A Project Based Approach to Statistics and Data Science

In an increasingly data-driven world, facility with statistics is more important than ever for our students. At institutions without a statistician, it often falls to the mathematics faculty to teach statistics courses. This paper presents a model that a mathematician asked to teach statistics can follow. This model entails connecting with faculty from numerous departments on campus to develop a list of topics, building a repository of real-world datasets from these faculty, and creating projects where students interface with these datasets to write lab reports aimed at consumers of statistics in other disciplines. The end result is students who are well prepared for interdisciplinary research, who are accustomed to coping with the idiosyncrasies of real data, and who have sharpened their technical writing and speaking skills

Experimentally Constrained Molecular Relaxation: The Case of Glassy GeSe2

An ideal atomistic model of a disordered material should contradict no experiments,and should also be consistent with accurate force fields (either {\it ab initio}or empirical). We make significant progress toward jointly satisfying {\it both} of these criteria using a hybrid reverse Monte Carlo approach in conjunction with approximate first principles molecular dynamics. We illustrate the method by studying the complex binary glassy material g-GeSe$_2$. By constraining the model to agree with partial structure factors and {\it ab initio} simulation, we obtain a 647-atom model in close agreement with experiment, including the first sharp diffraction peak in the static structure factor. We compute the electronic state densities and compare to photoelectron spectroscopies. The approach is general and flexible.Comment: 6 pages, 4 figure

The EPICS Software Framework Moves from Controls to Physics

The Experimental Physics and Industrial Control System (EPICS), is an open-source software framework for high-performance distributed control, and is at the heart of many of the world’s large accelerators and telescopes. Recently, EPICS has undergone a major revision, with the aim of better computing supporting for the next generation of machines and analytical tools. Many new data types, such as matrices, tables, images, and statistical descriptions, plus users’ own data types, now supplement the simple scalar and waveform types of the former EPICS. New computational architectures for scientific computing have been added for high-performance data processing services and pipelining. Python and Java bindings have enabled powerful new user interfaces. The result has been that controls are now being integrated with modelling and simulation, machine learning, enterprise databases, and experiment DAQs. We introduce this new EPICS (version 7) from the perspective of accelerator physics and review early adoption cases in accelerators around the world

5 year follow up of a hydroxyapatite coated short stem femoral component for hip arthroplasty: a prospective multicentre study

Short stem, uncemented femoral implants for hip arthroplasty are bone conserving achieving stability through initial metaphyseal press-fit and biological fixation. This study aimed to evaluate the survivorship, mid-term function and health related quality of life outcomes in patients who have undergone total hip arthroplasty (THA) with a fully hydroxyapatite coated straight short stem femoral component with up to 5 years follow-up. 668 patients were recruited to a multicentre study investigating the performance of the cementless Furlong Evolution® stem for THA. 137 patients withdrew at various time points. The mean follow-up was 49 months. Clinical (Harris Hip Score (HHS), radiographic and patient-reported outcome measures—Oxford Hip Score (OHS) and EuroQol 5D (EQ-5D), were recorded pre-operatively and at 6 weeks, 6 months, 1 year, 3 year and 5 year follow ups. At 5-year follow-up, 12 patients underwent revision surgery, representing a cumulative revision rate of 1.8%. Median OHS, HHS and EQ5D scores improved significantly: OHS improved from a pre-operative median of 21 (IQR 14–26) to 47 (IQR 44–48) (p < 0.001). HHS improved from 52 (IQR 40–63) to 98 (IQR 92–100) (p < 0.001) and EQ5D improved from 70 (IQR 50–80) to 85 (IQR 75–95) (p < 0.001). This fully HA-coated straight short femoral stem implant demonstrated acceptable mid-term survivorship and delivered substantial improvements in function and quality of life after THA

Self-conscious emotions in patients suffering from chronic musculoskeletal pain: a brief report.

OBJECTIVE: The role of self-conscious emotions (SCEs) including shame, guilt, humiliation and embarrassment are of increasing interest within health. Yet, little is known about SCEs in the experience of chronic pain. This study explored prevalence and experience of SCEs in chronic pain patients compared to controls and assessed the relationship between SCEs and disability in pain patients. DESIGN AND MEASURES: Questionnaire assessment comparing musculoskeletal pain patients (n=64) and pain-free control participants (n=63). Pain was assessed using the McGill Pain Questionnaire; disability, using the Roland-Morris Disability Questionnaire; and six SCEs derived from three measures (i) Test of Self-Conscious Affect-3 yielding subscales of shame, guilt, externalisation and detachment (ii) The Brief Fear of Negative Evaluation Scale and (iii) The Pain Self-Perception Scale assessing mental defeat. RESULTS: Significantly greater levels of shame, guilt, fear of negative evaluation and mental defeat were observed in chronic pain patients compared to controls. In the pain group, SCE variables significantly predicted affective pain intensity; only mental defeat was significantly related to disability. CONCLUSION: Findings highlight the prevalence of negative SCEs and their importance in assessment and management of chronic pain. The role of mood in this relationship is yet to be explored

Genetic algorithms with self-organizing behaviour in dynamic environments

Copyright @ 2007 Springer-VerlagIn recent years, researchers from the genetic algorithm (GA) community have developed several approaches to enhance the performance of traditional GAs for dynamic optimization problems (DOPs). Among these approaches, one technique is to maintain the diversity of the population by inserting random immigrants into the population. This chapter investigates a self-organizing random immigrants scheme for GAs to address DOPs, where the worst individual and its next neighbours are replaced by random immigrants. In order to protect the newly introduced immigrants from being replaced by fitter individuals, they are placed in a subpopulation. In this way, individuals start to interact between themselves and, when the fitness of the individuals are close, one single replacement of an individual can affect a large number of individuals of the population in a chain reaction. The individuals in a subpopulation are not allowed to be replaced by individuals of the main population during the current chain reaction. The number of individuals in the subpopulation is given by the number of individuals created in the current chain reaction. It is important to observe that this simple approach can take the system to a self-organization behaviour, which can be useful for GAs in dynamic environments.Financial support was obtained from FAPESP (Proc. 04/04289-6)

Theodicy and End-of-Life Care

Acknowledgments The section on Islamic perspective is contributed by information provided by Imranali Panjwani, Tutor in Theology & Religious Studies, King's College London.Peer reviewedPublisher PD

Boolean delay equations on networks: An application to economic damage propagation

We introduce economic models based on Boolean Delay Equations: this formalism makes easier to take into account the complexity of the interactions between firms and is particularly appropriate for studying the propagation of an initial damage due to a catastrophe. Here we concentrate on simple cases, which allow to understand the effects of multiple concurrent production paths as well as the presence of stochasticity in the path time lengths or in the network structure. In absence of flexibility, the shortening of production of a single firm in an isolated network with multiple connections usually ends up by attaining a finite fraction of the firms or the whole economy, whereas the interactions with the outside allow a partial recovering of the activity, giving rise to periodic solutions with waves of damage which propagate across the structure. The damage propagation speed is strongly dependent upon the topology. The existence of multiple concurrent production paths does not necessarily imply a slowing down of the propagation, which can be as fast as the shortest path.Comment: Latex, 52 pages with 22 eps figure

How to prioritize patients and redesign care to safely resume planned surgery during the COVID-19 pandemic.

AIMS: Restarting planned surgery during the COVID-19 pandemic is a clinical and societal priority, but it is unknown whether it can be done safely and include high-risk or complex cases. We developed a Surgical Prioritization and Allocation Guide (SPAG). Here, we validate its effectiveness and safety in COVID-free sites. METHODS: A multidisciplinary surgical prioritization committee developed the SPAG, incorporating procedural urgency, shared decision-making, patient safety, and biopsychosocial factors; and applied it to 1,142 adult patients awaiting orthopaedic surgery. Patients were stratified into four priority groups and underwent surgery at three COVID-free sites, including one with access to a high dependency unit (HDU) or intensive care unit (ICU) and specialist resources. Safety was assessed by the number of patients requiring inpatient postoperative HDU/ICU admission, contracting COVID-19 within 14 days postoperatively, and mortality within 30 days postoperatively. RESULTS: A total of 1,142 patients were included, 47 declined surgery, and 110 were deemed high-risk or requiring specialist resources. In the ten-week study period, 28 high-risk patients underwent surgery, during which 68% (13/19) of Priority 2 (P2, surgery within one month) patients underwent surgery, and 15% (3/20) of P3 ( three months) groups. Of the 1,032 low-risk patients, 322 patients underwent surgery. Overall, 21 P3 and P4 patients were expedited to 'Urgent' based on biopsychosocial factors identified by the SPAG. During the study period, 91% (19/21) of the Urgent group, 52% (49/95) of P2, 36% (70/196) of P3, and 26% (184/720) of P4 underwent surgery. No patients died or were admitted to HDU/ICU, or contracted COVID-19. CONCLUSION: Our widely generalizable model enabled the restart of planned surgery during the COVID-19 pandemic, without compromising patient safety or excluding high-risk or complex cases. Patients classified as Urgent or P2 were most likely to undergo surgery, including those deemed high-risk. This model, which includes assessment of biopsychosocial factors alongside disease severity, can assist in equitably prioritizing the substantial list of patients now awaiting planned orthopaedic surgery worldwide. Cite this article: Bone Jt Open 2021;2(2):134-140