The journal impact factor: angel, devil, or scapegoat? A comment on J.K. Vanclay’s article 2011

J.K. Vanclay’s article is a bold attempt to review recent works on the journal impact factor (JIF) and to call for alternative certifications of journals. The too broad scope did not allow the author to fulfill all his purposes. Attempting after many others to organize the various forms of criticism, with targets often broader than the JIF, we shall try to comment on a few points. This will hopefully enable us to infer in which cases the JIF is an angel, a devil, or a scapegoat. We shall also expand on a crucial question that Vanclay could not really develop in the reduced article format: the field-normalization. After a short recall on classical cited-side or ex post normalization and of the powerful influence measures, we will devote some attention to the novel way of citing-side or ex ante normalization, not only for its own interest, but because it directly proceeds from the disassembling of the JIF clockwork.     

Repetitive model refactoring strategy for the design space exploration of intensive signal processing applications

The efficient design of computation intensive multidimensional signal processing applications requires dealing with three kinds of constraints: those implied by the data dependencies, the non-functional requirements (real-time, power consumption) and resources availability of the execution platform. Modeling and Analysis of Real-time and Embedded systems (MARTE) UML profile through its repetitive structure modeling (RSM) package is well suited to model the inherent parallelism within these applications, a compact representation of parallel execution platforms and the distributive mapping of one on another. The execution of such a specification respects the whole set of constraints defined upon, while the quality of the scheduling is directly linked to the quality of the mapping of the multidimensional structures (data arrays or parallel loop nests) into time and space. We propose here a strategy to use a refactoring tool dedicated to this kind of application that allows to find good trade-offs in the usage of storage and computation resources and in parallelism (both task and data parallelism) exploitation. This strategy is illustrated on an industrial radar application.     

Concept drift and how to identify it

This paper studies concept drift over time. We first define the meaning of a concept in terms of intension, extension and label. Then we study concept drift over time using two theories: one based on concept identity and one based on concept morphing. A qualitative toolkit for analysing concept drift is proposed to detect concept shift and stability when concept identity is available, and concept split and strength of morphing chain if using the morphing theory. We apply our framework in four case-studies: a political vocabulary in SKOS, the DBpedia ontology in RDFS, the LKIF-Core ontology in OWL and a few biomedical ontologies in OBO. We describe ways of identifying interesting changes in the meaning of concept within given application contexts. These case-studies illustrate the feasibility of our framework in analysing concept drift in knowledge organisation schemas of varying expressiveness.     

Parameter-insensitive kernel in extreme learning for non-linear support vector regression

Support vector regression (SVR) is a state-of-the-art method for regression which uses the ε‐sensitive loss and produces sparse models. However, non-linear SVRs are difficult to tune because of the additional kernel parameter. In this paper, a new parameter-insensitive kernel inspired from extreme learning is used for non-linear SVR. Hence, the practitioner has only two meta-parameters to optimise. The proposed approach reduces significantly the computational complexity yet experiments show that it yields performances that are very close from the state-of-the-art. Unlike previous works which rely on Monte-Carlo approximation to estimate the kernel, this work also shows that the proposed kernel has an analytic form which is computationally easier to evaluate.     

Software transactional memories: an approach for multicore programming

The recent advance of multicore architectures and the deployment of multiprocessors as the mainstream computing platforms have given rise to a new concurrent programming impetus. Software transactional memories (STM) are one of the most promising approaches to take up this challenge. The aim of a STM system is to discharge the application programmer from the management of synchronization when he/she has to write multiprocess programs. His/her task is to decompose his/her program into a set of sequential tasks that access shared objects, and to decompose each task in atomic units of computation. The management of the required synchronization is ensured by the associated STM system. This paper presents two existing STM systems, and a new one based on time-window mechanism. The paper, which focuses mainly on STM principles, has an introductory and survey flavor.     

Discovery of Heterocyclic Nonacetamide Synaptic Vesicle Protein 2A (SV2A) Ligands with Single‐Digit Nanomolar Potency: Opening Avenues towards the First SV2A Positron Emission Tomography (PET) Ligands

The role of the synaptic vesicle protein 2A (SV2A) protein, target of the antiepileptic drug levetiracetam, is still mostly unknown. Considering its potential to provide in vivo functional insights into the role of SV2A in epileptic patients, the development of an SV2A positron emission tomography (PET) tracer has been undertaken. Using a 3D pharmacophore model based on close analogues of levetiracetam, we report the rationale design of three heterocyclic non‐acetamide lead compounds, UCB‐A, UCB‐H and UCB‐J, the first single‐digit nanomolar SV2A ligands with suitable properties for development as PET tracers.     

Novel Heterobimetallic Radiotheranostic: Preparation,Activity, and Biodistribution

A novel Ru^II(arene) theranostic complex is presented. It is based on a 1,4,7,10‐tetraazacyclododecane‐1,4,7,10‐tetraacetic acid macrocycle bearing a triarylphosphine and can be tracked in vivo by using the γ emission of ¹⁵³Sm atoms. Notably, the heteroditopic ligand can be selectively metalated with ruthenium at the phosphorus atom despite the presence of other functionalities that are prone to metal coordination. Subsequent labeling with radionuclides such as ¹⁵³Sm can then be performed easily. The resulting heterobimetallic complex exhibits favorable solubility and stability properties in biologically relevant media. It also shows in vitro cytotoxicity in line with that expected for this type of metallodrug, and is nontoxic to the organism as a whole. As a proof of concept, initial studies in healthy mice were performed to obtain information about the uptake, biodistribution, and excretion of the radiolabeled complex.