Partitioning a call graph

Splitting a large software system into smaller and more manageable units has become an important problem for many organizations. The basic structure of a software system is given by a directed graph with vertices representing the programs of the system and arcs representing calls from one program to another. Generating a good partitioning into smaller modules becomes a minimization problem for the number of programs being called by external programs. First, we formulate an equivalent integer linear programming problem with 0–1 variables. theoretically, with this approach the problem can be solved to optimality, but this becomes very costly with increasing size of the software system. Second, we formulate the problem as a hypergraph partitioning problem. This is a heuristic method using a multilevel strategy, but it turns out to be very fast and to deliver solutions that are close to optimal

Adult male patient with severe intellectual disability caused by a homozygous mutation in the HNMT gene

Histamine is involved in various physiological functions like sleep-wake cycle and stress regulation. The histamine N-methyltransferase (HNMT) enzyme is the only pathway for termination of histamine neurotransmission in the central nervous system. Experiments with HNMT knockout mice generated aggressive behaviours and dysregulation of sleep-wake cycles. Recently, seven members of two unrelated consanguineous families have been reported in whom two different missense HNMT mutations were identified. All showed severe intellectual disability, delayed speech development and mild regression from the age of 5 years without, however, any dysmorphisms or congenital abnormality. A diagnosis of mental retardation, autosomal recessive 51 was made. Here, we describe a severely mentally retarded adolescent male born from second cousins with a homozygous mutation in HNMT. His phenotypic profile comprised aggression, delayed speech, autism, sleep disturbances and gastro-intestinal problems. At early age, regression occurred. Treatment with hydroxyzine combined with a histamine-restricted diet resulted in significant general improvement

Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo

Redundancy reduction of IC models : by multirate time-integration and model order reduction

Circuit simulation is an essential step within circuit design. Because of the increasing complexity of the Integrated Circuits, electronic companies need fast and accurate simulation software and there is a constant request at the companies to further improve the simulation software. Development of new, more advanced, transient simulation algorithms is an attractive way to increase the performance of this software. Mathematics is the basis to analyze the convergence properties. The objective of this PhD research is to increase the performance of Pstar, the in-house analog circuit simulator at Philips and now of NXP Semiconductors, while properties like accuracy and robustness are maintained. In particular the convergence and stability properties of newly developed multirate time-integration algorithms is studied. Usually circuit models are large systems of differential-algebraic equations that are derived from Kirchhoff’s conservation laws for currents and voltages and the constitutive relations for the electronic components. For a transient analysis one traditionally uses implicit time-integration schemes, like Backward Difference Formulae (BDF). All these schemes discretise the time on one time-grid. In contrast multirate algorithms use more than one time-grid and compute the slowly time-varying state elements only at coarsely distributed time-points, while the fastly time-varying state elements are computed at finer distributed timepoints. This makes a multirate algorithm potentially much faster for circuits with large low-frequency parts. There are many types of multirate timeintegration methods that may differ in the order of the slow and fast integration and the treatment of the interface variables. We used a direct extension of the BDF scheme combined with Lagrange interpolation of the same order. The standard theory for multistep methods does not hold anymore for multirate algorithms. Therefore we look at properties like stability and convergence in more detail. It turns out that the method is stable if the partitioned subsystems are individually stable and if the coupling is sufficiently weak. The discretisation error for a multirate method also contains an interpolation error due to the slow unknowns at the interface. This error component is not needed for ordinary multistep methods. It is possible to control this error by independent control of the coarse and fine macro and micro time-steps, respectively. The interpolation error and the coarse discretisation error is controlled by the macro stepsize, while the micro stepsize controls the fine discretisation errors for the fast state part. For multirate it is necessary to partitioning the system into a slow and a fast part. Therefore a part of the research is spent to the development and analysis of automatic partitioning algorithms. The underlying problem is a discrete optimisation problem, that can be handled by greedy-like methods. It is also possible to change the partitioning dynamically during the simulation, which is useful for moving active parts. All algorithms are implemented in Matlab; they work satisfactorily when tested for a variety of circuit models. Furthermore a multirate implementation including error control and dynamical partitioning is created in the circuit simulator Pstar itself. Besides multirate time-integration also model order reduction is studied, which transforms the large data models into smaller and simpler models, that still give the proper accuracy, but that are much cheaper to solve. Because IC models are nonlinear, nonlinear reduction techniques are considered in particular, like POD. In particular we focused on the problem to reduce the evaluation costs of these reduced models. A proper use of multirate and model order reduction is able to speed up transient simulation in general and is significantly faster (more than an order) for redundant circuit models, while the accuracy and robustness are maintained. Redundancy occurs if the state elements have many correlations, or if the sampled state signal has correlations in time

Application of least squares MPE technique in the reduced order modeling of electrical circuits

Reduced order models are usually derived by performing the Galerkin projection procedure, where the original equations are projected onto the space spanned by a set of approximating basis functions. For Differential Algebraic Equations this projection scheme may yield an unsolvable reduced order model. This means that a model of an electrical circuit can become ill-posed if it is reduced by the Galerkin technique. As a remedy to the problem, in this paper the reformulation of the reduced order model problem in the least squares sense is suggested. The space where the original is projected is different to the space used in the Galerkin procedure. It is shown that the resulting reduced order model will be guaranteed to be well-posed when the problem of finding a reduced order model is cast into a least squares problem. To accelerate the reduced order modeling computation, the Missing Point Estimation (MPE) technique which was successfully implemented in the PDE-models of heat transfer processes is also applied to the least-squares reduced order model of the electrical circuit. The least-squares based MPE model is derived by projecting a subset of the original equation onto the least-squares space. The dynamics of the stiff DAE model can be approximated very closely by a reduced order model built from less than 28% of the original equations

Increased risk of hematologic malignancies in primary immunodeficiency disorders : opportunities for immunotherapy

Primary immunodeficiency disorders (PIDs) convey increased susceptibility to infections and sometimes to malignancies, particularly lymphomas. Such cancer development can be contributed by immune impairments resulting in weakened immunological surveillance against (pre)malignant cells and oncogenic viruses. Molecular defects in PID-patients are therefore being clarified, identifying new targets for innovative immunotherapy. Particularly pediatric cancers are being scrutinized, where over one third of cancer-related deaths is accounted for by leukemia and lymphomas. Here we review how immunopathogenic mechanisms of several PIDs might associate with lymphoma development. We furthermore delineate existing immunotherapy strategies in adults for potential therapeutic application in childhood leukemia and lymphomas

Increased risk of hematologic malignancies in primary immunodeficiency disorders : opportunities for immunotherapy

Primary immunodeficiency disorders (PIDs) convey increased susceptibility to infections and sometimes to malignancies, particularly lymphomas. Such cancer development can be contributed by immune impairments resulting in weakened immunological surveillance against (pre)malignant cells and oncogenic viruses. Molecular defects in PID-patients are therefore being clarified, identifying new targets for innovative immunotherapy. Particularly pediatric cancers are being scrutinized, where over one third of cancer-related deaths is accounted for by leukemia and lymphomas. Here we review how immunopathogenic mechanisms of several PIDs might associate with lymphoma development. We furthermore delineate existing immunotherapy strategies in adults for potential therapeutic application in childhood leukemia and lymphomas