A Recurrent Neural Network Survival Model: Predicting Web User Return Time

The size of a website's active user base directly affects its value. Thus, it is important to monitor and influence a user's likelihood to return to a site. Essential to this is predicting when a user will return. Current state of the art approaches to solve this problem come in two flavors: (1) Recurrent Neural Network (RNN) based solutions and (2) survival analysis methods. We observe that both techniques are severely limited when applied to this problem. Survival models can only incorporate aggregate representations of users instead of automatically learning a representation directly from a raw time series of user actions. RNNs can automatically learn features, but can not be directly trained with examples of non-returning users who have no target value for their return time. We develop a novel RNN survival model that removes the limitations of the state of the art methods. We demonstrate that this model can successfully be applied to return time prediction on a large e-commerce dataset with a superior ability to discriminate between returning and non-returning users than either method applied in isolation.Comment: Accepted into ECML PKDD 2018; 8 figures and 1 tabl

Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table

Water in the electrical double layer of ionic liquids on graphene

The performance of electrochemical devices using ionic liquids (ILs) as electrolytes can be impaired by water uptake. This work investigates the influence of water on the behavior of hydrophilic and hydrophobic ILs─with ethylsulfate and tris(perfluoroalkyl)trifluorophosphate or bis(trifluoromethyl sulfonyl)imide (TFSI) anions, respectively─on electrified graphene, a promising electrode material. The results show that water uptake slightly reduces the IL electrochemical stability and significantly influences graphene's potential of zero charge, which is justified by the extent of anion depletion from the surface. Experiments confirm the dominant contribution of graphene's quantum capacitance (CQ) to the total interfacial capacitance (Cint) near the PZC, as expected from theory. Combining theory and experiments reveals that the hydrophilic IL efficiently screens surface charge and exhibits the largest double layer capacitance (CIL ∼ 80 μF cm-2), so that CQ governs the charge stored. The hydrophobic ILs are less efficient in charge screening and thus exhibit a smaller capacitance (CIL ∼ 6-9 μF cm-2), which governs Cint already at small potentials. An increase in the total interfacial capacitance is observed at positive voltages for humid TFSI-ILs relative to dry ones, consistent with the presence of a satellite peak. Short-range surface forces reveal the change of the interfacial layering with potential and water uptake owing to reorientation of counterions, counterion binding, co-ion repulsion, and water enrichment. These results are consistent with the charge being mainly stored in a ∼2 nm-thick double layer, which implies that ILs behave as highly concentrated electrolytes. This knowledge will advance the design of IL-graphene-based electrochemical devices

Vectorlike Confinement at the LHC

We argue for the plausibility of a broad class of vectorlike confining gauge theories at the TeV scale which interact with the Standard Model predominantly via gauge interactions. These theories have a rich phenomenology at the LHC if confinement occurs at the TeV scale, while ensuring negligible impact on precision electroweak and flavor observables. Spin-1 bound states can be resonantly produced via their mixing with Standard Model gauge bosons. The resonances promptly decay to pseudo-Goldstone bosons, some of which promptly decay to a pair of Standard Model gauge bosons, while others are charged and stable on collider time scales. The diverse set of final states with little background include multiple photons and leptons, missing energy, massive stable charged particles and the possibility of highly displaced vertices in dilepton, leptoquark or diquark decays. Among others, a novel experimental signature of resonance reconstruction out of massive stable charged particles is highlighted. Some of the long-lived states also constitute Dark Matter candidates.Comment: 33 pages, 6 figures. v4: expanded discussion of Z_2 symmetry for stability, one reference adde

Strong Double Higgs Production at the LHC

The hierarchy problem and the electroweak data, together, provide a plausible motivation for considering a light Higgs emerging as a pseudo-Goldstone boson from a strongly-coupled sector. In that scenario, the rates for Higgs production and decay differ significantly from those in the Standard Model. However, one genuine strong coupling signature is the growth with energy of the scattering amplitudes among the Goldstone bosons, the longitudinally polarized vector bosons as well as the Higgs boson itself. The rate for double Higgs production in vector boson fusion is thus enhanced with respect to its negligible rate in the SM. We study that reaction in pp collisions, where the production of two Higgs bosons at high pT is associated with the emission of two forward jets. We concentrate on the decay mode hh -> WW^(*)WW^(*) and study the semi-leptonic decay chains of the W's with 2, 3 or 4 leptons in the final states. While the 3 lepton final states are the most relevant and can lead to a 3 sigma signal significance with 300 fb^{-1} collected at a 14 TeV LHC, the two same-sign lepton final states provide complementary information. We also comment on the prospects for improving the detectability of double Higgs production at the foreseen LHC energy and luminosity upgrades.Comment: 54 pages, 26 figures. v2: typos corrected, a few comments and one table added. Version published in JHE

Pay-it-forward dual gonorrhea/chlamydia test uptake among men who have sex with men in China: a pragmatic, quasi-experimental study

Background: Chinese men who have sex with men (MSM) rarely receive gonorrhea/chlamydia testing. The purpose of this pilot study was to evaluate a pay-it-forward strategy to increase gonorrhea/chlamydia testing among MSM. Pay-it-forward has one person receive a gift, then asks the same person if they would like to give a gift to another person. Methods: We used a quasi-experimental pragmatic study to compare a pay-it-forward model to standard of care at two HIV testing sites for MSM. A pay-it-forward program was implemented for three months, during which men were offered free gonorrhea/chlamydia testing and given the option of donating money toward testing for future participants. Both sites then switched to standard of care for three months, offering dual testing at the standard price. We compared test uptake and financial costs in the two groups. Findings: 408 men were included in this study. 203 men were offered pay-it-forward, and 205 were offered standard of care. Overall, 109 (109/203, 53·7%) men received gonorrhea/chlamydia testing in the pay-it-forward group and 12 (12/205, 5·9%) men received gonorrhea/chlamydia testing in the standard of care group (adjusted odds ratio 19·73, 95%CI 10·02-38·85). This was a first gonorrhea or chlamydia test for 86% (104/121) of men. 89% (97/109) of men in the pay-it-forward group donated some amount. The incremental unit cost per test in the pay-it-forward group was 67 USD, compared to 503 USD in the standard of care group. Interpretation: Pay-it-forward may be a sustainable model for expanding integrated HIV testing services among MSM in China

Mechanical activation of vinculin binding to talin locks talin in an unfolded conformation

The force-dependent interaction between talin and vinculin plays a crucial role in the initiation and growth of focal adhesions. Here we use magnetic tweezers to characterise the mechano-sensitive compact N-terminal region of the talin rod, and show that the three helical bundles R1-R3 in this region unfold in three distinct steps consistent with the domains unfolding independently. Mechanical stretching of talin R1-R3 enhances its binding to vinculin and vinculin binding inhibits talin refolding after force is released. Mutations that stabilize R3 identify it as the initial mechano-sensing domain in talin, unfolding at ~5 pN, suggesting that 5 pN is the force threshold for vinculin binding and adhesion progression

Metabolomics in Early Alzheimer's Disease: Identification of Altered Plasma Sphingolipidome Using Shotgun Lipidomics

The development of plasma biomarkers could facilitate early detection, risk assessment and therapeutic monitoring in Alzheimer's disease (AD). Alterations in ceramides and sphingomyelins have been postulated to play a role in amyloidogensis and inflammatory stress related neuronal apoptosis; however few studies have conducted a comprehensive analysis of the sphingolipidome in AD plasma using analytical platforms with accuracy, sensitivity and reproducibility.We prospectively analyzed plasma from 26 AD patients (mean MMSE 21) and 26 cognitively normal controls in a non-targeted approach using multi-dimensional mass spectrometry-based shotgun lipidomics to determine the levels of over 800 molecular species of lipids. These data were then correlated with diagnosis, apolipoprotein E4 genotype and cognitive performance. Plasma levels of species of sphingolipids were significantly altered in AD. Of the 33 sphingomyelin species tested, 8 molecular species, particularly those containing long aliphatic chains such as 22 and 24 carbon atoms, were significantly lower (p<0.05) in AD compared to controls. Levels of 2 ceramide species (N16:0 and N21:0) were significantly higher in AD (p<0.05) with a similar, but weaker, trend for 5 other species. Ratios of ceramide to sphingomyelin species containing identical fatty acyl chains differed significantly between AD patients and controls. MMSE scores were correlated with altered mass levels of both N20:2 SM and OH-N25:0 ceramides (p<0.004) though lipid abnormalities were observed in mild and moderate AD. Within AD subjects, there were also genotype specific differences.In this prospective study, we used a sensitive multimodality platform to identify and characterize an essentially uniform but opposite pattern of disruption in sphingomyelin and ceramide mass levels in AD plasma. Given the role of brain sphingolipids in neuronal function, our findings provide new insights into the AD sphingolipidome and the potential use of metabolomic signatures as peripheral biomarkers

British Colonialism and the Criminalization of Homosexuality

What explains the global variation in laws criminalizing homosexual conduct? Recent research has claimed that British colonialism is largely responsible for the criminalization of homosexuality around the world. This article utilizes a newly constructed dataset that includes up-to-date data on 185 countries to assess this claim. We find that British colonies are much more likely to have criminalization of homosexual conduct laws than other colonies or other states in general. This result holds after controlling for other variables that might be expected to influence the likelihood of repressive lesbian, gay, bisexual and transgender (LGBT) rights legislation. However, we also find that the evidence in favour of the claim that British imperialism ‘poisoned’ societies against homosexuality is weak. British colonies do not systematically take longer to decriminalize homosexual conduct than other European colonies

A close examination of double filtering with fold change and t test in microarray analysis

<p>Abstract</p> <p>Background</p> <p>Many researchers use the double filtering procedure with fold change and <it>t </it>test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods.</p> <p>Results</p> <p>This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while <it>t </it>statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure.</p> <p>Conclusion</p> <p>We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure.</p