Simultaneous Inference of User Representations and Trust

Inferring trust relations between social media users is critical for a number of applications wherein users seek credible information. The fact that available trust relations are scarce and skewed makes trust prediction a challenging task. To the best of our knowledge, this is the first work on exploring representation learning for trust prediction. We propose an approach that uses only a small amount of binary user-user trust relations to simultaneously learn user embeddings and a model to predict trust between user pairs. We empirically demonstrate that for trust prediction, our approach outperforms classifier-based approaches which use state-of-the-art representation learning methods like DeepWalk and LINE as features. We also conduct experiments which use embeddings pre-trained with DeepWalk and LINE each as an input to our model, resulting in further performance improvement. Experiments with a dataset of $\sim$356K user pairs show that the proposed method can obtain an high F-score of 92.65%.Comment: To appear in the proceedings of ASONAM'17. Please cite that versio

Spiers Memorial Lecture. Next generation nanoelectrochemistry: the fundamental advances needed for applications

Nanoelectrochemistry, where electrochemical processes are controlled and investigated with nanoscale resolution, is gaining more and more attention because of the many potential applications in energy and sensing and the fact that there is much to learn about fundamental electrochemical processes when we explore them at the nanoscale. The development of instrumental methods that can explore the heterogeneity of electrochemistry occurring across an electrode surface, monitoring single molecules or many single nanoparticles on a surface simultaneously, have been pivotal in giving us new insights into nanoscale electrochemistry. Equally important has been the ability to synthesise or fabricate nanoscale entities with a high degree of control that allows us to develop nanoscale devices. Central to the latter has been the incredible advances in nanomaterial synthesis where electrode materials with atomic control over electrochemically active sites can be achieved. After introducing nanoelectrochemistry, this paper focuses on recent developments in two major application areas of nanoelectrochemistry; electrocatalysis and using single entities in sensing. Discussion of the developments in these two application fields highlights some of the advances in the fundamental understanding of nanoelectrochemical systems really driving these applications forward. Looking into our nanocrystal ball, this paper then highlights: the need to understand the impact of nanoconfinement on electrochemical processes, the need to measure many single entities, the need to develop more sophisticated ways of treating the potentially large data sets from measuring such many single entities, the need for more new methods for characterising nanoelectrochemical systems as they operate and the need for material synthesis to become more reproducible as well as possess more nanoscale control

Biophysical Coarse-Grained Modeling Provides Insights into Transport through the Nuclear Pore Complex

AbstractThe nuclear pore complex (NPC) is the gatekeeper of the nucleus, capable of actively discriminating between the active and inert cargo while accommodating a high rate of translocations. The biophysical mechanisms underlying transport, however, remain unclear due to the lack of information about biophysical factors playing role in transport. Based on published experimental data, we have established a coarse-grained model of an intact NPC structure to examine nucleocytoplasmic transport with refined spatial and temporal resolutions. Using our model, we estimate the transport time versus cargo sizes. Our findings suggest that the mean transport time of cargos smaller than 15 nm is independent of size, while beyond this size, there is a sharp increase in the mean transport time. The model confirms that kap-FG hydrophobicity is sufficient for active cargo transport. Moreover, our model predicts that during translocation, small and large cargo-complexes are hydrophobically attached to FG-repeat domains for 86 and 96% of their transport time, respectively. Inside the central channel FG-repeats form a thick layer on the wall leaving an open tube. The cargo-complex is almost always attached to this layer and diffuses back and forth, regardless of the cargo size. Finally, we propose a plausible model for transport in which the NPC can be viewed as a lubricated gate. This model incorporates basic assumptions underlying virtual-gate and reduction-of-dimensionality models with the addition of the FG-layer inside the central channel acting as a lubricant

Surface coupling effects on the capacitance of thin insulating films

A general form for the surface roughness effects on the capacitance of a capacitor is proposed. We state that a capacitor with two uncoupled rough surfaces could be treated as two capacitors in series which have been divided from the mother capacitor by a slit. This is in contrast to the case where the two rough surfaces are coupled. When the rough surfaces are coupled, the type of coupling decides the modification of the capacitance in comparison to the uncoupled case. It is shown that if the coupling between the two surfaces of the capacitor is positive (negative), the capacitance is less (higher) than the case of two uncoupled rough plates. Also, we state that when the correlation length and the roughness exponent are small, the coupling effect is not negligible

IDENTIFYING SUITABLE LOCATIONS FOR MANGROVE PLANTATION USING GEOSPATIAL INFORMATION SYSTEM AND REMOTE SENSING

Mangroves provide numerous environmental benefits, such as carbon sequestration, water purification, climate change mitigation, and flood and Tsunami impact reduction. Despite these unique advantages, mangroves are threatened by the combined adverse impacts of human activities and climate change. Therefore, it is essential to implement reasonable practices to avoid further degradation of mangroves and provide efficient workflows to increase their extent. Accordingly, better plantation policies are principally required for their conservation and rehabilitation. In this study, we desired to detect suitable locations for mangrove plantation in coastal areas of Hormozgan Province, Iran. We considered a relatively new Multi Criteria Decision Making (MCDM) technique to combine ten criteria derived from remote sensing in a GIS environment. The Best Worst Method (BWM), as an MDCM technique, was implemented to determine the relative importance of each criterion. Afterward, all criteria were aggregated using the Weighted Linear Combination (WLC) method to produce a mangrove plantation suitability map. Statistical measures, including Overall Accuracy (OA = 95%), Kappa Coefficient (KC = 87.9%), and Area Under Curve (AUC = 98.79%), indicated the high applicability of the implemented method for mangrove plantation site allocation. The produced map could give managers a profound insight into finding optimal spots to plant mangroves

The active form of quinol-dependent Nitric Oxide reductase (qNOR) from Neisseria meningitidis is a dimer

Neisseria meningitidis is carried by nearly a billion humans, causing developmental impairment and over 100 000 deaths a year. A quinol-dependent nitric oxide reductase (qNOR) plays a critical role in the survival of the bacterium in the human host. X-ray crystallographic analyses of qNOR, including that from N. meningitidis (NmqNOR) reported here at 3.15 Å resolution, show monomeric assemblies, despite the more active dimeric sample being used for crystallization. Cryo-electron microscopic analysis of the same chromatographic fraction of NmqNOR, however, revealed a dimeric assembly at 3.06 Å resolution. It is shown that zinc (which is used in crystallization) binding near the dimer-stabilizing TMII region contributes to the disruption of the dimer. A similar destabilization is observed in the monomeric (∼85 kDa) cryo-EM structure of a mutant (Glu494Ala) qNOR from the opportunistic pathogen Alcaligenes (Achromobacter) xylosoxidans, which primarily migrates as a monomer. The monomer–dimer transition of qNORs seen in the cryo-EM and crystallographic structures has wider implications for structural studies of multimeric membrane proteins. X-ray crystallographic and cryo-EM structural analyses have been performed on the same chromatographic fraction of NmqNOR to high resolution. This represents one of the first examples in which the two approaches have been used to reveal a monomeric assembly in crystallo and a dimeric assembly in vitrified cryo-EM grids. A number of factors have been identified that may trigger the destabilization of helices that are necessary to preserve the integrity of the dimer. These include zinc binding near the entry of the putative proton-transfer channel and the preservation of the conformational integrity of the active site. The mutation near the active site results in disruption of the active site, causing an additional destabilization of helices (TMIX and TMX) that flank the proton-transfer channel helices, creating an inert monomeric enzyme

Quantitative Measurable Concepts to Visualize Business Process Improvement

Business process improvement evaluation enables performance indicators to be used alongside process improvement techniques in order to quantitatively compare measurement information between the as-is and to-be processes. Limitations of the present methods of business process improvement indicate there is scope for looking at the problem in a different way. Business processes are commonly modelled as diagrams which at their fundamental level are complex networks. This suggests the question as to whether complex network analysis (CNA) has anything to contribute to business process improvement. We develop a technique of projecting a business process model onto the sub-space of a complex network and identify the measurable concepts that can be useful in business process improvement. The measurable concepts from CNA are combined with Time and Cost metrics from the simulation technique to visualize and track improvement efforts and satisfy improvement requirements