bluuebunny/crossref_metadata_2025_split huggingface dataset:
Built environment influences on healthy eating and active living: The NEWPATH study
Authors: Frank Lawrence D. , Bigazzi Alexander , Hong Andy , Minaker Leia , Fisher Pat , Raine Kim D. 
Published: January 2022

AbstractObjectiveThe Neighbourhood Environments in Waterloo: Patterns of Active Transportation and Health (NEWPATH) study examined built environment influences on travel, physical activity, food consumption, and health. This collaboration between researchers and practitioners in health and transportation planning is the first, to our knowledge, to integrate food purchasing, diet, travel, and objectively measured physical activity into a trip‐destination protocol. This study simultaneously examines diet and physical activity relationships with BMI and waist circumference (WC).MethodsIndividual diet and travel diary data were linked to objective built‐environment measures of walkability and retail food environments. BMI and WC were self‐reported (n = 1,160). Some respondents wore accelerometers to objectively measure physical activity (n = 549). Pathways from the built environment through behavior (walking and eating) to BMI and WC were assessed using path analysis.ResultsWalkability was associated with lower BMI and WC through physical activity and active travel. Healthy retail food environments were associated with healthy eating and lower BMI and WC, whereas walkability and healthy retail food environments were insignificant (p < 0.05). Walkable neighborhoods had less healthy food environments, but active travel was not associated with healthy eating or caloric intake.ConclusionsFindings highlight the importance of neighborhood walkability and food environments in shaping physical activity, diet, and obesity.
Critic‐only online adaptive learning based decentralized control schemes for nonlinear large‐scale systems
Authors: Jiang He , Zhao Yan , Xie Xiangpeng , Wei Mofan 
Published: January 2022

AbstractIn this article, the decentralized control issues of nonlinear large‐scale systems are investigated via critic‐only adaptive dynamic programming learning methods. First of all, we build a specific relation between the decentralized control for interconnected subsystems and the optimal control for isolated subsystems. Then, we utilize neural networks (NNs) to implement a critic‐only online adaptive learning method. The stability analysis result provides the region of the online learning rate, and indicates the NN can approximate the optimal solution. Subsequently, it is proven that the small NN approximation errors cannot affect the system stability. Finally, the simulation examples verify the feasibility.
A cleaner processing approach for cellulose reinforced thermoplastic polyurethane nanocomposites
Authors: Mohd Amin Khairatun Najwa , Chaleat Celine , Edwards Grant , Martin Darren J. , Annamalai Pratheep Kumar 
Published: January 2022

AbstractIn a manner of addressing challenges in scalable processing of thermoplastic polyurethane (TPU) nanocomposites through extrusion methods, this study reports a very clean processing approach of incorporating cellulose nanocrystal (CNC) into a TPU matrix, with no acid or organic‐solvents usage. It involves a mechanical deconstruction of microcrystalline cellulose (MCC) into nanoscale particles in water and polyol through scalable bead‐milling, vacuum drying, and followed by twin‐screw reactive extrusion with isocyanate and chain extender. The thermal stability of CNC was higher than that of typically acid‐hydrolyzed CNC and suitable for processing with the precursors of TPU at typical processing temperature range (175–190°C). The CNC incorporation at very low loadings (0.5, 0.8 wt%) through this methodology resulted in substantial enhancements in tensile properties (for example, up to 28% in strength and toughness) without any significant stiffening effect. Moreover, the nanocomposites retained elastic properties, including elongation at break (%), resilience, and creep resistance. Their chemical properties and thermal transitions were also found to support the retained thermoplastic behavior while improving mechanical performance.
Novel histone modifications in microglia derived from a mouse model of chronic pain
Authors: Zhang Ping , Guergues Jennifer , Alleyne Amy R. , Cirino Thomas J. , Nadeau Owen , Figueroa Ariana M. , Stacy Heather M. , Suzuki Takayoshi , McLaughlin Jay P. , Stevens Stanley M. , Liu Bin 
Published: January 2022

AbstractAs the resident immune cells in the central nervous system, microglia play an important role in the maintenance of its homeostasis. Dysregulation of microglia has been associated with the development and maintenance of chronic pain. However, the relevant molecular pathways remain poorly defined. In this study, we used a mass spectrometry‐based proteomic approach to screen potential changes of histone protein modifications in microglia isolated from the brain of control and cisplatin‐induced neuropathic pain adult C57BL/6J male mice. We identified several novel microglial histone modifications associated with pain, including statistically significantly decreased histone H3.1 lysine 27 mono‐methylation (H3.1K27me1, 54.8% of control) and H3 lysine 56 tri‐methylation (7.5% of control), as well as a trend suggesting increased H3 tyrosine 41 nitration. We further investigated the functional role of H3.1K27me1 and found that treatment of cultured microglial cells for 4 consecutive days with 1–10 μM of NCDM‐64, a potent and selective inhibitor of lysine demethylase 7A, an enzyme responsible for the demethylation of H3K27me1, dose‐dependently elevated its levels with a greater than a two‐fold increase observed at 10 μM compared to vehicle‐treated control cells. Moreover, pretreatment of mice with NCDM‐64 (10 or 25 mg/kg/day, i.p.) prior to cisplatin treatment prevented the development of neuropathic pain in mice. The identification of specific chromatin marks in microglia associated with chronic pain may yield critical insight into the contribution of microglia to the development and maintenance of pain, and opens new avenues for the development of novel nonopioid therapeutics for the effective management of chronic pain.
How to derive spatial agents: A mixed‐method approach to model an elderly population with scarce data
Authors: Haacke Hannah C. , Enßle Friederike , Haase Dagmar , Lakes Tobia 
Published: January 2022

AbstractInformation about the spatial patterns of residents is essential, especially when elderly people are involved, as their action range is confined to their residential location. Since knowledge about patterns of elderly people in cities is limited, this paper formulates steps for the initialisation of an agent‐based model, combined with different data sources. The first step is to identify different types of elderly people using cluster analysis, and then the clusters are expanded into agent typologies with behaviour rules, which form the basis for an artificial population. The clusters are derived based on survey data and then analysed and modified using insights from census data and expert interviews. The agents' relocation behaviour is estimated based on literature research, expert interviews and a survey. The spatial information of the agents is added with a spatial microsimulation. The resulting artificial population presents the real population well and can be used in an empirically based data‐driven agent‐based model.
Time‐optimal control of piecewise affine bistable gene‐regulatory networks
Authors: Augier Nicolas , Yabo Agustín G. 
Published: January 2022

AbstractWe study the minimal‐time problem for a piecewise affine bistable switch. Motivated by applications in synthetic biology and biotechnology, the aim is to minimize the time needed for this system to achieve transitions between its two stable steady states. The latter represents the two possible states of a genetic toggle switch, a synthetic flip‐flop device playing a fundamental role in biocomputing and gene therapy. Results show that a time‐optimal transition between states should pass by an undifferentiated state, which is well known in cell biology for its importance in fate differentiation of cells. In order to characterize the capacity of the system to achieve transitions, we provide a lower bound on the minimal time, whose knowledge becomes relevant when considering realistic systems involving subsystems evolving on different time scales. Then, we show numerical simulations of optimal trajectories illustrating the structure of the bang‐bang optimal control for different scenarios.
Geomorphic responses of fluvial systems to climate change: A habitat perspective
Authors: Juracek Kyle E. , Fitzpatrick Faith A. 
Published: January 2022

AbstractFluvial systems provide a variety of habitats that support thousands of species including many that are threatened or endangered. Moreover, these habitats, which range from aquatic and riparian to floodplain, are important for the variety of ecosystem services they provide. In addition to water temperature and streamflow change, geomorphic change is important and warrants consideration as one of the several potential threats to these habitats posed by climate change. The geomorphic response of fluvial systems to global warming in temperate environments, for example, caused by an increase in the frequency and magnitude of floods, is important because geomorphology is a primary determinant of habitat availability and quality. Possible geomorphic responses include increased erosion and (or) deposition in the river channel, riparian zone, and floodplain with associated habitat implications. Geomorphic changes caused by global warming can be beneficial (e.g., increased habitat complexity) or detrimental (e.g., mortality caused by scour or burial) to biota. The ability of a species to respond to and survive disturbances, including geomorphic changes, will depend on the nature of the disturbances and the sensitivity and adaptive capabilities of the species. Post‐flood recovery often is rapid; however, for certain species (e.g., periphyton, macroinvertebrates), changes in community composition may persist. Increased flood frequency, sediment mobility, and associated geomorphic changes potentially will result in more frequent and persistent changes in habitat and community composition in the affected fluvial systems.
Tongue worm (Linguatula serrata) infection in a dog imported into the United Kingdom from Romania
Authors: Macrelli Michele , Mackintosh Adrienne 
Published: January 2022

AbstractLinguatula serrata, also known as tongue worm, is a zoonotic parasite that lives in the nasal airways of dogs where it is responsible for mild to severe rhinosinusitis. In recent years, the number of pets entering the United Kingdom from abroad has increased, with a coinciding increase in the number of L. serrata infections diagnosed in UK veterinary clinics. Here, we report a case of linguatulosis in a 10‐month‐old rescued dog imported from Romania. Two weeks post‐arrival, the dog showed coughing, nasal discharge, epiphora and respiratory distress. Two worm‐like parasites were expelled by sneezing and they were morphologically identified as L. serrata. L. serrata eggs were also detected. A macrocyclic lactone treatment was administered, and clinical signs resolved. L. serrata should be included in the differential diagnosis of respiratory disease in imported dogs. Due to the zoonotic potential of this parasite, rapid diagnosis and correct treatment is essential.
Long‐term mechanical ventilation of an 8‐week‐old dog with idiopathic polyradiculoneuritis
Authors: Calero Rodriguez Abraham , van Oostrom Hugo , de Grauw Janny 
Published: January 2022

AbstractA 2‐month‐old labrador retriever diagnosed with progressive polyradiculoneuritis was anaesthetised and mechanically ventilated with the aid of pressure control ventilation due to severe hypoventilation and hypoxaemia. Anaesthesia was maintained with propofol and midazolam constant‐rate infusions (CRIs). Over time, once the patient was showing spontaneous breathing attempts and arterial partial pressure of carbon dioxide was within normal range, ventilatory mode was switched to pressure support ventilation. The anaesthetic protocol was modified to maintain an appropriate level of anaesthesia with a minimum amount of fluid administered. The midazolam CRI was substituted by a sufentanil CRI, followed by a change to a dexmedetomidine CRI. An intensive nursing care protocol was established. Intermittent hyperthermia and peripheral oedema were the main complications observed. Ventilatory support was reduced until the patient was successfully weaned from the ventilator at the third attempt, after 116 hours of ventilatory support.
Neoplastic transformation of arteriopathy‐derived bone infarct into nascent osteosarcoma in the proximal tibia of a miniature schnauzer
Authors: Jimenez Isabel A. , Pool Roy R. , Fischetti Anthony J. , Gabrielson Kathy , Canapp Sherman O. 
Published: January 2022

AbstractA 9‐year‐old, entire, male miniature schnauzer with a history of chronic right hindlimb lameness was presented to a referral orthopaedic surgery practice for acute non‐weight bearing and suspected cranial cruciate ligament rupture. Radiographs revealed polyostotic bone infarcts, characterised by stippled medullary densities, and an aggressive osteolytic infarct in the right proximal tibia. Histopathology of the amputated limb revealed an arteriopathy of the nutrient artery and a zonal histologic pattern of neoplastic transformation: at the infarct apex, mesenchymal stromal cells were engaged in repair. As the cells proliferated towards the centre of the infarct within an environment of chronic ischaemia, cell features became consistent with low‐grade sarcoma, then nascent (early) osteosarcoma. This zonal progression has been described in humans, but not in dogs. It is unknown whether nascent osteosarcoma has the same biologic activity as long‐standing osteosarcoma. Veterinarians should be aware of canine bone infarcts and their potential sequelae.
Incremental deep learning for reflectivity data recognition in stomatology
Authors: Procházka Aleš , Charvát Jindřich , Vyšata Oldřich , Mandic Danilo 
Published: January 2022

AbstractThe recognition of stomatological disorders and the classification of dental caries are important areas of biomedicine that can hugely benefit from machine learning tools for the construction of relevant mathematical models. This paper explores the possibility of using reflectivity data to distinguish between healthy tissues and caries by deep learning and multilayer convolutional neural networks. The experimental data set includes more than 700 observations recorded in the stomatology laboratory. For rigor, the results obtained from the deep learning systems are compared with those evaluated for selected sets of features estimated for each observation and classified by a decision tree, support vector machine (SVM), k-nearest neighbor, Bayesian methods, and two-layer neural networks. The classification accuracy obtained for the deep learning systems was 98.1% and 94.4% for data in the signal and spectral domains, respectively, in comparison with an accuracy of 97.2% and 87.2% evaluated by the SVM method. The proposed method conclusively demonstrates how the artificial intelligence and deep learning methodology can contribute to improved diagnosis of dental problem in stomatology.
Media and government framing of asylum seekers and migrant workers in Canada during the COVID-19 pandemic
Authors: Stack Michelle , Wilbur Amea 
Published: January 2022

AbstractOne understudied area of adult education and lifelong learning is the role of media as educator and policy player. This article describes how the authors used critical discourse analysis to examine how asylum seekers, migrant workers and their advocates have challenged long-standing discursive framings of them as benefactors of Canadian generosity, criminals, burdens or victims – during the first ten months of the COVID-19 pandemic. The analysis points to the difficulties of navigating media engagement to advocate for individuals facing deportation from Canada, while also attempting to challenge the dichotomy of people seen either as worthy of dignity (those who work for low pay and in dangerous conditions to care for Canadians) or as unworthy (those who work on farms or who are not able to work). However, it also reveals the potential for critical lifelong media education to inform the work of adult educators across classroom, labour and social movement contexts to disrupt exclusionary and oppressive media and government narratives.
Relationship of abdominal aortic calcification with lumbar vertebral volumetric bone mineral density assessed by quantitative computed tomography in maintenance hemodialysis patients
Authors: Chen Tian-Yi , Yang Jie , Zuo Li , Wang Ling , Wang Li-Fang 
Published: January 2022

Abstract
Introduction
This cross-sectional study aimed to investigate the relationship between abdominal aortic calcification (AAC), which is a marker of vascular calcification, and volumetric bone mineral density (vBMD) by quantitative computed tomography (QCT) in maintenance hemodialysis (MHD) patients.

Methods
All participants underwent lumbar vertebral vBMD measurement by QCT. Eight cross-sections were extracted sequentially and analyzed by ImageJ software to obtain the ratio of the calcified area to the abdominal aortic area (the calcification ratio). The AAC score was determined by the sum of the calcification ratios. The relationship between AAC and vBMD was analyzed using multivariate logistic regression.

Results
Ninety MHD patients (58.89% male) with a mean age of 63.43 (standard deviation [SD] = 13.20) years were included in the study. AAC was present (AAC score > 0) in 93.33% of the patients. The 75th percentile of the AAC score corresponding to 119 was used as the cutoff point between the mild and severe groups. After full adjustment in the logistic model, AAC was found to be inversely associated with vBMD (odds ratio [OR], 0.970; 95% confidence interval [CI], 0.944 to 0.996; P = 0.025), and patients with osteoporosis had a significantly higher risk of severe AAC than those with normal bone mass (OR, 14.498; 95% CI, 1.507 to 139.486; P = 0.021). The independent inverse association was still stable after adjusting for variables measured at different time periods and using different cutoff points of the AAC score.

Conclusion
There was an independent inverse association between AAC and vBMD, and osteoporosis was significantly associated with severe AAC in patients with MHD.
Liver transplantation as a treatment for Wilson’s disease with neurological presentation: a systematic literature review
Authors: Litwin Tomasz , Bembenek Jan , Antos Agnieszka , Przybyłkowski Adam , Skowrońska Marta , Kurkowska-Jastrzębska Iwona , Członkowska Anna 
Published: January 2022

Abstract
Introduction
Wilson’s disease (WD) is a potentially treatable, genetic disorder of copper metabolism, with survival similar to healthy populations if controlled. However, in almost 50% of WD patients, neurological symptoms persist despite treatment, and in up to 10% of patients, neurological deterioration is irreversible. International guidelines on WD treatment do not recommend liver transplantation (LT) as a treatment for neurological symptoms in WD. However, such treatment has been assessed in retrospective analyses, case and series reports. We aimed to systematically assess all available evidence on the effectiveness and safety of LT in WD patients with neurological presentation.

Methods
This systematic literature review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were identified by searching the PubMed database (up to 6 April 2021) and by screening reference lists.

Results
Based on the systematic literature review, 48 articles were identified, showing outcomes of LT in 302 WD patients with neurological symptoms. Of these patients, major improvement was found in 215 cases (71.2%), with no difference in neurological status before and after LT in 21 cases (6.9%). There were 29 deaths (9.6%), neurological worsening in 24 cases (7.9%), and 13 cases (4.3%) were lost to follow-up.

Conclusions
The results suggest that LT is a promising method of WD management in patients with severe, neurological symptoms, particularly if the patient has not responded to pharmacological de-coppering treatment. Further studies of LT in these patients are warranted.
Predictive Market Making via Machine Learning
Authors: Haider Abbas , Wang Hui , Scotney Bryan , Hawe Glenn 
Published: January 2022

AbstractMarket making (MM) is an important means of providing liquidity to the stock markets. Recent research suggests that reinforcement learning (RL) can improve MM significantly in terms of returns. In the latest work on RL-based MM, the reward is a function of equity returns, calculated based on its current price, and the inventory of MM agent. As a result, the agent’s return is maximised and liquidity is provided. If the price movement is known and this information is optimally utilised, there is potential that the MM agent’s return can be further improved. Important questions are, how to predict stock price movement, and how to utilise such prediction? In this paper, we introduce the concept of predictive market marking (PMM) and present our method for PMM, which comprises a RL-based MM agent and a deep neural network (DNN)-based price predictor. A key component of PMM is the consolidated price equation (CPE), which amalgamates an equity’s present and predicted market prices into a consolidated price, which is used to generate ask and bid quotes that reflect both current price and future movement. Our PMM method is evaluated against the state-of-the-art (RL-based MM) and a traditional MM method, using ten stocks and three exchange traded funds (ETFs). Out-of-sample backtesting showed that our PMM method outperformed the two benchmark methods.
Feasibility of Calculating Aortic Pulse Wave Velocity from Oscillometric Upper Arm Pulse Waves Using the Antares Algorithm
Authors: Baulmann Johannes , Dörr Marcus , Genzel Elisabeth , Stäuber Alexander , Richter Stefan , Ohlow Marc-Alexander , Eckert Siegfried 
Published: January 2022

Abstract
Background
Antares is an algorithm for oscillometric blood pressure (BP) monitors to determine aortic pulse wave velocity (PWV) solely using oscillometric pulse waves without dependence of any other input. The aim of this study is to test Antares PWV for feasibility and whether the known age and blood pressure dependence of PWV can be shown with Antares PWV.

Methods
In total, 259 patients were investigated for PWV as sub-study of the invasive validation of Antares algorithm, of which 219 entered analyses. Non-invasive PWV determination by Antares algorithm, integrated into an oscillometric BP monitor (custo screen 400) was compared to five different ePWV equations based on age, BP, or both. Additionally, in a subset of 27 patients, comparison of ARCSolver PWV algorithm (Mobil-O-Graph) with Antares PWV and ePWV was conducted.

Results
Mean differences ± SD between Antares PWV and (A) ePWV (based on age and systolic BP) was − 0.05 ± 1.06 m/s (Spearman’s rank correlation coefficient, rS = 0.805); (B) ePWV (based on age) was − 1.75 ± 1.17 m/s (rS = 0.829); (C) ePWV (based on mean BP) was − 1.35 ± 1.24 m/s (rS = 0.763), and (D) ePWV (based on age and mean BP) was − 1.64 ± 1.22 m/s (rS = 0.810) and − 1.69 ± 1.18 m/s (rS = 0.802). Comparison of Antares PWV with ARCSolver PWV revealed a mean difference of − 0.65 ± 1.31 m/s (rS = 0.854).

Conclusion
The Antares algorithm confirmed its feasibility to use an oscillometric BP monitor as a single-point measurement device to calculate aortic PWV with acceptable comparability and high correlation to both estimated PWV and ARCSolver PWV. Antares achieves these results solely based on analysis of waveform features without requiring any secondary input, like BP or age.