bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel artificial intelligence based intensive care unit monitoring system: using physiological waveforms to identify sepsis
Authors: Mollura Maximiliano , Lehman Li-Wei H. , Mark Roger G. , Barbieri Riccardo 
Published: October 2021

A massive amount of multimodal data are continuously collected in the intensive care unit (ICU) along each patient stay, offering a great opportunity for the development of smart monitoring devices based on artificial intelligence (AI). The two main sources of relevant information collected in the ICU are the electronic health records (EHRs) and vital sign waveforms continuously recorded at the bedside. While EHRs are already widely processed by AI algorithms for prompt diagnosis and prognosis, AI-based assessments of the patients’ pathophysiological state using waveforms are less developed, and their use is still limited to real-time monitoring for basic visual vital sign feedback at the bedside. This study uses data from the MIMIC-III database (PhysioNet) to propose a novel AI approach in ICU patient monitoring that incorporates features estimated by a closed-loop cardiovascular model, with the specific goal of identifying sepsis within the first hour of admission. Our top benchmark results (AUROC = 0.92, AUPRC = 0.90) suggest that features derived by cardiovascular control models may play a key role in identifying sepsis, by continuous monitoring performed through advanced multivariate modelling of vital sign waveforms. This work lays foundations for a deeper data integration paradigm which will help clinicians in their decision-making processes.This article is part of the theme issue ‘Advanced computation in cardiovascular physiology: new challenges and opportunities’.
Robustness of convolutional neural networks to physiological electrocardiogram noise
Authors: Venton J. , Harris P. M. , Sundar A. , Smith N. A. S. , Aston P. J. 
Published: October 2021

The electrocardiogram (ECG) is a widespread diagnostic tool in healthcare and supports the diagnosis of cardiovascular disorders. Deep learning methods are a successful and popular technique to detect indications of disorders from an ECG signal. However, there are open questions around the robustness of these methods to various factors, including physiological ECG noise. In this study, we generate clean and noisy versions of an ECG dataset before applying symmetric projection attractor reconstruction (SPAR) and scalogram image transformations. A convolutional neural network is used to classify these image transforms. For the clean ECG dataset, F1 scores for SPAR attractor and scalogram transforms were 0.70 and 0.79, respectively. Scores decreased by less than 0.05 for the noisy ECG datasets. Notably, when the network trained on clean data was used to classify the noisy datasets, performance decreases of up to 0.18 in F1 scores were seen. However, when the network trained on the noisy data was used to classify the clean dataset, the decrease was less than 0.05. We conclude that physiological ECG noise impacts classification using deep learning methods and careful consideration should be given to the inclusion of noisy ECG signals in the training data when developing supervised networks for ECG classification.
This article is part of the theme issue ‘Advanced computation in cardiovascular physiology: new challenges and opportunities’.
A novel multi-branch architecture for state of the art robust detection of pathological phonocardiograms
Authors: Duggento Andrea , Conti Allegra , Guerrisi Maria , Toschi Nicola 
Published: October 2021

Heart auscultation is an inexpensive and fundamental technique to effectively diagnose cardiovascular disease. However, due to relatively high human error rates even when auscultation is performed by an experienced physician, and due to the not universal availability of qualified personnel, e.g. in developing countries, many efforts are made worldwide to propose computational tools for detecting abnormalities in heart sounds. The large heterogeneity of achievable data quality and devices, the variety of possible heart pathologies, and a generally poor signal-to-noise ratio make this problem very challenging. We present an accurate classification strategy for diagnosing heart sounds based on (1) automatic heart phase segmentation, (2) state-of-the art filters drawn from the field of speech synthesis (mel-frequency cepstral representation) and (3) an ad hoc multi-branch, multi-instance artificial neural network based on convolutional layers and fully connected neuronal ensembles which separately learns from each heart phase hence implicitly leveraging their different physiological significance. We demonstrate that it is possible to train our architecture to reach very high performances, e.g. an area under the curve of 0.87 or a sensitivity of 0.97. Our machine-learning-based tool could be employed for heartsound classification, especially as a screening tool in a variety of situations including telemedicine applications.This article is part of the theme issue ‘Advanced computation in cardiovascular physiology: new challenges and opportunities’.
Advanced computation in cardiovascular physiology: new challenges and opportunities
Authors: Valenza Gaetano , Faes Luca , Toschi Nicola , Barbieri Riccardo 
Published: October 2021

Recent developments in computational physiology have successfully exploited advanced signal processing and artificial intelligence tools for predicting or uncovering characteristic features of physiological and pathological states in humans. While these advanced tools have demonstrated excellent diagnostic capabilities, the high complexity of these computational 'black boxes’ may severely limit scientific inference, especially in terms of biological insight about both physiology and pathological aberrations. This theme issue highlights current challenges and opportunities of advanced computational tools for processing dynamical data reflecting autonomic nervous system dynamics, with a specific focus on cardiovascular control physiology and pathology. This includes the development and adaptation of complex signal processing methods, multivariate cardiovascular models, multiscale and nonlinear models for central-peripheral dynamics, as well as deep and transfer learning algorithms applied to large datasets. The width of this perspective highlights the issues of specificity in heartbeat-related features and supports the need for an imminent transition from the black-box paradigm to explainable and personalized clinical models in cardiovascular research.
This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.
Development of Permanent Artificial Bowel Replacement Substrates
Authors: Koysombat Kantida , Haneef Atikah 
Published: October 2021

AbstractShort bowel syndrome (SDS) is a malabsorption disorder caused by loss of function of the small intestine, either by trauma or innately. Current treatment options include parenteral nutrition (PN) or allograft transplants. Long term PN dependence can lead to complications due to line infections and toxicity from the formula itself. A lack of healthy donors results in long waiting lists and high mortality rates. With allograft transplants, long-term graft and patient survival rates are poor (48% and 39% respectively at 5 years); graft loss occurs due to rejection (48%), thrombosis (28%), sepsis (12%); main causes of death are due to bacterial infection (94%) and rejection. Costs associated with PN annually per patient approximate to £40,000, whereas one allograft procedure costs approximately £80,000; not including intervention due to complications.Interest in developing an off-the-shelf bioengineered alternative have been expressed. Autologous transplants could be a more beneficial route to improving survival rates, enabling the transplant of patients’ healthy cells back to them. We describe here the development of a synthetic poly(ethylene terephthalate) scaffold using electrospinning, which showed excellent physical and chemical characteristics; high surface area:volume ratio, high mechanical strength, high porosity, and the ability to be chemically/physically functionalised without losing integrity in structure and physical properties. The cost of electrospinning is far lower in comparison to the current available treatment options, potentially providing a stable, off-the-shelf, ready-to-culture product as the need arises for applications in tissue engineered small intestine (TESI), or 3D models for small bowel research.
Financial literacy, financial distress and socioeconomic characteristics of individuals in Ghana
Authors: Karakara Alhassan Abdul-Wakeel , Sebu Joshua , Dasmani Isaac 
Published: October 2021

PurposePersonal financial stress-free living is desired by many, which dwells on sound financial literacy (including financial behaviour, financial knowledge and financial attitude). Many individuals do not make optimal savings and investment decisions. The realisation that these choices may well lead to low living standards has also increased economic anxiety, especially in Sub-Sahara African countries, including Ghana. Thus, this study underscores the link between financial literacy and financial distress in Ghana. It establishes whether persons that are financially literate escape financial distress in their life.Design/methodology/approachThe paper engages nationally representative survey data and adopts a positivist research approach with logistic regression analysis to establish the likelihood of financial literate persons experiencing financial distress.FindingsThis study establishes that financially literate individuals are 2.4% less likely to experience financial distress. Socioeconomic characteristics greatly influence the probability of one experiencing financial hardship. It submits that policy can be directed towards improving financial habits (financial literacy) to enhance individuals' financial behaviour to lessen personal financial distress.Originality/valueNot much attention has been paid to whether financial literacy has a nexus with financial distress. Few studies (not on Sub-Saharan Africa) that have looked at this are done, neglecting a sensitivity analysis of socioeconomic characteristics in establishing the relations. However, this current study dwells on econometric analysis to establish the margin or extend to which a financially literate person may or may not escape financial distress given his/her socioeconomic characteristics.
Hospital salutogenic public spaces: a conceptual framework of effective perceptional environment quality components on patients' satisfaction
Authors: Ghaffari Faezeh , Shabak Maryam , Norouzi Nima , Nayyeri Fallah Siyamak 
Published: October 2021

PurposeThis study aimed at the identification of perceptional environment properties in hospital public spaces that can affect salutogenic components and patients' overall satisfaction and suggested a conceptual framework.Design/methodology/approachA systematic review focused on specific steps to clarify the impact of public spaces' environmental quality on patients' satisfaction through the salutogenic approach. Searches were conducted in five databases and four scientific journals.FindingsFive perceptional environment components of hospital public spaces: physical–psychological comfort, visibility, accessibility, legibility and relationability can be related to three indicators of salutogenic approach: manageability, perception and meaning and can be evaluated in patients' overall satisfaction: desire to use hospital again, to recommend the hospital to others, to prefer hospital to other healthcare environments and to trust in the hospital.Originality/valueDespite studies on healthcare environments, there is a lack of research on the salutogenic approach in hospital public spaces. Therefore, this paper focuses on the environmental quality in public spaces as an influence on patients' satisfaction with the salutogenic perspective to create a health-promoting environment.
Measuring the up-to-date quality of online food delivery: formative index construction
Authors: Chan Janelle , Gao Yixing Lisa 
Published: October 2021

Purpose
This study aims to fill this paucity of knowledge by exploring and formulating a formative index to measure the up-to-date quality of online food delivery (DEQUAL). The quality measurements for online food delivery have not been well recognized and even little is known after the COVID-19 outbreak. This study fills this paucity of knowledge by exploring and formulating a formative index to measure the up-to-date quality of online food delivery (DEQUAL).

Design/methodology/approach
Owing to the explorative nature and the lack of developed quality theory under the unprecedented COVID-19 pandemic, DEQUAL is conceptualized as a formative construct. This study adopts a mixed-method approach including expert interviews and online surveys to ascertain the underlying structure of DEQUAL.

Findings
Using partial least squares structural equation modeling as the analytical method, the results support that DEQUAL is a formative construct with 32 indicators. This study provides a measurement index with robust psychometric properties to assist practitioners in evaluating DEQUAL.

Research limitations/implications
This study contributes a theoretical and empirical-based conceptualization of DEQUAL as a multi-dimensional construct. Supplementing the past studies which commonly applied the reflective approach, this study evinces that the formative approach is also appropriate and thence furnishes the relevance of the formative index in the service management theories.

Practical implications
Practitioners are suggested to apply the validated indicators for service audit and customer relationship management. By systematically monitoring and measuring the online food delivery service quality, restaurants can improve customer satisfaction and loyalty.

Originality/value
This study offers various insights to the service quality literature in the food delivery service context.
Patient engagement in system redesign teams: a process of social identity
Authors: Atkinson Mariam Krikorian , Benneyan James C. , Phillips Russell S. , Schiff Gordon D. , Hunt Lindsay S. , Singer Sara J. 
Published: October 2021

PurposeStudies demonstrate how patient roles in system redesign teams reflect a continuum of involvement and influence. This research shows the process by which patients move through this continuum and effectively engage within redesign projects.Design/methodology/approachThe authors studied members of redesign teams, consisting of 5–10 members: clinicians, systems engineers, health system staff and patient(s), from three health systems working on separate projects in a patient safety learning lab. Weekly team meetings were observed, January 2016–April 2018, 17 semi-structured interviews were conducted and findings through a patient focus group were refined. Grounded theory was used to analyze field notes and transcripts.FindingsResults show how the social identity process enables patients to move through stages in a patient engagement continuum (informant, partner and active change agent). Initially, patient and team member perceptions of the patient's role influence their respective behaviors (activating, directing, framing and sharing). Subsequently, patient and team member behaviors influence patient contributions on the team, which can redefine patient and team member perceptions of the patient's role.Originality/valueAs health systems grow increasingly complex and become more interested in responding to patient expectations, understanding how to effectively engage patients on redesign teams gains importance. This research investigates how and why patient engagement on redesign teams changes over time and what makes different types of patient roles valuable for team objectives. Findings have implications for how redesign teams can better prepare, anticipate and support the changing role of engaged patients.
On the design and manufacturing of topologically optimized wings
Authors: Proença Tiago , Afonso Frederico , Lau Fernando , Policarpo Hugo , Lourenço João 
Published: October 2021

Purpose
The purpose of this paper is to evaluate the impact of different Additive Manufacturing (AM) orientations on the structural behavior of topologically optimized wings for Unmanned Aerial Systems (UAS), which might enable lightweight and low cost, yet complex, wing structural designs.

Design/methodology/approach
Based on an aerodynamic load, a two dimensional NACA0012 airfoil is topologically optimized considering PolyLatic Acid (PLA), several volume fractions and different manufacturing orientations. Then, the resulting topologies are post-processed to allow for manufacturing and extrude to three dimensional wing geometries with constant cross-sections. These wings are then manufactured using Fusion Deposition Modeling (FDM) technology and their dynamic structural behavior analyzed by means of Experimental Modal Analysis (EMA) in the linear elastic region.

Findings
Volume fraction increase is observed to improve the structural performance without increasing the manufacturing time. Despite manufacturing the wing from the leading edge to the trailing edge can reduce manufacturing time using FDM technology, it is found to be more difficult to build.

Originality/value
This research is a contribution toward the design and built of lightweight and low cost wings for UAS.
Histopathological examination of the ectocervical biopsy in non‐transplanted uteri: A study contributing to the provisional scoring system of subclinical graft rejection after uterus transplantation
Authors: Balko Jan , Novackova Marta , Skapa Petr , Pastor Zlatko , Chmel Roman , Zamecnik Josef , Chmel Roman 
Published: October 2021

AbstractIntroductionUterus transplantation is a causal treatment for absolute uterine factor infertility. Assessing rejection signs using a histopathological examination of the ectocervical biopsy from the transplanted uterus is common practice in all human uterus transplants worldwide to date. A provisional scoring system was used for the histopathological assessment of subclinical rejection signs in uterus recipients. Here we hypothesized that histopathological and immunohistochemical findings in the normal uteri would differ from the borderline category of subclinical rejection in uterine transplants.Material and methodsThis prospective observational study included ectocervical biopsies of 54 women who underwent hysterectomy for benign reasons. All biopsy samples were assessed histopathologically and immunohistochemically.ResultsMost of the ectocervical biopsies showed clustering lymphocytic infiltrates affecting the stromal–epithelial interface with the epithelial influx of lymphocytes, primarily CD45RO‐positive activated T‐cells with CD8 T‐lymphocyte predominance. CD4‐positive T‐lymphocytes and B‐cells were rarely detected in the ectocervix. These morphological findings and immunoprofiles of lymphocytic populations overlapped with the so‐called borderline changes defined in the provisional scoring system for rejection in the transplanted uteri. The immunoprofiles of ectocervical and endocervical lymphocytic populations differed, with strikingly prominent B‐cell participation in the endocervix vs the rare detection of B‐cells in the ectocervix.ConclusionsThe histopathological and immunohistochemical findings in the uteri of premenopausal women were similar to the borderline category of the currently used provisional scoring system of subclinical uterine rejection utilized in all uterine transplant studies. However, future similar studies are required to validate our findings.
Ontogenetic spatial constraints of sub‐arctic marine fish species
Authors: Ciannelli Lorenzo , Neuheimer Anna B. , Stige Leif C. , Frank Kenneth T. , Durant Joel M. , Hunsicker Mary , Rogers Lauren A. , Porter Steve , Ottersen Geir , Yaragina Natalia A. 
Published: October 2021

AbstractMarine species may respond and adapt to climate change through shifting spatial distributions, but options may be limited by the occupancy of essential habitats which are anchored in space. Limited knowledge of when spatial constraints are most likely to occur in marine fish life cycles has impeded the development of realistic distribution forecasts. In this study, we develop and implement analytical techniques to identify spatial constraints, defined by both the consistency through which a particular geographic area is used year after year, and by the extent of such area with respect to the entire population range. This approach is applied to simulated data and to ten case‐studies including six groundfish species from three subarctic marine systems. Our analyses illustrate that the early phase of the species’ life cycle is more spatially constrained than older life stages. We detected significant species‐specific variability in both the degree to which species are anchored in space throughout their life cycle, and the ontogenetic changes in the geographic association. There is an indication that this variability can be explained by the species life history strategy, highlighting the need to extend similar analyses to other species and regions. The presence of ontogenetic spatial constraints, particularly during early life stages, indicates restrictions exist to changes in spatial distribution and questions the assertion that global warming will uniformly result in an increase in abundance and harvest at higher latitudes and decreases at lower latitudes. Our study develops ecological and analytical insights that are critical for accurate projections of species distributions under different climate change scenarios.
The determinants of open interest in option markets
Authors: Harris Jeffrey H. , Shafer Michael 
Published: October 2021

AbstractOpen interest, the supply of options created, is driven by proxies for asymmetric information and theta (since option writers benefit from theta). Open interest increases with the magnitude of stock return momentum, especially for short‐sale constrained equities with negative return momentum. Moreover, open interest is positively related to firm risk (i.e., option writers respond to hedging demand), but the elasticity of supply decreases toward expiration when adverse selection costs become more salient. Open interest is also informative—we document that increases in open interest significantly presage seasoned equity offerings (SEOs), reflecting informed trading that is not evident with volume metrics.