dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments This project is partly based on the platform NUM3D (partners:  UTT, ENSAM, and CReSTIC for URCA). The author also thanks the  Champagne-Ardenne region  and the  General Council. Advice on AM material from  Julien Gardan of Aztech  society and help from  Alexandre Schneider  from the  University of Reims  deserve the authors' heartfelt thanks.
Recordings were performed at 37°i n the presence of adenosine deaminase (5 g/ml) and, if indicated, of CGS21680 (10 M). Optical stacks were acquired in Visiview 1. 7. 0 (Visitron Systems, Puchheim, Germany) as described previously  (17)  with the following modifications. The minimum length of a cognate trajectory was 50 frames. An intermission by quantum dot blinking of 10 frames duration was tolerated. Recordings with longer blinking events were dismissed, as were trajectories with out-of-focus events. Stacks were recorded at a rate of 50 frames/s, except when full frames were acquired (ϳ30 frames/s). To exclude spurious trajectories, cells were visualized by bright field illumination immediately after the fluorescence recordings. Analysis of Quantum Dot Trajectories-Stack files were analyzed in MATLAB R2009a (MathWorks, Natick, MA) as described previously  (17).
The set of parameter estimates () comprises the diffusion coefficients characteristic of states 1 and 2 (D1 and D2) and the probabilities of the particle transitioning between state 1 and state 2 (p12 and p21). We implemented, in MATLAB R2011a, the algorithms devised by Das et al. (21). For an estimation of forward-backward variables, we made use of the compatible fwdback. m program file, which replaced algorithms 2 and 4 in Ref. 21. The likelihood of the estimate of is proportional to the joint probability density function of all the tracks from one experimental group as given by L͉͕͑T j ͖ N ͒ ϳ p͕͑T j ͖ N ͉ ͒ ϭ j ϭ 1 N ͑P͑T j ͉ ͒͒ (Eq. 5) where T j is the observed jth trajectory, N is the number of all trajectories per group, and P is the probability of a given trajectory to obey the parameters.
However, it was also readily evident that the C terminus played a major role in specifying the mobility of the receptor. Accordingly, we searched for candidate mechanisms. We identified a fragment comprising the GUK domain and the adjacent SH3 domain of the postsynaptic protein SAP102 as a possible interaction partner in a yeast two-hybrid interaction screen using the C terminus of the A 2A adenosine receptor as bait. The interaction of this fragment of SAP102 with the C terminus induced the same level of ␤-galactosidase activity as ARNO/cytohesin 2 and USP-4 or (data not shown and Refs. 13, 19). The direct physical interaction between the two protein fragments was confirmed in vitro by pulldown assays. Fusion proteins were engineered to comprise GST and the domains of SAP102 (outlined in Fig.
5  and in subsequent figures were generated with an N-terminally tagged version of SAP102. Direct complex formation may also be visualized by FRET. However, in the N-terminally tagged SAP102, the (predicted) distance between the YFP moiety and the SH3-GUK domain (i. e. the interaction site with the A 2A receptor) is larger than the Fo ¨rster distance of the YFP/CFP pair. Accordingly, YFP was also fused to the C terminus of SAP102. However, this protein was only expressed poorly (data not shown), thus precluding any further analysis. Single Particle Tracking of a SAP102 Binding-deficient Mutant A 2A Receptor in Neurons-Taken together, the data summarized in Figs. 4 5 6 predicted that diffusion of the mutant receptor with the charge reversal in the DVELL motif ( 383 DVELL 387 changed to 383 RVRAA 387 ) should not be affected by SAP102 levels.
Acknowledgments-We thank  Eckart D. Gundelfinger  ( Leibniz-Institut fu ¨r Neurobiologie, Magdeburg, Germany ) for the cDNA encoding SAP102, cloned by  Craig Garner  ( University of Hamburg, Hamburg, Germany ). We also thank  Ivana Ostrouska  for measuring cAMP accumulation and ERK phosphorylation,  Eduard Stefan  for conducting the original yeast two-hybrid screen that identified SAP102 as an interactor, and  Qiong Yang  and  Helmut Drobny  for technical assistance.
On the other hand, one of our objectives is to propose a LISP-based FMC in a complete virtual environment using the trendy concept of Network Function Virtualization (NFV)  [10] ,  [11] ,  [27]. Indeed, NFV aims at running network functions in virtualized environments on VMs on top of virtualized platforms, rather than on dedicated hardware. This is expected to help in rapid deployment of FMC solution, at least within the cloud domain. To achieve this objective, we implemented all LISP protocol elements using ClickOS  [12] , a minimalist and efficient Operating System (OS) dedicated to support NFV, implemented on top of XEN and integrating a software-based router (namely, Click modular routers). The remainder of this paper is structured as follows. Section II describes some research work related to LISP, NFV, and service migration in the cloud.
The latter searches in its local database to find a xTR that would correspond to this EID, and replies with a Map_Reply if it exists. Otherwise, it replies with a Negative_Map_Reply. It is worth noting that the Map Server receives Map_Registers from ETRs and registers EID to RLOC mapping in the mapping database. Thanks to the separation between location and identifier, LISP represents an interesting solution to support station mobility, avoiding the mobile IP drawback (e. g. , triangular routing). Indeed, a station can move from one location to another location without changing its EID. Only RLOC has to be updated at MS/MR. Furthermore, with few modifications, LISP can ensure VM migration with short downtime  [9]. For the above reasons and more, LISP is chosen to extend the FMC concept to support mobile users of non-3GPP networks.
Note that the NFV ETSI group is supported by leading telecom operators and equipment vendors. It has already published different documents to build the basis of the NFV architecture and system. As a technology enabler for NFV, the ClickOS initiative  [12]  has been proposed. It is based on open source tools. It is a minimal OS based on XEN software platform optimized for middlebox processing. Hereby, middlebox refer to all hardware-based network appliances used to run a specific network function (e. g. , firewall, Intrusion Detection System -IDS, and Network Address Translation -NAT. ). ClickOS includes a software modular router, namely Click, that processes packets and acts as a router or a firewall. As one of the challenges of NFV is to enable processing of packets as fast as in dedicated hardware-based solutions, ClickOS leverages the XEN I/O subsystem by changing the back-end switch, virtual network devices, and back/front end-drivers.
The results presented in  [12]  show that ClickOS is able to forward packets at around 30Gbps, proving that NFV could achieve a performance similar to that of dedicated hardwarebased solutions. To take advantage of the flexibility offered by NFV, and to ease the deployment of FMC, particularly in the cloud domain, we envision implementing LISP elements on top of ClickOS. Virtualizing the LISP elements, especially xTR, requires high performance forwarding system, which is now enabled by ClickOS. All LISP protocol elements were implemented by extending the Click software router. The xTR are Click modules that implement the LISP functionality, such as encapsulation and EID-to-RLOC mapping and forwarding. The MR and MS elements are regrouped in one entity, and implemented in a standalone ClickOS VM.
It shall be noted that MR and MS do not require a high packet processing capability. Indeed, they may be implemented on MiniOS by adding a database management system to maintain the EIDto-RLOC mapping of all the LISP architecture. Besides the LISP elements, we also implemented the FMC controller, as described in  [5] , on ClickOS. In this paper, the scenario we envision and want to implement is depicted in Fig. 2  and is described as follows. A mobile user, with a service hosted in DC1 and initially connected to subnet1, moves to subnet2. The xTR router of subnet 2 notifies MR/MS about this movement. MR/MS accordingly updates its cache and informs the FMC controller about the new location of the user. As specified in  [5] ,  [7] , and  [8] , the FMC controller uses some intelligence to decide whether to migrate or not the user's service to a new DC corresponding to the new location of the user.
In fact, if the VM has no packet to transmit, the current xTR router communicating with the VM may continue using old RLOC. An alternative to this approach was proposed in  [9] , whereby LISP is used in the control plane to inform the source and target xTR routers about the success of a VM migration. In this solution, a new message, dubbed, LISP Change Priotity (CP) message, is introduced. The CP message allows: (i) the target hypervisor to inform the target xTR router about the migration of a new VM to the target DC (including the VM's EID) and (ii) to update the cache (RLOC-EID mapping) of other xTR routers. However, this solution requires modifying the hypervisor, making it hard to implement in real-life as the hypervisor software is independent from the operator (as well as the LISP domain).
Certainly, RTT has an impact, but its impact remains relatively small, in comparison to the impact of the link bandwidth, as depicted in Fig. 7. Tab. 1 shows an example of the bandwidth used for migrating the VM from DC1 to DC2. Here, the link bandwidth is also set to 100 Mbps and its RTT is about 10ms. The showed results represent the average, the maximum and minimum used bandwidth for several tests. The objective beneath Tab. 1 is to show the cost of VM migration in terms of the consumed bandwidth. Clearly, we notice that the required bandwidth (around 80 Mbps) does not represent an issue nowadays, as DCs are currently interconnected with high-speed data link. Tab. 1 results indeed demonstrate that the cost of migrating a VM with the considered specifications is not a major technical issue, particularly when using hypervisors such as KVM, which migrates only a part of VMs.
Background Sprints, Hackathons and Codefests are all names for informal software developer meetings, especially popular in Open Source communities. These meetings, which often take place in loose conjunction with more traditional conferences, are a vital part of the international network of interactions between software developers working in bioinformatics and computational biology, and complement purely online interactions such as project mailing lists, online chat, web forums, voice and video calls. Collaborative development of software has figured significantly in bioinformatics for over 20 years. Leveraging and building upon existing Open Source software is a powerful way to rapidly implement new ideas and methods into reliable working code. This helps in a world where scientific groups are under increasing pressure to produce results quickly and more cheaply than ever.
The challenge for everyone is to be aware of existing implementations of a particular desired functionality and their compatibility with local infrastructure. Strategically, it is beneficial to know other contributors to externally maintained libraries, and to ensure that contributions are integrated with the remaining code in the best future-compatible way and with the least possible redundancies. This paper summarises the activities and backgrounds of three related types of meetings: Sprints, Hackathons and Codefests. These share the aim of fostering collaborative interactions and the trust to allow mutual dependencies between developers in computational biology and bioinformatics. Although these meetings share common features, each event has its own particular slant and flavour of the community.
Hackathons Focus on bringing together existing developers of closely related projects, to accelerate development while encouraging inter-project cohesion. A series of BioHackathons (short for "biologically motivated code hacking marathons") have been held. The BioHackathons  [1] [2] [3]  have been organized as an invitational event with the loose intention of encouraging the participants to collaborate on a given theme. This flexibility recognises that with hindsight the most productive results/ideas were not always predictable beforehand, but emerged from self-organized collaborative work during the BioHackathons when developers from different domains spent a week talking and coding together. The original BioHackathons in 2002 and 2003 were mainly dedicated to interoperability in handling sequence data amongst the Bio* projects.
Over 30 developers participated in the BOSC 2013 Codefest, hosted by Humboldt-University in Berlin. Projects accomplished by attendees included the extension of several existing open-source tools, development of standards for provenance tracking, and integration of infrastructure management, visualization and parallelization frameworks  [5]. A key outcome was increased interoperability between tools, an essential requirement for carrying out large scale science in rapidly evolving research areas  [6]. Specific BOSC 2013 Codefest accomplishments included small updates in the Biopython and Cloud Bio-Linux projects, and work on integration of SLURM, an HPC job manager, to the iPython Cluster. Scala is an alternative language to Java that runs in the same JVM environment. During the 2013 Codefest the Scala SCABIO code was integrated into BioJava, with the developers working together to ensure that the result was implemented cleanly and without redundancy.
The BioRuby group tackled a new project which enables programmers to develop Web applications for BaseSpace [http://basespace. illumina. com], a cloud solution provided by Illumina on which users can apply various analysis tools to next generation sequencing (NGS) data. During the 2013 Codefest, a Ruby version of the BaseSpace SDK was tested, documented and completed for release as an Open Source package. Recently, the BaseSpace Ruby SDK was contributed to Illumina as one of the official toolkits along with the Python, Java and R versions with the help of a participant from Illumina. Mobyle  [5]  was modified to provide provenance data using W3C PROV-O  [6]  and integrated with the EDAM ontology  [7]  for describing its services. The Synthetic Biology Open Language Visual Standard  [8]  had been formalized as an ontology, and the 2013 Codefest brought together Semantic Web engineers who were consulted on how to model the visual representation of concepts within the ontology.
Sometimes at Codefests existing technologies are retired in favour of new ones. For the last eight years, RNAmmer has been the standard tool for predicting ribosomal RNA features in genomes. Its drawbacks are that it relies on small, old databases; requires an obsolete version of HMMER; and has restrictive licence terms that prevent anyone beyond the authors from distributing improved code. To resolve these issues for prokaryotes, a new rRNA predictor was implemented which uses the new "nhmmer" tool from HMMER 3. 1 for searching DNA profiles against DNA sequences. This led to the development of Barrnap [http://www. vicbioinformatics. com/software. barrnap. shtml], which will be packaged in Bio-Linux and replace RNAmmer in the Prokka bacterial annotation system  [9]. The identification of the problem, a technical solution and its immediate employment in larger workflows needed several individuals to work together to agree on the approach and begin the required coding-a type of interaction fostered by Codefests and similar events.
Sprints Focus on a single overarching project or technical challenge, providing a meet-up for existing developers as well as a way to involve and mentor new project members. When Linux surfaced as a free operating system, it was adopted quickly by the research community, including many bioinformatics developers. This, along with the ethos of open data in the major international biological databases  [10] , led to a large body of software developed for Linux and released with Free/Open licenses. For example, the Open Source Bio* projects, most prominently BioPerl  [4] , BioJava  [11] , Biopython  [12]  and BioRuby  [13, 14] , originated over 14 years ago as community projects providing widely used libraries for building bioinformatics tools, pipelines and one-off analysis scripts. The situation also led to a natural alliance between bioinformatics software developers and the community-supported Linux distributions they use.
To help promote the redistribution, general availability and mutual compatibility of software, the Debian Linux project launched the Debcamp event, a hacking session right before the Debian Conference. Debcamp is an "unconference", a meeting at which people meet and work on specific topics, either alone or in teams. Along the same lines, the Debian Med initiative was founded in 2001  [15] , with the Debian Sprint held as an annual meeting since 2011. Debian Med  [16]  and Bio-Linux  [17]  provide the necessary infrastructure for distributing software tools and their updates to the wider community. This is achieved by packaging and distributing the tools in the context of these larger tool repositories. The Cloud Bio-Linux community in turn further enhances the distribution, tailored for bioinformatics on cloud infrastructure  [18].
The Sprint helps with the integration of these efforts. The 2013 Debian Sprint invited contributors to BOINC  [19] , a distributed computing project, and we found the binaries of Debian, auto-compiled for multiple different architectures, to be directly usable in BOINC projects across Linux distributions. Together with an ongoing effort to provide packages for the BOINC server side, this will help increase the availability of compute time for biological groups, e. g. , for biochemists with a novel receptor addressing protein docking  [20]. This is a good example of the positive outcomes that can result from the cross-disciplinary collaborative activities at Sprints and similar events. The integration of a single software package can trigger a collection of multiple other software tools to be packaged together to complete common workflows in that field.
For example, porting of the GenomeTools software suite  [21]  during the 2012 Debian Med Sprint not only integrated a substantial number of published and established sequence analysis tools into Debian, but also paved the way for future inclusion of packages dependent on the associated GenomeTools library, e. g. , ParsEval  [22]  or LTRsift  [23]  or the wealth of Predict-Protein  [24]. This emphasizes the role of Sprints as strong promoters of synergistic effects within the community.
Discussion Since Open Source software developers spread across the globe already collaborate by communicating online via distributed source-code repositories, mailing lists, chat and other means, the time and expense of travelling to meet up in person may seem like a waste. However, physical meetings bring an edge to productivity, including temporarily avoiding day-to-day workplace duties, and the opportunity to see software and infrastructure problems from outside of one's local needs. Also, meeting in person temporarily solves the problems of cross-time-zone collaborations. This is particularly important for contributors in Australasia communicating with Europeans or Americans, where live interactions like conference calls must be often scheduled outside normal office hours, and any conversation by email can take days.
The events described here focus on the science and easier access to technology in an intense way that is open to everyone (Figure  1 ). This underscores the Sprints' direct effect on the activity of the projects, both in terms of the number of patches submitted and, on the social side, the number of emails distributed on the mailing list (Figure  2 ). A considerable change observable with the advent of Synthetic Biology is that engineers and computer scientists are building and using tools for tasks that have in the past been performed manually by biologists, e. g. , planning of cloning experiments. We need to learn to address and attract such neighbouring communities to co-develop and share Open Source infrastructure to avoid being crowded out by closed-source solutions. A critical mass of software solutions and users for the synthetic biology field has yet to emerge, and the interplay between Open Source and commercial entities is yet to be established.
The BOSC 2013 Codefest  [27]  helped establish first contact between the Bioinformatics and Synthetic Biology communities, and hopefully will lead to helpful interchange between the fields. Not only academic or research institutions use Open Source tools or frameworks. Open Source tools are widely used in commercial research and commercial service providers who build products and services around Open Source components. Both of these types of companies have an interest in improving the quality of the Open Source software they use. Hackathons and Codefests offer an opportunity for these improvements to be made whilst simultaneously meeting with the original developers, learning from them, and giving them guidance as to future requirements. The BOSC Codefest and the Debian Med Sprint are more constrained as a two-day meeting than the weeklong Hackathon.
Conclusions Participation in a Hackathon, Codefest, or Sprint can be an extremely rewarding experience for the participants and the greater community. These informal, interactive meetings have played an important historical role in the development of Open Source technologies and are now benefiting the bioinformatics community. At these events, developers of all ages and levels of experience interact with each other. Besides the joint problem-solving work, these events can encourage new contributors to surface. Hands-on training and exchange of experiences, actively and passively, remain core features of the events. In closing, we can point to specific examples of software developments and bug fixes made during the developer meetings described, and in some cases publications that have resulted from these meetings.
Acknowledgements All scientific groups that support contributions to  Open Source  software are thanked. The events' hosting institutions are thanked for providing facilities and support. O'Reilly, Electric Genetics, Apple Asia , the  Debian  project, UK  Natural Environment Research Council , the participants' employing institutions and their funding agencies are thanked for contributing to the travel costs of the events. Participants contributing to this paper who were financed by grants received those from the  DFG  ( EXC 306/2 ), the  EU  ( COST "SeqAhead" BM 1006, STREP  " Wf4Ever" FP7-ICT-2007-6 270192 ) and the  Research Council of Norway  ("ELIXIR. NO", 208481). The anonymous reviewers are thanked for their constructive comments. The authors are listed alphabetically by surname, with the exception of the first and last authors who initiated the meetings.
Furthermore, on scales smaller than 30h -1 Mpc, matter density fluctuations become large and linear perturbation theory is not sufficient to compute them. On these scales, in principle, we rely on costly N-body simulations. In an accompanying paper  [3]  we describe a code, CLASSgal, which calculates galaxy number counts, ∆(n, z), as functions of direction n and observed redshift z in linear perturbation theory. In this code all the relativistic effects due to peculiar motion, lensing, integrated Sachs Wolfe effect (ISW) and other effects of metric perturbations as described in  [4, 5]  are fully taken into account. Even if a realistic treatment of the problem of biasing mentioned above is still missing, the number counts have the advantage that they are directly observable as opposed to the power spectrum of fluctuations in real space which depends on cosmological parameters.