order to solve the problems of law enforcement, in order to ensure effectiveness of the application of the existing regulations concerning liability in corporate relations, and taking into account their civil legal nature, it is necessary to specify in normative legal acts the conditions and grounds for civil liability imposed for corporate offenses and to specify the criteria for imposing civil liability or exempting from it on the basis of objective characteristics of "normal conditions of civil law relations or entrepreneurial risk" (Art. 53.1 of the RF Civil Code).

Vascular segmentation in hepatic CT images using adaptive threshold fuzzy connectedness method.

BackgroundFuzzy connectedness method has shown its effectiveness for fuzzy object extraction in recent years. However, two problems may occur when applying it to hepatic vessel segmentation task. One is the excessive computational cost, and the other is the difficulty of choosing a proper threshold value for final segmentation.MethodsIn this paper, an accelerated strategy based on a lookup table was presented first which can reduce the connectivity scene calculation time and achieve a speed-up factor of above 2. When the computing of the fuzzy connectedness relations is finished, a threshold is needed to generate the final result. Currently the threshold is preset by users. Since different thresholds may produce different outcomes, how to determine a proper threshold is crucial. According to our analysis of the hepatic vessel structure, a watershed-like method was used to find the optimal threshold. Meanwhile, by using Ostu algorithm to calculate the parameters for affinity relations and assigning the seed with the mean value, it is able to reduce the influence on the segmentation result caused by the location of the seed and enhance the robustness of fuzzy connectedness method.ResultsExperiments based on four different datasets demonstrate the efficiency of the lookup table strategy. These experiments also show that an adaptive threshold found by watershed-like method can always generate correct segmentation results of hepatic vessels. Comparing to a refined region-growing algorithm that has been widely used for hepatic vessel segmentation, fuzzy connectedness method has advantages in detecting vascular edge and generating more than one vessel system through the weak connectivity of the vessel ends.ConclusionsAn improved algorithm based on fuzzy connectedness method is proposed. This algorithm has improved the performance of fuzzy connectedness method in hepatic vessel segmentation.

Reasoning about Topological and Cardinal Direction Relations Between 2-Dimensional Spatial Objects

Increasing the expressiveness of qualitative spatial calculi is an essential step towards meeting the requirements of applications. This can be achieved by combining existing calculi in a way that we can express spatial information using relations from multiple calculi. The great challenge is to develop reasoning algorithms that are correct and complete when reasoning over the combined information. Previous work has mainly studied cases where the interaction between the combined calculi was small, or where one of the two calculi was very simple. In this paper we tackle the important combination of topological and directional information for extended spatial objects. We combine some of the best known calculi in qualitative spatial reasoning, the RCC8 algebra for representing topological information, and the Rectangle Algebra (RA) and the Cardinal Direction Calculus (CDC) for directional information. We consider two different interpretations of the RCC8 algebra, one uses a weak connectedness relation, the other uses a strong connectedness relation. In both interpretations, we show that reasoning with topological and directional information is decidable and remains in NP. Our computational complexity results unveil the significant differences between RA and CDC, and that between weak and strong RCC8 models. Take the combination of basic RCC8 and basic CDC constraints as an example: we show that the consistency problem is in P only when we use the strong RCC8 algebra and explicitly know the corresponding basic RA constraints.

Parallel fuzzy connected image segmentation on GPU

Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm implementation on NVIDIA's compute unified device Architecture (CUDA) platform for segmenting medical image data sets. In the FC algorithm, there are two major computational tasks: (i) computing the fuzzy affinity relations and (ii) computing the fuzzy connectedness relations. These two tasks are implemented as CUDA kernels and executed on GPU. A dramatic improvement in speed for both tasks is achieved as a result. Our experiments based on three data sets of small, medium, and large data size demonstrate the efficiency of the parallel algorithm, which achieves a speed-up factor of 24.4x, 18.1x, and 10.3x, correspondingly, for the three data sets on the NVIDIA Tesla C1060 over the implementation of the algorithm on CPU, and takes 0.25, 0.72, and 15.04 s, correspondingly, for the three data sets. The authors developed a parallel algorithm of the widely used fuzzy connected image segmentation method on the NVIDIA GPUs, which are far more cost- and speed-effective than both cluster of workstations and multiprocessing systems. A near-interactive speed of segmentation has been achieved, even for the large data set.

Multicolor well-composed pictures

As was noted early in the history of computer vision, using the same adjacency relation for the entire digital picture leads to so-called “paradoxes” related to the Jordan Curve Theorem. The most popular idea to avoid these paradoxes in binary images was using different adjacency relations for the foreground and the background: 8-adjacency for black points and 4-adjacency for white points, or vice versa. This idea cannot be extended in a straightforward way to multicolor pictures. In this paper a solution is presented which guarantees us to avoid the connectivity paradoxes related to the Jordan Curve Theorem for all multicolor pictures. Only one connectedness relation will be used for the entire digital picture, i.e. for every component of every color. The idea is not to allow a certain “critical configuration” which can be detected locally to occur in digital pictures; such pictures will be called “well-composed”. Well-composed pictures have very nice topological properties. For example the Jordan Curve Theorem holds and the Euler characteristic is locally computable. This implies that properties of algorithms used in computer vision can be stated and proved in a clear way, and that the algorithms themselves become simpler and faster. Moreover, if a digitization process is guaranteed to preserve topology, then the obtained digital pictures must be well-composed.

Well-Composed Sets

A special class of subsets of binary digital images called "well-composed sets" is defined. The sets of this class have very nice topological properties; for example, the Jordan Curve Theorem holds for them, their Euler characteristic is locally computable, and they have only one connectedness relation, since 4- and 8-connectedness are equivalent. This implies that many basic algorithms used in computer vision become simpler. There are real advantages in applying thinning algorithms to well-composed sets, For example, thinning is an internal operation on these sets and the problems with irreducible "thick" sets disappear. Furthermore, we prove that the skeletons obtained are "one point thick" and we give a formal definition of this concept. We also show that these skeletons have a graph structure and we define what this means.