A New Information-Theoretical Distance Measure for Evaluating Community Detection Algorithms

Community detection is a research area from network science dealing withthe investigation of complex networks such as social or biological networks, aimingto identify subgroups (communities) of entities (nodes) thatare more closely relatedto each other inside the community than with the remaining entities in the network.Various community detection algorithms have been developed and used in the literaturehowever evaluating community structures that have been automatically detected isa challenging task due to varying results in different scenarios.Current evaluationmeasures that compare extracted community structures with the reference structure orground truth suffer from various drawbacks; some of them having beenpoint out in theliterature. Information theoretic measures form a fundamental classin this domain andhave recently received increasing interest. However even the well employed measures(NVI and NID) also share some limitations, particularly they are biased toward thenumber of communities in the network. The main contribution ofthis paper is tointroduce a new measure that overcomes this limitation while holding the importantproperties of measures. We review the mathematical properties of our measure based on¿2divergence inspired fromf-divergence measures in information theory. Theoreticalproperties as well as experimental results in various scenarios show the superiority of theproposed measure to evaluate community detection over the ones from the literature

f-Divergence Measures for Evaluation in Community Detection

International audienceCommunity detection is a research area from network science dealing with the investigation of complex networks such as biological, social and computer networks, aiming to identify subgroups (communities) of entities (nodes) that are more closely related to each other than with remaining entities in the network [1]. Various community detection algorithms are used in the literature however the evaluation of their derived community structure is a challenging task due to varying results on different networks. In searching good community detection algorithms diverse comparison measures are used actively [2]. Information theoretic measures form a fundamental class in this discipline and have recently received increasing interest [3]. In this paper we first mention the usual evaluation measures used for community detection evaluation We then review the properties of f -divergence measures and propose the ones that can serve community detection evaluation. Preliminary experiments show the advantage of these measures in the case of large number of communities

Community detection: comparison of state of the art algorithms

International audienceReal world complex networks may contain hidden structures called communities or groups. They are composed of nodes being tightly connected within those groups and weakly connected between them. Detecting communities has numerous applications in different sciences such as biology, social network analysis, economics and computer science. Since there is no universally accepted definition of community, it is a complicated task to distinguish community detection algorithms as each of them use a different approach, resulting in different outcomes. Thus large number of articles are devoted to investigating community detection algorithms, implementation on both real world and artificial data sets and development of evaluation measures. In this article several state of the art algorithms and evaluation measures are studied which are used in clustering and community detection literature. The main focus of this article is to survey recent work and evaluate them using artificially generated networks

Cause-effect relations between defects of medical care and lethal outcome

The article discusses the issues of identifying and determining the cause-effect relations between defects in the provision of medical care and lethal outcome based on the materials of commission forensic medical expertise. In the presence of defects in the provision of medical care in 30.3% of cases a cause-effect relation was detected between the frequency of defects in medical care and the likelihood of lethal outcome. The likelihood of the occurrence of lethal outcome was most influenced by defects in diagnosis (RR = 2.41) and treatment (RR = 15.65).W artykule omówiono problematykę rozpoznawania i określania związków przyczynowo-skutkowych między błędami w świadczeniu opieki medycznej a skutkiem śmiertelnym na podstawie materiałów zleconych ekspertyz z zakresu medycyny sądowej. W odniesieniu do wystąpienia błędów w świadczeniu opieki medycznej w 30,3% przypadków stwierdzono związek przyczynowo-skutkowy między częstością błędów medycznych a prawdopodobieństwem śmiertelności. Największy wpływ na prawdopodobieństwo wystąpienia zgonu miały błędy w rozpoznaniu (RR = 2,41) i leczeniu (RR = 15,65)

Intervertebral disc swelling demonstrated by 3D and water content magnetic resonance analyses after a 3-day dry immersion simulating microgravity

International audienceBackground Vertebral deconditioning is commonly experienced after space flight andsimulation studies. Disc herniation (DH) is quadrupled after space flight.Purpose The main hypothesis formulated by the authors is that microgravity results inintervertebral disc swelling.Study Design The aim of the study was to identify the morphological changes of the spine andtheir clinical consequences after simulated microgravity by 3-day dry immersion (DI).The experimental protocol was performed on 12 male volunteers using magnetic resonanceimaging and spectroscopy before and after DI.Methods All the experiment was financially supported by CNES (Centre national d’étudesspatiales i.e. French Space Agency).Results We observed an increase in rachis height of 1.5 ± 0.4 cm and a decrease in curvature,particularly for the lumbar region with a decrease of -4 ± 2.5°. We found a significantincrease in intervertebral disc (IVD) volume of +8 ± 9% at T12-L1 and +11 ± 9% at L5-S1.This phenomenon is likely associated with the increase in disc intervertebral water content(IWC), 17 ± 27%. During the 3 days in DI, 92% of the subjects developed back pain in thelumbar region below the diaphragmatic muscle. This clinical observation may be linked to themorphological changes of the spine.Conclusions The morphological changes observed and, specifically, the disc swelling causedby increased IWC may contribute to understanding disc herniation after microgravityexposure. Our results confirmed the efficiency of the 3-day DI model to reproduce quickly theeffects of microgravity on spine morphology. Our findings raise the question of the subjectselection in spatial studies, especially studies about spine morphology and reconditioningprograms after space flight. These results may contribute to a better understanding of themechanisms underlying disc herniation and may serve as the basis to developcountermeasures for astronauts and to prevent IVD herniation and back pain on Earth

First combined in vivo X-ray tomography and high-resolution molecular electron paramagnetic resonance (EPR) imaging of the mouse knee joint taking into account the disappearance kinetics of the EPR probe.

International audienceAlthough laboratory data clearly suggest a role for oxidants (dioxygen and free radicals derived from dioxygen) in the pathogenesis of many age-related and degenerative diseases (such as arthrosis and arthritis), methods to image such species in vivo are still very limited. This methodological problem limits physiopathologic studies about the role of those species in vivo, the effects of their regulation using various drugs, and the evaluation of their levels for diagnosis of degenerative diseases. In vivo electron paramagnetic resonance (EPR) imaging and spectroscopy are unique, noninvasive methods used to specifically detect and quantify paramagnetic species. However, two problems limit their application: the anatomic location of the EPR image in the animal body and the relative instability of the EPR probes. Our aim is to use EPR imaging to obtain physiologic and pathologic information on the mouse knee joint. This article reports the first in vivo EPR image of a small tissue, the mouse knee joint, with good resolution (≈ 160 μm) after intra-articular injection of a triarylmethyl radical EPR probe. It was obtained by combining EPR and x-ray micro-computed tomography for the first time and by taking into account the disappearance kinetics of the EPR probe during image acquisition to reconstruct the image. This multidisciplinary approach opens the way to high-resolution EPR imaging and local metabolism studies of radical species in vivo in different physiologic and pathologic situations