A semi-supervised graph-based algorithm for detecting outliers in online-social-networks

In this paper, we propose a semi-supervised approach of anomaly detection in Online Social Networks. The social network is modeled as a graph and its features are extracted to detect anomaly. A clustering algorithm is then used to group users based on these features and fuzzy logic is applied to assign degree of anomalous behavior to the users of these clusters. Empirical analysis shows effectiveness of this method.

A people-to-people matching system using graph mining techniques

A people-to-people matching system (or a match-making system) refers to a system in which users join with the objective of meeting other users with the common need. Some real-world examples of these systems are employer-employee (in job search networks), mentor-student (in university social networks), consume-to-consumer (in marketplaces) and male-female (in an online dating network). The network underlying in these systems consists of two groups of users, and the relationships between users need to be captured for developing an efficient match-making system. Most of the existing studies utilize information either about each of the users in isolation or their interaction separately, and develop recommender systems using the one form of information only. It is imperative to understand the linkages among the users in the network and use them in developing a match-making system. This study utilizes several social network analysis methods such as graph theory, small world phenomenon, centrality analysis, density analysis to gain insight into the entities and their relationships present in this network. This paper also proposes a new type of graph called “attributed bipartite graph”. By using these analyses and the proposed type of graph, an efficient hybrid recommender system is developed which generates recommendation for new users as well as shows improvement in accuracy over the baseline methods.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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Brain networks subserving the evaluation of static and dynamic facial expressions

Because moving depictions of face emotion have greater ecological validity than their static counterparts, it has been suggested that still photographs may not engage ‘authentic’ mechanisms used to recognize facial expressions in everyday life. To date, however, no neuroimaging studies have adequately addressed the question of whether the processing of static and dynamic expressions rely upon different brain substrates. To address this, we performed an functional magnetic resonance imaging (fMRI) experiment wherein participants made emotional expression discrimination and Sex discrimination judgements to static and moving face images. Compared to Sex discrimination, Emotion discrimination was associated with widespread increased activation in regions of occipito-temporal, parietal and frontal cortex. These regions were activated both by moving and by static emotional stimuli, indicating a general role in the interpretation of emotion. However, portions of the inferior frontal gyri and supplementary/pre-supplementary motor area showed task by motion interaction. These regions were most active during emotion judgements to static faces. Our results demonstrate a common neural substrate for recognizing static and moving facial expressions, but suggest a role for the inferior frontal gyrus in supporting simulation processes that are invoked more strongly to disambiguate static emotional cues.

Identification of pre-spike network in patients with mesial temporal lobe epilepsy

Background: Seizures and interictal spikes in mesial temporal lobe epilepsy (MTLE) affect a network of brain regions rather than a single epileptic focus. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) studies have demonstrated a functional network in which hemodynamic changes are time-locked to spikes. However, whether this reflects the propagation of neuronal activity from a focus, or conversely the activation of a network linked to spike generation remains unknown. The functional connectivity (FC) changes prior to spikes may provide information about the connectivity changes that lead to the generation of spikes. We used EEG-fMRI to investigate FC changes immediately prior to the appearance of interictal spikes on EEG in patients with MTLE. Methods/principal findings: Fifteen patients with MTLE underwent continuous EEG-fMRI during rest. Spikes were identified on EEG and three 10 s epochs were defined relative to spike onset: spike (0–10 s), pre-spike (−10 to 0 s), and rest (−20 to −10 s, with no previous spikes in the preceding 45s). Significant spike-related activation in the hippocampus ipsilateral to the seizure focus was found compared to the pre-spike and rest epochs. The peak voxel within the hippocampus ipsilateral to the seizure focus was used as a seed region for FC analysis in the three conditions. A significant change in FC patterns was observed before the appearance of electrographic spikes. Specifically, there was significant loss of coherence between both hippocampi during the pre-spike period compared to spike and rest states. Conclusion/significance: In keeping with previous findings of abnormal inter-hemispheric hippocampal connectivity in MTLE, our findings specifically link reduced connectivity to the period immediately before spikes. This brief decoupling is consistent with a deficit in mutual (inter-hemispheric) hippocampal inhibition that may predispose to spike generation.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

Common psychotic symptoms can be explained by the theory of ecological perception

The symptoms of psychiatric illness are diverse, as are the causes of the illnesses that cause them. Yet, regardless of the heterogeneity of cause and presentation, a great deal of symptoms can be explained by the failure of a single perceptual function – the reprocessing of ecological perception. It is a central tenet of the ecological theory of perception that we perceive opportunities to act. It has also been found that perception automatically causes actions and thoughts to occur unless this primary action pathway is inhibited. Inhibition allows perceptions to be reprocessed into more appropriate alternative actions and thoughts. Reprocessing of this kind takes place over the entire frontal lobe and it renders action optional. Choice about what action to take (if any) is the basis for the feeling of autonomy and ultimately for the sense-of-self. When thoughts and actions occur automatically (without choice) they appear to originate outside of the self, thereby providing prima facie evidence for some of the bizarre delusions that define schizophrenia such as delusional misidentification, delusions of control and Cotard’s delusion. Automatic actions and thoughts are triggered by residual stimulation whenever reprocessing is insufficient to balance automatic excitatory cues (for whatever reason). These may not be noticed if they are neutral and therefore unimportant whereas actions and thoughts with a positive bias are desirable. Responses to negative stimulus, on the other hand, are always unwelcome, because the actions that are triggered will carry the negative bias. Automatic thoughts may include spontaneous positive feelings of love and joy, but automatic negative thoughts and visualisations are experienced as hallucinations. Not only do these feel like they emerge from elsewhere but they carry a negative bias (they are most commonly critical, rude and are irrationally paranoid). Automatic positive actions may include laughter and smiling and these are welcome. Automatic behaviours that carry a negative bias, however, are unwelcome and like hallucinations, occur without a sense of choice. These include crying, stereotypies, perseveration, ataxia, utilization and imitation behaviours and catatonia.

The structure and connectivity of semantic memory in the healthy older adult brain

The anterior temporal lobes (ATLs) have been proposed to serve as a "hub" linking amodal or domain general information about the meaning of words, objects, facts and people distributed throughout the brain in semantic memory. The two primary sources of evidence supporting this proposal, viz. structural imaging studies in semantic dementia (SD) patients and functional imaging investigations, are not without problems. Similarly, knowledge about the anatomo-functional connectivity of semantic memory is limited to a handful of intra-operative electrocortical stimulation (IES) investigations in patients. Here, using principal components analyses (PCA) of a battery of conceptual and non-conceptual tests coupled with voxel based morphometry (VBM) and diffusion tensor imaging (DTI) in a sample of healthy older adults aged 55-85. years, we show that amodal semantic memory relies on a predominantly left lateralised network of grey matter regions involving the ATL, posterior temporal and posterior inferior parietal lobes, with prominent involvement of the left inferior fronto-occipital fasciculus (IFOF) and uncinate fasciculus fibre pathways. These results demonstrate relationships between semantic memory, brain structure and connectivity essential for human communication and cognition.

Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer's disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, highangular resolution diffusion MRI. We adapted GWASs to screen the brain's connectivity pattern, allowing us to discover genetic variants that affect the human brain's wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer's disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

Brain network efficiency and topology depend on the fiber tracking method: 11 tractography algorithms compared in 536 subjects

As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.

New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

Network approach for capturing ligand-induced subtle global changes in protein structures

Ligand-induced conformational changes in proteins are of immense functional relevance. It is a major challenge to elucidate the network of amino acids that are responsible for the percolation of ligand-induced conformational changes to distal regions in the protein from a global perspective. Functionally important subtle conformational changes (at the level of side-chain noncovalent interactions) upon ligand binding or as a result of environmental variations are also elusive in conventional studies such as those using root-mean-square deviations (r.m.s.d.s). In this article, the network representation of protein structures and their analyses provides an efficient tool to capture these variations (both drastic and subtle) in atomistic detail in a global milieu. A generalized graph theoretical metric, using network parameters such as cliques and/or communities, is used to determine similarities or differences between structures in a rigorous manner. The ligand-induced global rewiring in the protein structures is also quantified in terms of network parameters. Thus, a judicious use of graph theory in the context of protein structures can provide meaningful insights into global structural reorganizations upon perturbation and can also be helpful for rigorous structural comparison. Data sets for the present study include high-resolution crystal structures of serine proteases from the S1A family and are probed to quantify the ligand-induced subtle structural variations.

Treewidth: theory and applications to computer science

This report is an introduction to the concept of treewidth, a property of graphs that has important implications in algorithms. Some basic concepts of graph theory are presented in the first chapter for those readers that are not familiar with the notation. In Chapter 2, the definition of treewidth and some different ways of characterizing it are explained. The last two chapters focus on the algorithmic implications of treewidth, which are very relevant in Computer Science. An algorithm to compute the treewidth of a graph is presented and its result can be later applied to many other problems in graph theory, like those introduced in the last chapter.

Efeito da estimulação transcraniana por corrente contínua sobre o desempenho físico: análise das respostas cerebrais, metabólicas e perceptivas durante e após exercícios aeróbio e de força

Estimulação transcraniana por corrente contínua (ETCC) sobre áreas corticais pré-selecionadas, tem aumentado o desempenho físico de diferentes populações. Porém, lacunas persistem no tocante aos mecanismos subjacentes à estes efeitos. Assim, a presente tese objetivou: a) investigar os efeitos da ETCC anódica (aETCC) e placebo (Sham) no córtex motor (CM) de indivíduos saudáveis sobre o desempenho de força máxima; b) comparar os efeitos da ETCC sobre a produção de força máxima e estabilidadade da força durante exercícios máximo e submáximo em sujeitos hemiparéticos e saudáveis; c) investigar o efeito da ETCC sobre a conectividade funcional inter-hemisférica (coerência eletroencefalográfica cEEG) do córtex pré-frontal (CPF), desempenho aeróbio e dispêndio energético (EE) durante e após exercício máximo e submáximo. No 1 estudo, 14 adultos saudáveis executaram 2 sessões de exercício máximo de força (EMF) dos músculos flexores e extensores do joelho dominante (3 séries de 10 rep máximas), precedidos por aETCC ou Sham (2mA; 20 mim). aETCC não foi capaz de aumentar o trabalho total e pico de torque (PT), resistência à fadiga ou atividade eletromiográfica durante o EMF. No 2 estudo, 10 hemiparéticos e 9 sujeitos saudáveis receberam aETCC e Sham no CM. O PT e a estabilidade da força (coeficiente de variação - CV) foram avaliados durante protocolo máximo e submáximo de extensão e flexão unilateral do joelho (1 série de 3 reps a 100% do PT e 2 séries de 10 reps a 50% do PT). Nenhuma diferença no PT foi observada nos dois grupos. Diminuições no CV foram obervadas durante a extensão (~25-35%, P<0.001) e flexão de joelho (~22-33%, P<0.001) após a aETCC comparada com Sham nos hemiparéticos, entretanto, somente o CV na extensão de joelhos diminuiu (~13-27%, P<0.001) nos saudáveis, o que sugere que aETCC pode melhorar o CV, mas não o PT em sujeitos hemiparéticos. No 3 estudo, 9 adultos saudáveis realizaram 2 testes incrementais máximos precedidos por aETCC ou Sham sobre o CPF com as respostas cardiorrespiratórias, percepção de esforço (PSE) e cEEG do CPF sendo monitoradas. O VO2 de pico (42.64.2 vs. 38.23.3 mL.kg.min-1; P=0,02), potência total (252.776.5 vs. 23773.3 W; P=0,05) e tempo de exaustão (531.1140 vs. 486.7115.3 seg; P=0,04) foram maiores após aETCC do que a Sham. Nenhuma diferença foi encontrada para FC e PSE em função da carga de trabalho (P>0,05). A cEEG do CPF aumentou após aETCC vs. repouso (0.700.40 vs. 0.380.05; P=0,001), mas não após Sham vs. repouso (0.360.49 vs. 0.330.50; P=0,06), sugerindo que a aETCC pode retardar a fadiga aumentando a conectividade funcional entre os hemisférios do CPF e desempenho aeróbio durante exercício exaustivo. No 4 estudo, o VO2 e EE foram avaliados em 11 adultos saudáveis antes, durante a aETCC ou Sham no CPF e 30 min após exercício aeróbio submáximo isocalórico (~200kcal). Diferenças não foram observadas no VO2 vs. repouso durante aETCC e Sham (P=0.95 e P=0.85). Porém, a associação entre exercício e aETCC aumentou em ~19% o EE após ao menos, 30 min de recuperação após exercício quando comparada a Sham (P<0,05).

若尔盖自然保护区高原林蛙(Rana kukunoris)扩散模型与景观连接分析

揭示水体中繁殖的两栖动物在异质性景观中的空间扩散特点，探讨景观面积丧失和破碎化对于两栖动物的影响，为两栖动物的保护提供理论依据。本文以四川西北部若尔盖湿地自然保护区的高原林蛙(Rana kukunoris)为研究对象，通过运用地理信息系统及建立景观模型等方法，在分析若尔盖湿地自然保护区范围内现有景观格局的基础上，建立了高原林蛙的景观扩散模型，并模拟了“沼泽→草甸”的湿地逆演化过程下高原林蛙的空间分布与景观连接的变化特点。主要结果是： 1．若尔盖湿地自然保护区呈典型的沼泽—草甸式斑块—基质景观格局。草甸面积占整个景观面积的79.42%，景观蔓延度指数（CONTAG）为79.00远离最小值0而更趋向于最大值100，面积和景观蔓延度指数表明草甸是整个景观中面积占绝对优势且景观连接好的类型，构成了景观的基质，对景观的动态格局演变起主导作用。沼泽面积仅占整个景观面积的18.08%，但却是整个景观中斑块数目最多的单元，占所有斑块数的82.9%。因此沼泽斑块与草甸基质之间的动态结构对高原林蛙的扩散起着决定性的作用。 2．空间扩散模型表明，其它类型的景观不但扩展了高原林蛙的活动范围，而且也为高原林蛙在不同沼泽斑块间的连接提供了通道。高原林蛙的空间扩散区域使得彼此间成斑块化隔离状分布的沼泽形成了潜在景观功能连接，促进了不同斑块间物种的交流。小型沼泽作为垫脚石（stepping-stone），使得整个景观中的相隔距离较远的大型斑块联结为一个功能整体，促进了高原林蛙在整个景观中的相互动态联系。 3．模拟“沼泽→草甸”的湿地逆演化过程表明，大量小型沼泽湿地的消失将会 对在沼泽中繁殖并扩散到其它景观类型中去的高原林蛙造成潜在影响。逆演化过程不仅使沼泽斑块的分布范围，沼泽源斑块的面积和空间扩散面积减少，而且对景观连接也有很大影响。小型沼泽的消失，将使得景观斑块的功能连接变小，使得依靠小型沼泽作为跳板的动物在沼泽斑块之间的移动将变得更加困难。 本文是对生境丧失与破碎化影响下两栖动物的行为反应的一种尝试。影响模型的因素很多，包括动物对各种类型景观的偏好程度，地理数据的精度，及模型的可靠程度都是制约模型准确度的因素。 The spatial diffusion of water—breeding amphibian through heterogeneous landscape and the effects of landscape losing and fragmentation to amphibian were the core theory of the landscape ecology of amphibian. Geographical information system (GIS) and landscape model were used to model the diffused area of Rana kukunoris in Zoige Wetland Natural Reserve. Model was also used to analysis the spatial distribution variation of R. kukunoris and the change of landscape connectivity when simulated the retrogressive succession of landscape. The main results are below: 1. There was peatland—meadow pattern which was typical patch—matrix landscape pattern in Zoige Natural Reserve. The meadow area occupied 79.42% of the entire landscape area, contagion index (CONTAG) was 79.00 which was far away the minimum value (0) but tend to the maximum value (100). Both of these showed that meadow was the largest part and the most continue units. It was shown that meadow was matrix of the landscape, which evolved the leading role to the landscape dynamic pattern. Though their area only occupies 18.08% of entire landscape area, peatlands were according to 82.9% of the total patches. Dynamic of the pattern between peatlands and meadows decided the spatial diffusion of R. kukunoris. 2．The model indicated that the other types of landscape not only expanded diffusion of R. kukunoris, but also have provided the potential channels for frog's connections among different peatlands. The spatial diffusion zone of R. kukunoris forced isolated patch peatlands to be potential landscape functional connectivity. The small peatlands, as stepping-stone, made the large peatlands connect as a functional one and promoted the integrated and dynamic connectivity of R. kukunoris in the whole landscape. 3. The simulation of “peatlands→meadows”retrogressive succession process indicated that the decrease of small peatlands will have potential effect to R. kukunoris because they must bred in peatlands and diffuse to other type of the landscape. Retrogressive succession process not only made the decrease of distribution of peatlands, patches number of peatlands and diffused area of R. kukunoris, but also reduced the connectivity among source patches. As stepping-stone, the disappearance of small peatlands will made the migration of R. kukunoris among patches more difficult. The model was an experiment of the amphibian behavior reaction to habitat losing and fragmentation. There were many factors that could influence the accuracy of model, such as the preference of animals to each type of landscape, the geographical data precision, reliable degree of model.