Fast, Multicore-Scalable, Low-Fragmentation Memory Allocation through Large Virtual Memory and Global Data Structures

We demonstrate that general-purpose memory allocation involving many threads on many cores can be done with high performance, multicore scalability, and low memory consumption. For this purpose, we have designed and implemented scalloc, a concurrent allocator that generally performs and scales in our experiments better than other allocators while using less memory, and is still competitive otherwise. The main ideas behind the design of scalloc are: uniform treatment of small and big objects through so-called virtual spans, efficiently and effectively reclaiming free memory through fast and scalable global data structures, and constant-time (modulo synchronization) allocation and deallocation operations that trade off memory reuse and spatial locality without being subject to false sharing

The Relationship between Personality Organization and Psychiatric Classification in Chronic Pain Patients

The assessment of PO is a crucial issue for diagnosis and treatment planning in CPPs, since it represents a measure of structural impairment that is to a considerable extent independent of axis I and II diagnoses. Moreover, the STIPO dimensional rating focuses on the most salient dysfunctions at a given time. Copyright (C) 2010 S. Karger AG, BaselBackground: The present study investigated the relationship between psychiatric classification and personality organization (PO) in a secondary/tertiary clinical sample of chronic pain patients (CPPs). Sampling and Methods: Forty-three patients were administered the Structured Clinical Interview for DSM-IV (SCID I+II) and the Structured Interview of Personality Organization (STIPO). The prevalence of axis I and axis II disorders was correlated with the STIPO level of PO. The STIPO dimensional ratings of patients without personality disorder (PD) were compared to those of patients diagnosed with one or more PDs. Results: Axis I comorbidity was high (93%), and 63% of the patients met the criteria for at least one axis II diagnosis. Twenty-five patients (58%) were diagnosed as borderline PO, with high-level impairments in the dimensions `coping/rigidity', `primitive defenses' and `identity'. Higher axis I and axis II comorbidity corresponded with greater severity of PO impairment. No difference was found between the dimensional ratings of patients without PD and those of patients with one or more PDs. Conclusions

Strongly walk-regular graphs

We study a generalization of strongly regular graphs. We call a graph strongly walk-regular if there is an $\ell >1$ such that the number of walks of length $\ell$ from a vertex to another vertex depends only on whether the two vertices are the same, adjacent, or not adjacent. We will show that a strongly walk-regular graph must be an empty graph, a complete graph, a strongly regular graph, a disjoint union of complete bipartite graphs of the same size and isolated vertices, or a regular graph with four eigenvalues. Graphs from the first three families in this list are indeed strongly $\ell$-walk-regular for all $\ell$, whereas the graphs from the fourth family are $\ell$-walk-regular for every odd $\ell$. The case of regular graphs with four eigenvalues is the most interesting (and complicated) one. Such graphs cannot be strongly $\ell$-walk-regular for even $\ell$. We will characterize the case that regular four-eigenvalue graphs are strongly $\ell$-walk-regular for every odd $\ell$, in terms of the eigenvalues. There are several examples of infinite families of such graphs. We will show that every other regular four-eigenvalue graph can be strongly $\ell$-walk-regular for at most one $\ell$. There are several examples of infinite families of such graphs that are strongly 3-walk-regular. It however remains open whether there are any graphs that are strongly $\ell$-walk-regular for only one particular $\ell$ different from 3

Lost conversations: finding new ways for black and white Australians to lead together

It\u27s time for a game-changer in how black and white Australians relate.   The difficulties we have in coming together—to talk, to work, to lead change—are core to our challenge to reconcile, as a country. But if we want to shift the status quo, if we want to lead change on entrenched Indigenous disadvantage, we don\u27t need another program, initiative or money to try and \u27fix\u27 the problem. We need to start having a different conversation.  The result of two years experience working together as part of a Social Leadership Australia initiative, Lost Conversations brings together the diverse perspectives and personal stories of five Aboriginal and four non-Indigenous authors, all with first-hand knowledge of what happens when black and white Australians come together to try and work on change.  Lost Conversations asks the questions and starts the conversations that we daren\u27t have in Australia ... until now:  What is \u27black\u27 power? What is \u27white\u27 power?  What qualifies someone to lead in this cross-cultural space?  Why is this so hard to talk about?  Can we start to name these things and try to shift the status quo?  Can we change?  Should we?  &nbsp

Recent Advances and the Potential for Clinical Use of Autofluorescence Detection of Extra-Ophthalmic Tissues

The autofluorescence (AF) characteristics of endogenous fluorophores allow the label-free assessment and visualization of cells and tissues of the human body. While AF imaging (AFI) is well-established in ophthalmology, its clinical applications are steadily expanding to other disciplines. This review summarizes clinical advances of AF techniques published during the past decade. A systematic search of the MEDLINE database and Cochrane Library databases was performed to identify clinical AF studies in extra-ophthalmic tissues. In total, 1097 articles were identified, of which 113 from internal medicine, surgery, oral medicine, and dermatology were reviewed. While comparable technological standards exist in diabetology and cardiology, in all other disciplines, comparability between studies is limited due to the number of differing AF techniques and non-standardized imaging and data analysis. Clear evidence was found for skin AF as a surrogate for blood glucose homeostasis or cardiovascular risk grading. In thyroid surgery, foremost, less experienced surgeons may benefit from the AF-guided intraoperative separation of parathyroid from thyroid tissue. There is a growing interest in AF techniques in clinical disciplines, and promising advances have been made during the past decade. However, further research and development are mandatory to overcome the existing limitations and to maximize the clinical benefits

The influence of bicuspid aortic valves on the dynamic pressure distribution in the ascending aorta: a porcine ex vivo model †

OBJECTIVES The aim of the study was to simulate the effect of different bicuspid aortic valve configurations on the dynamic pressure distribution in the ascending aorta. METHODS Aortic specimens were harvested from adult domestic pigs. In Group 1, bicuspidalization was created by a running suture between the left and the right coronary leaflets (n = 6) and in Group 2 by a running suture between the left and the non-coronary leaflets (n = 6). Eleven tricuspid specimens served as controls. Two intraluminal pressure catheters were positioned at the concavity and the convexity of the ascending aorta. The specimens were connected to a mock circulation (heart rate: 60 bpm, target pressure: 95 mmHg). A comparison of the different conditions was also done in a numerical simulation. RESULTS At a distal mean aortic pressure of 94 ± 10 mmHg, a mean flow rate of 5.2 ± 0.3 l/min was achieved. The difference of maximal dynamic pressure values (which occurred in systole) between locations at the convexity and the concavity was 7.8 ± 2.9 mmHg for the bicuspid and 1.0 ± 0.9 mmHg for the tricuspid specimens (P < 0.001). The numerical simulation revealed an even higher pressure difference between convexity and concavity for bicuspid formation. CONCLUSIONS In this hydrodynamic mock circulation model, we were able to demonstrate that bicuspid aortic valves are associated with significant pressure differences in different locations within the ascending aorta compared with tricuspid aortic valves. These altered pressure distributions and flow patterns may further add to the understanding of aneurismal development in patients with bicuspid aortic valves and might serve to anticipate adverse aortic events due to a better knowledge of the underlying mechanism

Expression Analysis of Fibronectin Type III Domain-Containing (FNDC) Genes in Inflammatory Bowel Disease and Colorectal Cancer

Background. Fibronectin type III domain-containing (FNDC) proteins fulfill manifold functions in tissue development and regulation of cellular metabolism. FNDC4 was described as anti-inflammatory factor, upregulated in inflammatory bowel disease (IBD). FNDC signaling includes direct cell-cell interaction as well as release of bioactive peptides, like shown for FNDC4 or FNDC5. The G-protein-coupled receptor 116 (GPR116) was found as a putative FNDC4 receptor. We here aim to comprehensively analyze the mRNA expression of FNDC1, FNDC3A, FNDC3B, FNDC4, FNDC5, and GPR116 in nonaffected and affected mucosal samples of patients with IBD or colorectal cancer (CRC). Methods. Mucosa samples were obtained from 30 patients undergoing diagnostic colonoscopy or from surgical resection of IBD or CRC. Gene expression was determined by quantitative real-time PCR. In addition, FNDC expression data from publicly available Gene Expression Omnibus (GEO) data sets (GDS4296, GDS4515, and GDS5232) were analyzed. Results. Basal mucosal expression revealed higher expression of FNDC3A and FNDC5 in the ileum compared to colonic segments. FNDC1 and FNDC4 were significantly upregulated in IBD. None of the investigated FNDCs was differentially expressed in CRC, just FNDC3A trended to be upregulated. The GEO data set analysis revealed significantly downregulated FNDC4 and upregulated GPR116 in microsatellite unstable (MSI) CRCs. The expression of FNDCs and GPR116 was independent of age and sex. Conclusions. FNDC1 and FNDC4 may play a relevant role in the pathobiology of IBD, but none of the investigated FNDCs is regulated in CRC. GPR116 may be upregulated in advanced or MSI CRC. Further studies should validate the altered FNDC expression results on protein levels and examine the corresponding functional consequences

Datenbasierte Optimierung unter Unsicherheit für Stromnetzwerke

This cumulative doctoral thesis presents a comprehensive exploration of data-driven optimization under uncertainty in the context of power system analysis. Critical mathematical challenges related to the operation of power grids are addressed, accompanied by innovative solution approaches. The primary focus is on several extensions of the optimal power flow problem which is the predominantly used model in the literature to optimize the power distribution in an electricity network. We study nonconvex mixed-integer nonlinear programs arising in power system analysis, which we solve by the construction and successive refinement of piecewise linear relaxations. Our work introduces various problem-specific and generally applicable algorithmic enhancements to obtain an efficient implementation that outperforms state-of-the-art solvers. Another focus are stochastic mixed-integer linear optimal power flow problems with probabilistic constraints. The solution approach is based on the robust safe approximation of the computationally intractable chance constraints. To construct the approximative problems, suitably defined confidence sets from historical data are computed. We derive a tractable reformulation of the resulting problems and prove quality guarantees about the robustness of the calculated solutions. Numerical experiments on benchmark instances with real weather and network data demonstrate the quality of our solutions. Further improvements are achieved by combining stochastic programming with a model-based prediction of uncertainties. Finally, we present a novel algorithmic framework for optimization under uncertainty over time. The approach uses online learning and scenario observations arriving as a data stream to learn more about the uncertain parameters. We provide a dynamic regret bound for our solutions and illustrate the broad applicability of our approach.Die vorliegende Arbeit widmet sich der datenbasierten Optimierung unter Unsicherheit im Kontext der optimalen Lastflussberechnung in Stromnetzwerken. Wir thematisieren zentrale mathematische Herausforderungen und präsentieren innovative Lösungsansätze. Besonderes Augenmerk liegt auf verschiedene Erweiterungen des klassischen Optimal Power Flow Problems, das als das am häufigsten verwendete Modell zur Stromnetzoptimierung gilt. Wir befassen uns mit nichtkonvexen gemischt-ganzzahligen nichtlinearen Optimierungsproblemen, die in der Steuerung von Stromnetzwerken auftreten. Diese werden durch die Konstruktion und sukzessive Verfeinerung von stückweise linearen Relaxierungen gelöst. Um eine performante Implementierung zu erreichen, präsentieren wir verschiedene, sowohl problemspezifische als auch allgemein anwendbare, algorithmische Erweiterungen. Das resultierende Lösungsverfahren übertrifft existierende Ansätze an Schnelligkeit und Lösungsqualität für die betrachteten Anwendungsprobleme. Wir beschäftigen uns auch mit stochastischen gemischt-ganzzahligen linearen Lastflussoptimierungsproblemen, die probabilistische Nebenbedingungen enthalten. Unser Lösungsansatz basiert auf der robust sicheren Approximation der anspruchsvollen stochastischen Nebenbedingungen. Um die approximativen Modelle aufzustellen werden geeignete Konfidenzmengen mithilfe von historischen Daten berechnet. Wir präsentieren für die resultierenden Probleme eine algorithmisch behandelbare Reformulierung und können Qualitätsaussagen für die berechneten Lösungen treffen. Numerische Experimente an Benchmark-Instanzen unter Verwendung realer Wetter- und Netzwerkdaten verdeutlichen die Performanz unseres Ansatzes. Eine zusätzliche Verbesserung wird durch die innovative Verknüpfung von stochastischer Optimierung mit einer modellbasierten Vorhersage von Unsicherheiten erreicht. Schließlich präsentieren wir einen neuartigen algorithmischen Ansatz für die zeitexpandierte Optimierung unter Unsicherheiten. Unsere Methode nutzt Online-Lernen und die Beobachtung von Szenarien, die als fortlaufender Datenstrom eintreffen, um eine bessere Schätzung von Wahrscheinlichkeitsverteilungen der unsicheren Parameter zu erhalten. Wir beweisen eine dynamische Qualitätsgüte unserer Lösungen und veranschaulichen die vielseitige Anwendbarkeit des Ansatzes

Motzkin monoids and partial Brauer monoids

We study the partial Brauer monoid and its planar submonoid, the Motzkin monoid. We conduct a thorough investigation of the structure of both monoids, providing information on normal forms, Green's relations, regularity, ideals, idempotent generation, minimal (idempotent) generating sets, and so on. We obtain necessary and sufficient conditions under which the ideals of these monoids are idempotent-generated. We find formulae for the rank (smallest size of a generating set) of each ideal, and for the idempotent rank (smallest size of an idempotent generating set) of the idempotent-generated subsemigroup of each ideal; in particular, when an ideal is idempotent-generated, the rank and idempotent rank are equal. Along the way, we obtain a number of results of independent interest, and we demonstrate the utility of the semigroup theoretic approach by applying our results to obtain new proofs of some important representation theoretic results concerning the corresponding diagram algebras, the partial (or rook) Brauer algebra and Motzkin algebra