Pain Research Forum: application of scientific social media frameworks in neuroscience

Background: Social media has the potential to accelerate the pace of biomedical research through online collaboration, discussions, and faster sharing of information. Focused web-based scientific social collaboratories such as the Alzheimer Research Forum have been successful in engaging scientists in open discussions of the latest research and identifying gaps in knowledge. However, until recently, tools to rapidly create such communities and provide high-bandwidth information exchange between collaboratories in related fields did not exist. Methods: We have addressed this need by constructing a reusable framework to build online biomedical communities, based on Drupal, an open-source content management system. The framework incorporates elements of Semantic Web technology combined with social media. Here we present, as an exemplar of a web community built on our framework, the Pain Research Forum (PRF) (http://painresearchforum.org). PRF is a community of chronic pain researchers, established with the goal of fostering collaboration and communication among pain researchers. Results: Launched in 2011, PRF has over 1300 registered members with permission to submit content. It currently hosts over 150 topical news articles on research; more than 30 active or archived forum discussions and journal club features; a webinar series; an editor-curated weekly updated listing of relevant papers; and several other resources for the pain research community. All content is licensed for reuse under a Creative Commons license; the software is freely available. The framework was reused to develop other sites, notably the Multiple Sclerosis Discovery Forum (http://msdiscovery.org) and StemBook (http://stembook.org). Discussion: Web-based collaboratories are a crucial integrative tool supporting rapid information transmission and translation in several important research areas. In this article, we discuss the success factors, lessons learned, and ongoing challenges in using PRF as a driving force to develop tools for online collaboration in neuroscience. We also indicate ways these tools can be applied to other areas and uses

Location prediction based on a sector snapshot for location-based services

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shaped cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the new Markov-based mobility prediction (NMMP) and prediction location model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression, and insufficient accuracy. In this paper, a novel cell splitting algorithm is proposed. Also, a new prediction technique is introduced. The cell splitting is universal so it can be applied to all types of cells. Meanwhile, this algorithm is implemented to the Micro cell in parallel with the new prediction technique. The prediction technique, compared with two classic prediction techniques and the experimental results, show the effectiveness and robustness of the new splitting algorithm and prediction technique

Machine Learning for Smart and Energy-Efficient Buildings

Energy consumption in buildings, both residential and commercial, accounts for approximately 40% of all energy usage in the U.S., and similar numbers are being reported from countries around the world. This significant amount of energy is used to maintain a comfortable, secure, and productive environment for the occupants. So, it is crucial that the energy consumption in buildings must be optimized, all the while maintaining satisfactory levels of occupant comfort, health, and safety. Recently, Machine Learning has been proven to be an invaluable tool in deriving important insights from data and optimizing various systems. In this work, we review the ways in which machine learning has been leveraged to make buildings smart and energy-efficient. For the convenience of readers, we provide a brief introduction of several machine learning paradigms and the components and functioning of each smart building system we cover. Finally, we discuss challenges faced while implementing machine learning algorithms in smart buildings and provide future avenues for research at the intersection of smart buildings and machine learning

An intuitionistic approach to scoring DNA sequences against transcription factor binding site motifs

Background: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs is a crucial problem in computational biology and includes the subtask of predicting the location of known TFBS motifs in a given DNA sequence. It has previously been shown that, when scoring matches to known TFBS motifs, interdependencies between positions within a motif should be taken into account. However, this remains a challenging task owing to the fact that sequences similar to those of known TFBSs can occur by chance with a relatively high frequency. Here we present a new method for matching sequences to TFBS motifs based on intuitionistic fuzzy sets (IFS) theory, an approach that has been shown to be particularly appropriate for tackling problems that embody a high degree of uncertainty. Results: We propose SCintuit, a new scoring method for measuring sequence-motif affinity based on IFS theory. Unlike existing methods that consider dependencies between positions, SCintuit is designed to prevent overestimation of less conserved positions of TFBSs. For a given pair of bases, SCintuit is computed not only as a function of their combined probability of occurrence, but also taking into account the individual importance of each single base at its corresponding position. We used SCintuit to identify known TFBSs in DNA sequences. Our method provides excellent results when dealing with both synthetic and real data, outperforming the sensitivity and the specificity of two existing methods in all the experiments we performed. Conclusions: The results show that SCintuit improves the prediction quality for TFs of the existing approaches without compromising sensitivity. In addition, we show how SCintuit can be successfully applied to real research problems. In this study the reliability of the IFS theory for motif discovery tasks is proven

Deconfining Phase Transition as a Matrix Model of Renormalized Polyakov Loops

We discuss how to extract renormalized from bare Polyakov loops in SU(N) lattice gauge theories at nonzero temperature in four spacetime dimensions. Single loops in an irreducible representation are multiplicatively renormalized without mixing, through a renormalization constant which depends upon both representation and temperature. The values of renormalized loops in the four lowest representations of SU(3) were measured numerically on small, coarse lattices. We find that in magnitude, condensates for the sextet and octet loops are approximately the square of the triplet loop. This agrees with a large $N$ expansion, where factorization implies that the expectation values of loops in adjoint and higher representations are just powers of fundamental and anti-fundamental loops. For three colors, numerically the corrections to the large $N$ relations are greatest for the sextet loop, $\leq 25$; these represent corrections of $\sim 1/N$ for N=3. The values of the renormalized triplet loop can be described by an SU(3) matrix model, with an effective action dominated by the triplet loop. In several ways, the deconfining phase transition for N=3 appears to be like that in the $N=\infty$ matrix model of Gross and Witten.Comment: 24 pages, 7 figures; v2, 27 pages, 12 figures, extended discussion for clarity, results unchange

The Fire and Tree Mortality Database, for Empirical Modeling of Individual Tree Mortality After Fire

Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research

Dispersion, solvent and metal effects in the binding of gold cations to alkynyl ligands: implications for Au(i) catalysis.

The coordination modes of the [Au(PPh3)](+) cation to metal alkynyl complexes have been investigated. On addition to ruthenium, a vinylidene complex, [Ru(η(5)-C5H5)(PPh3)2([double bond, length as m-dash]C[double bond, length as m-dash]CPh{AuPPh3})](+), is obtained while addition to a gold(iii) compound gives di- and trinuclear gold complexes depending on the conditions employed. In the trinuclear species, a gold(i) cation is sandwiched between two gold(iii) alkynyl complexes, suggesting that coordination of multiple C-C triple bonds to gold is facile

A novel piggybac transposon inducible expression system identifies a role for akt signalling in primordial germ cell migration

In this work, we describe a single piggyBac transposon system containing both a tet-activator and a doxycycline-inducible expression cassette. We demonstrate that a gene product can be conditionally expressed from the integrated transposon and a second gene can be simultaneously targeted by a short hairpin RNA contained within the transposon, both in vivo and in mammalian and avian cell lines. We applied this system to stably modify chicken primordial germ cell (PGC) lines in vitro and induce a reporter gene at specific developmental stages after injection of the transposon-modified germ cells into chicken embryos. We used this vector to express a constitutively-active AKT molecule during PGC migration to the forming gonad. We found that PGC migration was retarded and cells could not colonise the forming gonad. Correct levels of AKT activation are thus essential for germ cell migration during early embryonic development

Abiraterone acetate plus prednisolone for metastatic patients starting hormone therapy: 5-year follow-up results from the STAMPEDE randomised trial (NCT00268476)

Abiraterone acetate plus prednisolone (AAP) previously demonstrated improved survival in STAMPEDE, a multiarm, multistage platform trial in men starting long-term hormone therapy for prostate cancer. This long-term analysis in metastatic patients was planned for 3 years after the first results. Standard-of-care (SOC) was androgen deprivation therapy. The comparison randomised patients 1:1 to SOC-alone with or without daily abiraterone acetate 1000 mg + prednisolone 5 mg (SOC + AAP), continued until disease progression. The primary outcome measure was overall survival. Metastatic disease risk group was classified retrospectively using baseline CT and bone scans by central radiological review and pathology reports. Analyses used Cox proportional hazards and flexible parametric models, accounting for baseline stratification factors. One thousand and three patients were contemporaneously randomised (November 2011 to January 2014): median age 67 years; 94% newly-diagnosed; metastatic disease risk group: 48% high, 44% low, 8% unassessable; median PSA 97 ng/mL. At 6.1 years median follow-up, 329 SOC-alone deaths (118 low-risk, 178 high-risk) and 244 SOC + AAP deaths (75 low-risk, 145 high-risk) were reported. Adjusted HR = 0.60 (95% CI: 0.50-0.71; P = 0.31 × 10−9) favoured SOC + AAP, with 5-years survival improved from 41% SOC-alone to 60% SOC + AAP. This was similar in low-risk (HR = 0.55; 95% CI: 0.41-0.76) and high-risk (HR = 0.54; 95% CI: 0.43-0.69) patients. Median and current maximum time on SOC + AAP was 2.4 and 8.1 years. Toxicity at 4 years postrandomisation was similar, with 16% patients in each group reporting grade 3 or higher toxicity. A sustained and substantial improvement in overall survival of all metastatic prostate cancer patients was achieved with SOC + abiraterone acetate + prednisolone, irrespective of metastatic disease risk group

Direct Numerical Simulation of Turbulent Heat Transfer Modulation in Micro-Dispersed Channel Flow

The object of this paper is to study the influence of dispersed micrometer size particles on turbulent heat transfer mechanisms in wall-bounded flows. The strategic target of the current research is to set up a methodology to size and design new-concept heat transfer fluids with properties given by those of the base fluid modulated by the presence of dynamically-interacting, suitably-chosen, discrete micro- and nano- particles. We run Direct Numerical Simulation (DNS) for hydrodynamically fully-developed, thermally-developing turbulent channel flow at shear Reynolds number Re=150 and Prandtl number Pr=3, and we tracked two large swarms of particles, characterized by different inertia and thermal inertia. Preliminary results on velocity and temperature statistics for both phases show that, with respect to single-phase flow, heat transfer fluxes at the walls increase by roughly 2% when the flow is laden with the smaller particles, which exhibit a rather persistent stability against non-homogeneous distribution and near-wall concentration. An opposite trend (slight heat transfer flux decrease) is observed when the larger particles are dispersed into the flow. These results are consistent with previous experimental findings and are discussed in the frame of the current research activities in the field. Future developments are also outlined.Comment: Pages: 305-32