Bulletin of Mathematical Biology - facts, figures and comparisons

The Society for Mathematical Biology (SMB) owns the Bulletin of Mathematical Biology (BMB). This is an international journal devoted to the interface of mathematics and biology. At the 2003 SMB annual meeting in Dundee the Society asked the editor of the BMB to produce an analysis of impact factor, subject matter of papers, submission rates etc. Other members of the society were interested in the handling times of articles and wanted comparisons with other (appropriate) journals. In this article we present a brief history of the journal and report on how the journal impact factor has grown substantially in the last few years. We also present an analysis of subject areas of published papers over the past two years. We finally present data on times from receipt of paper to acceptance, acceptance to print (and to online publication) and compare these data with some other journals

Principal Component Analysis with Noisy and/or Missing Data

We present a method for performing Principal Component Analysis (PCA) on noisy datasets with missing values. Estimates of the measurement error are used to weight the input data such that compared to classic PCA, the resulting eigenvectors are more sensitive to the true underlying signal variations rather than being pulled by heteroskedastic measurement noise. Missing data is simply the limiting case of weight=0. The underlying algorithm is a noise weighted Expectation Maximization (EM) PCA, which has additional benefits of implementation speed and flexibility for smoothing eigenvectors to reduce the noise contribution. We present applications of this method on simulated data and QSO spectra from the Sloan Digital Sky Survey.Comment: Accepted for publication in PASP; v2 with minor updates, mostly to bibliograph

‘Lots of little jobs’ – building local skills ecosystems for the precarious worker

‘The world needs a wash and a week’s rest,’ wrote W.H. Auden in his 1947 poem, The Age of Anxiety. Almost three-quarters of a century later, that is the reality for many whose fulltime work ideas have fragmented into several little short-term jobs, exacerbated by COVID19. The polarisation between those who enjoy security and prosperity and those who do not has increased (Allas et al 2020). Scholars have raised concerns over the impact on the (particularly marginalised) worker of the expansion of non-standard employment, poverty cycles, and lack of training and development (Egdell and Beck 2020), resulting in dualisation, the division between workers with stable jobs and insecure jobs (Chung 2018). By marginalised, we refer to workers who tend to be at the lower or outer edge of the labour market in uncertain, unpredictable, and risky work, from the worker’s perspective (Kalleberg 2012). We argue that in light of Brexit, increased poverty, and weak skills development, understanding and involvement by employers in their local ecosystem is even more imperative. A skills ecosystem is a community of interacting living parts comprising producers, consumers, and decomposers and non-living components that define the ecosystem’s environment. We share the human resource development (HRD) interventions undertaken jointly by a university and a non-governmental organisation (NGO) between 2016 and 2019 within the City of Liverpool. The context of the research in a skills ecosystem is relevant. We worked with a local NGO based in Toxteth, Liverpool, a highly diverse area characterised by very high levels of multiple deprivation (McCurdy 2020). We found little research in HRD that has challenged the life chances of education and training (Simmons et al 2014) for those in the lower socio-economic groups or, indeed, been involved in offering solutions for those in this growing group of workers. We share our understanding of the lived experience of one of the most disadvantaged groups in the UK, the Roma (Cromarty 2019). Virtually all of the Roma in this study were in irregular, insecure work with high work–labour ratios. This may infer the participants worked in small, less regulated environments; instead, many worked in FTSE 100 UK companies. Participants’ work was generally deemed independent (in contractual terms noted as self-employment) and organised through labour market intermediaries, commonly termed agencies, with evidence of some ‘abusive’ and ‘exploitative’ practice such as poor working conditions, rather than directly with an employer

Mesoscopic Model for Free Energy Landscape Analysis of DNA sequences

A mesoscopic model which allows us to identify and quantify the strength of binding sites in DNA sequences is proposed. The model is based on the Peyrard-Bishop-Dauxois model for the DNA chain coupled to a Brownian particle which explores the sequence interacting more importantly with open base pairs of the DNA chain. We apply the model to promoter sequences of different organisms. The free energy landscape obtained for these promoters shows a complex structure that is strongly connected to their biological behavior. The analysis method used is able to quantify free energy differences of sites within genome sequences.Comment: 7 pages, 5 figures, 1 tabl

Patient Focused internet-based approaches to cardiovascular rehabilitation - a systematic review

Cardiac rehabilitation (CR) has been shown to improve health behaviours and risk factors and the evidence suggests that home CR is as effective as hospital-based CR. Telemedicine offers the potential for more patients to engage in CR. We reviewed the evidence for patient focused Internet-based approaches to cardiovascular rehabilitation. Searches were performed in PubMed, EMBASE, Scopus and the Cochrane Controlled Trials Register (CCTR). In total, 9 studies involving 830patients with heart disease that compared Internet-based cardiac rehabilitation to usual care were identified. The quality of trials was assessed using the Jadad scale. Outcome data were pooled under four subheadings: compliance; physical activity outcomes; clinical outcomes; psychosocial outcomes. Compliance rates were high but dropped over time in all studies. Physical activity measures were generally improved, as were clinical outcomes. Changes in psychosocial measures were positive, with two studies noting no change. No interventions noted a negative effect on outcomes. Despite the relatively small number of trials and the limited outcome measures, the results appeared to be positive with regard to patient outcomes and patient feedback. However, none had progressed to a clinical service

Damage and repair classification in reinforced concrete beams using frequency domain data

This research aims at developing a new vibration-based damage classification technique that can efficiently be applied to a real-time large data. Statistical pattern recognition paradigm is relevant to perform a reliable site-location damage diagnosis system. By adopting such paradigm, the finite element and other inverse models with their intensive computations, corrections and inherent inaccuracies can be avoided. In this research, a two-stage combination between principal component analysis and Karhunen-Loéve transformation (also known as canonical correlation analysis) was proposed as a statistical-based damage classification technique. Vibration measurements from frequency domain were tested as possible damage-sensitive features. The performance of the proposed system was tested and verified on real vibration measurements collected from five laboratory-scale reinforced concrete beams modelled with various ranges of defects. The results of the system helped in distinguishing between normal and damaged patterns in structural vibration data. Most importantly, the system further dissected reasonably each main damage group into subgroups according to their severity of damage. Its efficiency was conclusively proved on data from both frequency response functions and response-only functions. The outcomes of this two-stage system showed a realistic detection and classification and outperform results from the principal component analysis-only. The success of this classification model is substantially tenable because the observed clusters come from well-controlled and known state conditions

Solid-state and solution-phase conformations of pseudoproline-containing dipeptides

The conformations of 14 threonine-derived pseudoproline-containing dipeptides (including four d-allo-Thr derivatives) have been investigated by NMR. In solution, the major conformer observed for all dipeptides is that in which the amide bond between the pseudoproline and the preceding amino acid is cis. For dipeptides in which the N-terminus is protected, the ratio of cis- to trans-conformers does not depend significantly on the side chain of the N-terminal amino acid, or the stereochemistry of the Thr residue. However, for dipeptides bearing a free N-terminus, there are significant differences in the ratios of cis- to trans-conformers depending on the side chain present. Three dipeptides were crystallized and their X-ray structures determined. In two cases, (benzyloxycarbonyl (Cbz)-Val-Thr(ΨMe,Mepro)-OMe and Cbz-Val-Thr(ΨMe,Mepro)-OH), the dipeptides adopt a trans-conformation in the solid state, in contrast to the structures observed in solution. In the third case, (9-fluorenylmethoxycarbonyl (Fmoc)-Val-d-allo-Thr(ΨMe,Mepro)-OH), a cis-amide geometry is observed. These structural differences are attributed to crystal-packing interactions

Mono- and dinucleating Ni(II), Cu(II), Zn(II) and Fe(III) complexes of symmetric and unsymmetric Schiff bases incorporating salicylimine functions - Synthetic and structural studies

The known Schiff base, 3-(2-aminophenylamino)-1-phenylbut-2-en-1-one (1), formed by 1:1 condensation of o-phenylenediamine and benzoylacetylacetone reacts at its free amine site with salicylaldehyde and 5-tert-butylsalicylaldehyde in the presence of Ni(II) and Cu(II) acetates, or with 5-tert-butylsalicylaldehyde in the presence of Zn(II) acetate, to generate 1:1 (M:L) diimine complexes (2) of the corresponding doubly deprotonated, unsymmetric, O2N 2-tetradentate ligands. In contrast, reaction of Zn(II) acetate with 1 and salicylaldehyde led to Schiff base exchange (with loss of benzoylacetylacetone) to yield symmetric [ZnL3] [where L3 is N,N′-o-phenylenebis(salicyliminato)]. Similarly, when Fe(II) chloride was substituted for metal acetate in the reaction of 1 with 5-tert-butyl- salicylaldehyde and the initial product crystallised in the presence of dabco (as base), a related Schiff base exchange reaction occurred along with aerial oxidation of the Fe(II) to produce the neutral dinuclear [Fe III(L4)2(μ-O)] species [where L4 is N,N′-o-phenylenebis(5-tert-butylsalicyliminato)] in which Fe(III) centres are linked by an oxo group to produce two 5-coordinate Fe(III) centres; pairs of these (oxo-bridged) dinuclear complex units are further linked via elongated intermolecular Fe-Ophenolic contacts (Fe-O, 2.44 Å) to form an unusual tetranuclear supramolecular cluster. This complex was also synthesised directly by the in situ reaction of 5-tert-butyl-salicylaldehyde, o-phenylenediamine and Fe(II) chloride (2:1:1 mol ratio) in air. In an extension of these studies, the in situ reaction of the 1,3-aryl linked bis-β-diketone, 1,1-(1,3-phenylene)-bis-butane-1,3-dione), o-phenylenediamine, salicylaldehyde and Ni(II) acetate in a 1:2:2:2 ratio yielded [Ni2L5], the dinuclear analogue of the unsymmetric mononuclear Ni(II) complex 2, in which each nickel centre has a square planar environment. Reaction of the above 1,3-phenylene linked bis-β-diketone precursor with o-phenylenediamine in a 1:2 M ratio yields 1,3-bis(4-methyl-3H- benzo[b][1,4]diazepin-2-yl)benzene as its monohydrate (3·H2O) incorporating two 7-membered diaza heterocyclic rings; thus contrasting with the 'open' Schiff base structure observed for 1. X-ray structures of 1, 3·H2O, [NiL1]·py, [NiL1] ·EtOH, [NiL2], [CuL1]·py, [CuL 1]·0.5CHCl3, [(FeL4)2(μ-O) ]2·1.5THF·0.4EtOH·0.6H2O and [NiL5]·0.25EtOH·0.125py are reported

Sparse Exploratory Factor Analysis

Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could greatly benefit from sparse solutions. Unfortunately, there are very few works considering sparse versions of the classic factor analysis. Our goal is to contribute further in this direction. We revisit the most popular procedures for exploratory factor analysis, maximum likelihood and least squares. Sparse factor loadings are obtained for them by, first, adopting a special reparameterization and, second, by introducing additional [Formula: see text]-norm penalties into the standard factor analysis problems. As a result, we propose sparse versions of the major factor analysis procedures. We illustrate the developed algorithms on well-known psychometric problems. Our sparse solutions are critically compared to ones obtained by other existing methods

Sparsest factor analysis for clustering variables: a matrix decomposition approach

We propose a new procedure for sparse factor analysis (FA) such that each variable loads only one common factor. Thus, the loading matrix has a single nonzero element in each row and zeros elsewhere. Such a loading matrix is the sparsest possible for certain number of variables and common factors. For this reason, the proposed method is named sparsest FA (SSFA). It may also be called FA-based variable clustering, since the variables loading the same common factor can be classified into a cluster. In SSFA, all model parts of FA (common factors, their correlations, loadings, unique factors, and unique variances) are treated as fixed unknown parameter matrices and their least squares function is minimized through specific data matrix decomposition. A useful feature of the algorithm is that the matrix of common factor scores is re-parameterized using QR decomposition in order to efficiently estimate factor correlations. A simulation study shows that the proposed procedure can exactly identify the true sparsest models. Real data examples demonstrate the usefulness of the variable clustering performed by SSFA