Discovering items with potential popularity on social media

Predicting the future popularity of online content is highly important in many applications. Preferential attachment phenomena is encountered in scale free networks.Under it's influece popular items get more popular thereby resulting in long tailed distribution problem. Consequently, new items which can be popular (potential ones), are suppressed by the already popular items. This paper proposes a novel model which is able to identify potential items. It identifies the potentially popular items by considering the number of links or ratings it has recieved in recent past along with it's popularity decay. For obtaining an effecient model we consider only temporal features of the content, avoiding the cost of extracting other features. We have found that people follow recent behaviours of their peers. In presence of fit or quality items already popular items lose it's popularity. Prediction accuracy is measured on three industrial datasets namely Movielens, Netflix and Facebook wall post. Experimental results show that compare to state-of-the-art model our model have better prediction accuracy.Comment: 7 pages in ACM style.7 figures and 1 tabl

Abnormal wave reflections and left ventricular hypertrophy late after coarctation of the aorta repair

Patients with repaired coarctation of the aorta are thought to have increased afterload due to abnormalities in vessel structure and function. We have developed a novel cardiovascular magnetic resonance protocol that allows assessment of central hemodynamics, including central aortic systolic blood pressure, resistance, total arterial compliance, pulse wave velocity, and wave reflections. The main study aims were to (1) characterize group differences in central aortic systolic blood pressure and peripheral systolic blood pressure, (2) comprehensively evaluate afterload (including wave reflections) in the 2 groups, and (3) identify possible biomarkers among covariates associated with elevated left ventricular mass (LVM). Fifty adult patients with repaired coarctation and 25 age- and sex-matched controls were recruited. Ascending aorta area and flow waveforms were obtained using a high temporal-resolution spiral phase-contrast cardiovascular magnetic resonance flow sequence. These data were used to derive central hemodynamics and to perform wave intensity analysis noninvasively. Covariates associated with LVM were assessed using multivariable linear regression analysis. There were no significant group differences (P≥0.1) in brachial systolic, mean, or diastolic BP. However central aortic systolic blood pressure was significantly higher in patients compared with controls (113 versus 107 mm Hg, P=0.002). Patients had reduced total arterial compliance, increased pulse wave velocity, and larger backward compression waves compared with controls. LVM index was significantly higher in patients than controls (72 versus 59 g/m(2), P<0.0005). The magnitude of the backward compression waves was independently associated with variation in LVM (P=0.01). Using a novel, noninvasive hemodynamic assessment, we have shown abnormal conduit vessel function after coarctation of the aorta repair, including abnormal wave reflections that are associated with elevated LVM

Impact of valve morphology, hypertension and age on aortic wall properties in patients with coarctation: a two-centre cross-sectional study

Objective: We aimed to investigate the combined effects of arterial hypertension, bicuspid aortic valve disease (BAVD) and age on the distensibility of the ascending and descending aortas in patients with aortic coarctation. Design: Cross-sectional study. Setting: The study was conducted at two university medical centres, located in Berlin and London. Participants: A total of 121 patients with aortic coarctation (ages 1-71 years) underwent cardiac MRI, echocardiography and blood pressure measurements. Outcome measures: Cross-sectional diameters of the ascending and descending aortas were assessed to compute aortic area distensibility. Findings were compared with age-specific reference values. The study complied with the Strengthening the Reporting of Observational Studies in Epidemiology statement and reporting guidelines. Results: Impaired distensibility (below fifth percentile) was seen in 37% of all patients with coarctation in the ascending aorta and in 43% in the descending aorta. BAVD (43%) and arterial hypertension (72%) were present across all ages. In patients >10 years distensibility impairment of the ascending aorta was predominantly associated with BAVD (OR 3.1, 95% CI 1.33 to 7.22, p=0.009). Distensibility impairment of the descending aorta was predominantly associated with arterial hypertension (OR 2.8, 95% CI 1.08 to 7.2, p=0.033) and was most pronounced in patients with uncontrolled hypertension despite antihypertensive treatment. Conclusion: From early adolescence on, both arterial hypertension and BAVD have a major impact on aortic distensibility. Their specific effects differ in strength and localisation (descending vs ascending aorta). Moreover, adequate blood pressure control is associated with improved distensibility. These findings could contribute to the understanding of cardiovascular complications and the management of patients with aortic coarctation

How successful is successful?:Aortic arch shape after successful aortic coarctation repair correlates with left ventricular function

International audienceObjectives: Even after successful aortic coarctation repair, there remains a significant incidence of late systemic hypertension and other morbidities. Independently of residual obstruction, aortic arch morphology alone may affect cardiac function and outcome. We sought to uncover the relationship of arch 3-dimensional shape features with functional data obtained from cardiac magnetic resonance scans.Methods: Three-dimensional aortic arch shape models of 53 patients (mean age, 22.3 ± 5.6 years) 12 to 38 years after aortic coarctation repair were reconstructed from cardiac magnetic resonance data. A novel validated statistical shape analysis method computed a 3-dimensional mean anatomic shape of all aortic arches and calculated deformation vectors of the mean shape toward each patient's arch anatomy. From these deformations, 3-dimensional shape features most related to left ventricular ejection fraction, indexed left ventricular end-diastolic volume, indexed left ventricular mass, and resting systolic blood pressure were extracted from the deformation vectors via partial least-squares regression.Results: Distinct arch shape features correlated significantly with left ventricular ejection fraction (r = 0.42, P = .024), indexed left ventricular end-diastolic volume (r = 0.65, P < .001), and indexed left ventricular mass (r = 0.44, P = .014). Lower left ventricular ejection fraction, larger indexed left ventricular end-diastolic volume, and increased indexed left ventricular mass were identified with an aortic arch shape that has an elongated ascending aorta with a high arch height-to-width ratio, a relatively short proximal transverse arch, and a relatively dilated descending aorta. High blood pressure seemed to be linked to gothic arch shape features, but this did not achieve statistical significance.Conclusions: Independently of hemodynamically important arch obstruction or residual aortic coarctation, specific aortic arch shape features late after successful aortic coarctation repair seem to be associated with worse left ventricular function. Analyzing 3-dimensional shape information via statistical shape modeling can be an adjunct to long-term risk assessment in patients after aortic coarctation repair

Fretting Wear Analysis of Different Tube Materials Used in Heat Exchanger Tube Bundle

Research on heat exchange is being carried out for more than five decades because of its importance in process industries and power generation plants. Heat exchanger experiencing cross flow are vulnerable to flow induced vibration. These vibration causes the interaction of tubes with the baffle resulting in a fretting wear of the tubes. Present study focuses on the fretting wear analysis of different tube materials. Fretting wear tests were performed on aluminum, copper and stainless steel instrumented central tubes against mild steel baffle. For each tube material the tests were performed for three different test durations i.e. 60 minutes, 120 minutes and 180 minutes at a cross flow velocity of 0.55 m/s. It was observed that vibrational amplitude of the flexible test tube is affected by its weight. A scanning electron microscope was used to analyze and measure the sizes of wear scar. The results indicated that wear loss in case of aluminum tube is the highest while that in case of stainless steel tube is the lowest

A Novel Temporal Network-Embedding Algorithm for Link Prediction in Dynamic Networks

Understanding the evolutionary patterns of real-world complex systems such as human interactions, biological interactions, transport networks, and computer networks is important for our daily lives. Predicting future links among the nodes in these dynamic networks has many practical implications. This research aims to enhance our understanding of the evolution of networks by formulating and solving the link-prediction problem for temporal networks using graph representation learning as an advanced machine learning approach. Learning useful representations of nodes in these networks provides greater predictive power with less computational complexity and facilitates the use of machine learning methods. Considering that existing models fail to consider the temporal dimensions of the networks, this research proposes a novel temporal network-embedding algorithm for graph representation learning. This algorithm generates low-dimensional features from large, high-dimensional networks to predict temporal patterns in dynamic networks. The proposed algorithm includes a new dynamic node-embedding algorithm that exploits the evolving nature of the networks by considering a simple three-layer graph neural network at each time step and extracting node orientation by using Given&rsquo;s angle method. Our proposed temporal network-embedding algorithm, TempNodeEmb, is validated by comparing it to seven state-of-the-art benchmark network-embedding models. These models are applied to eight dynamic protein&ndash;protein interaction networks and three other real-world networks, including dynamic email networks, online college text message networks, and human real contact datasets. To improve our model, we have considered time encoding and proposed another extension to our model, TempNodeEmb++. The results show that our proposed models outperform the state-of-the-art models in most cases based on two evaluation metrics

A Novel Temporal Network-Embedding Algorithm for Link Prediction in Dynamic Networks

Understanding the evolutionary patterns of real-world complex systems such as human interactions, biological interactions, transport networks, and computer networks is important for our daily lives. Predicting future links among the nodes in these dynamic networks has many practical implications. This research aims to enhance our understanding of the evolution of networks by formulating and solving the link-prediction problem for temporal networks using graph representation learning as an advanced machine learning approach. Learning useful representations of nodes in these networks provides greater predictive power with less computational complexity and facilitates the use of machine learning methods. Considering that existing models fail to consider the temporal dimensions of the networks, this research proposes a novel temporal network-embedding algorithm for graph representation learning. This algorithm generates low-dimensional features from large, high-dimensional networks to predict temporal patterns in dynamic networks. The proposed algorithm includes a new dynamic node-embedding algorithm that exploits the evolving nature of the networks by considering a simple three-layer graph neural network at each time step and extracting node orientation by using Given’s angle method. Our proposed temporal network-embedding algorithm, TempNodeEmb, is validated by comparing it to seven state-of-the-art benchmark network-embedding models. These models are applied to eight dynamic protein–protein interaction networks and three other real-world networks, including dynamic email networks, online college text message networks, and human real contact datasets. To improve our model, we have considered time encoding and proposed another extension to our model, TempNodeEmb++. The results show that our proposed models outperform the state-of-the-art models in most cases based on two evaluation metrics

Mycobacterium tuberculosis Rv0580c Impedes the Intracellular Survival of Recombinant Mycobacteria, Manipulates the Cytokines, and Induces ER Stress and Apoptosis in Host Macrophages via NF-κB and p38/JNK Signaling

The Mycobacterium tuberculosis (M. tb) genome encodes a large number of hypothetical proteins, which need to investigate their role in physiology, virulence, pathogenesis, and host interaction. To explore the role of hypothetical protein Rv0580c, we constructed the recombinant Mycobacterium smegmatis (M. smegmatis) strain, which expressed the Rv0580c protein heterologously. We observed that Rv0580c expressing M. smegmatis strain (Ms_Rv0580c) altered the colony morphology and increased the cell wall permeability, leading to this recombinant strain becoming susceptible to acidic stress, oxidative stress, cell wall-perturbing stress, and multiple antibiotics. The intracellular survival of Ms_Rv0580c was reduced in THP-1 macrophages. Ms_Rv0580c up-regulated the IFN-γ expression via NF-κB and JNK signaling, and down-regulated IL-10 expression via NF-κB signaling in THP-1 macrophages as compared to control. Moreover, Ms_Rv0580c up-regulated the expression of HIF-1α and ER stress marker genes via the NF-κB/JNK axis and JNK/p38 axis, respectively, and boosted the mitochondria-independent apoptosis in macrophages, which might be lead to eliminate the intracellular bacilli. This study explores the crucial role of Rv0580c protein in the physiology and novel host-pathogen interactions of mycobacteria