COSMO: A conic operator splitting method for large convex problems

This paper describes the Conic Operator Splitting Method (COSMO), an operator splitting algorithm for convex optimisation problems with quadratic objective function and conic constraints. At each step the algorithm alternates between solving a quasi-definite linear system with a constant coefficient matrix and a projection onto convex sets. The solver is able to exploit chordal sparsity in the problem data and to detect infeasible problems. The low per-iteration computational cost makes the method particularly efficient for large problems, e.g. semidefinite programs in portfolio optimisation, graph theory, and robust control. Our Julia implementation is open-source, extensible, integrated into the Julia optimisation ecosystem and performs well on a variety of large convex problem classes

COSMO: A conic operator splitting method for convex conic problems

This paper describes the conic operator splitting method (COSMO) solver, an operator splitting algorithm and associated software package for convex optimisation problems with quadratic objective function and conic constraints. At each step, the algorithm alternates between solving a quasi-definite linear system with a constant coefficient matrix and a projection onto convex sets. The low per-iteration computational cost makes the method particularly efficient for large problems, e.g. semidefinite programs that arise in portfolio optimisation, graph theory, and robust control. Moreover, the solver uses chordal decomposition techniques and a new clique merging algorithm to effectively exploit sparsity in large, structured semidefinite programs. Numerical comparisons with other state-of-the-art solvers for a variety of benchmark problems show the effectiveness of our approach. Our Julia implementation is open source, designed to be extended and customised by the user, and is integrated into the Julia optimisation ecosystem

A clique graph based merging strategy for decomposable SDPs

Chordal decomposition techniques are used to reduce large structured positive semidefinite matrix constraints in semidefinite programs (SDPs). The resulting equivalent problem contains multiple smaller constraints on the nonzero blocks (or cliques) of the original problem matrices. This usually leads to a significant reduction in the overall solve time. A further reduction is possible by remerging cliques with significant overlap. The degree of overlap for which this is effective is dependent on the particular solution algorithm and hardware to be employed. We propose a novel clique merging approach that utilizes the clique graph to identify suitable merge candidates. We show its performance by comparing it with two existing methods on selected problems from a benchmark library. Our approach is implemented in the latest version of the conic ADMM-solver COSMO.Comment: arXiv admin note: substantial text overlap with arXiv:1901.1088

Alien Invasive Slider Turtle in Unpredicted Habitat: A Matter of Niche Shift or of Predictors Studied?

BACKGROUND: Species Distribution Models (SDMs) aim on the characterization of a species' ecological niche and project it into geographic space. The result is a map of the species' potential distribution, which is, for instance, helpful to predict the capability of alien invasive species. With regard to alien invasive species, recently several authors observed a mismatch between potential distributions of native and invasive ranges derived from SDMs and, as an explanation, ecological niche shift during biological invasion has been suggested. We studied the physiologically well known Slider turtle from North America which today is widely distributed over the globe and address the issue of ecological niche shift versus choice of ecological predictors used for model building, i.e., by deriving SDMs using multiple sets of climatic predictor. PRINCIPAL FINDINGS: In one SDM, predictors were used aiming to mirror the physiological limits of the Slider turtle. It was compared to numerous other models based on various sets of ecological predictors or predictors aiming at comprehensiveness. The SDM focusing on the study species' physiological limits depicts the target species' worldwide potential distribution better than any of the other approaches. CONCLUSION: These results suggest that a natural history-driven understanding is crucial in developing statistical models of ecological niches (as SDMs) while "comprehensive" or "standard" sets of ecological predictors may be of limited use

Protocol for a multicentre randomised controlled trial of the Pharmacy Homeless Outreach Engagement Non-medical and Independent Prescriber (PHOENIx) intervention for people facing severe and multiple disadvantages

Introduction: People experiencing severe and multiple disadvantage (SMD: homelessness, substance use and criminal offending) have multiple intersecting unmet health and social care needs and high mortality rates, often due to street-drug overdose. Pilot randomised controlled trials (RCTs) suggest an integrated, holistic, collaborative outreach intervention (Pharmacy Homeless Outreach Engagement Non-medical Independent Prescribing Rx (PHOENIx)) involving generalist-trained pharmacists, nurses or General Practitioners accompanied by staff from third sector homeless organisations may improve outcomes, including reducing overdose. Methods: Multicentre, parallel group, prospective RCT with parallel economic and process evaluation. Set in six areas of Scotland, UK, 378 adults with SMD will be recruited and randomised (stratified by setting and previous non-fatal overdoses) to PHOENIx intervention in addition to usual care (UC) or UC. Aiming to meet participants weekly for 9–15 months, PHOENIx teams assess and address health and social care needs while referring onwards as necessary, co-ordinating care with wider health and third sector teams. During a person-centred consultation, in the participants’ choice of venue, and taking account of the participant’s priorities, the NHS clinician may prescribe, de-prescribe and treat, for example, wound care, and refer to other health services as necessary. The third sector worker may help with welfare benefit applications, social prescribing or advocacy, for example, securing stable housing. Pairings of clinicians and third sector workers support the same participants. The primary outcome is time to first fatal/non-fatal street-drug overdose at nine months. Secondary endpoints include health-related quality of life, healthcare use and criminal justice encounters. A health economic evaluation will assess cost per quality adjusted life year of PHOENIx relative to standard care. A parallel qualitative process evaluation will explore the perceptions and experiences of PHOENIx, by participants, stakeholders and PHOENIx staff. Analysis: The primary and other time-to-event secondary outcomes will be analysed by Cox proportional hazards regression. Ethics and dissemination: IRAS number 345246, approved 23/10/2024 by North of Scotland Research Ethics Service. Results will be shared with participants, third sector homelessness organisations, health and social care partnerships, then peer-reviewed journals and conferences worldwide, from the first quarter of 2027

Allele-Independent Turnover of Human Leukocyte Antigen (HLA) Class Ia Molecules.

Major histocompatibility complex class I (MHCI) glycoproteins present cytosolic peptides to CD8+ T cells and regulate NK cell activity. Their heavy chains (HC) are expressed from up to three MHC gene loci (human leukocyte antigen [HLA]-A, -B, and -C in humans), whose extensive polymorphism maps predominantly to the antigen-binding groove, diversifying the bound peptide repertoire. Codominant expression of MHCI alleles is thus functionally critical, but how it is regulated is not fully understood. Here, we have examined the effect of polymorphism on the turnover rates of MHCI molecules in cell lines with functional MHCI peptide loading pathways and in monocyte-derived dendritic cells (MoDCs). Proteins were labeled biosynthetically with heavy water (2H2O), folded MHCI molecules immunoprecipitated, and tryptic digests analysed by mass spectrometry. MHCI-derived peptides were assigned to specific alleles and isotypes, and turnover rates quantified by 2H incorporation, after correcting for cell growth. MHCI turnover half-lives ranged from undetectable to a few hours, depending on cell type, activation state, donor, and MHCI isotype. However, in all settings, the turnover half-lives of alleles of the same isotype were similar. Thus, MHCI protein turnover rates appear to be allele-independent in normal human cells. We propose that this is an important feature enabling the normal function and codominant expression of MHCI alleles