bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factor V activity in apheresis platelets: Implications for management of FV deficiency
Authors: Gupta Gaurav K. , Hendrickson Jeanne E. , Bahel Parveen , Siddon Alexa J. , Rinder Henry M. , Tormey Christopher A. 
Published: November 2020

AbstractBackgroundAllogeneic platelet (PLT) infusion is a strategy to raise Factor V (FV) levels in patients with congenital FV deficiency. However, since FV is labile in vitro, we hypothesized that FV activity could be low in PLT units.Study Design and MethodsFV activity was tested using a prothrombin time‐based platform in the supernatant and platelet lysate (PL) of apheresis PLT units (16 units stored in PLT additive solution with acetate and phosphate [PAS‐C] and 10 units stored in plasma only), on post‐collection days 3‐6. Statistical analysis was performed using Student's t test (P < .05).ResultsFV activity was severely diminished in PAS‐C PLTs (N = 16) supernatant (3.70% ± 1.02%) and PL (3.26% ± 1.02%). FV activity in plasma‐only PLTs (N = 10) was lower in both supernatant (44.55% ± 6.46%) and lysate (39.67% ± 6.33%) relative to normal plasma levels, but both were significantly higher (P < .0001) compared to PAS‐C PLTs. In a separate set of experiments, FV activity in PAS‐C PLTs examined serially over storage time (N = 3 for these experiments) showed that FV levels were reduced by day 3 and not significantly different by day 5 of storage (Day 3 supernatant 5.03% ± 1.41%; Day 5 supernatant: 3.10% ± 0.57%; P = .2; Day 3 lysate: 3.89% ± 1.03%; Day 5 lysate: 2.61% ± 0.41%; P = .4).ConclusionPlasma should be considered over PLTs as first‐line therapy for non‐complex FV deficiency‐associated hemorrhage. If PLTs are considered for transfusion, plasma‐only PLT units should be preferentially utilized, as PAS‐C PLT have near‐absent FV activity.
Determinants of intention to return to donate blood among first‐time blood donors in Ghana
Authors: Asamoah‐Akuoko Lucy , Ullum Henrik , Appiah Bernard , Hassall Oliver W , Ndanu Thomas , Adongo Philip , Bates Imelda 
Published: November 2020

ObjectiveThis study seeks to identify factors that are predictive of intention to return to donate blood among first‐time blood donors.MethodsA cross‐sectional survey of 505 first‐time blood donors, selected from blood donation sessions across three regions in Ghana. Data were obtained on their intention to donate blood in the next four months, factors that would influence this decision. Logistic regression models were used to test factors that were predictive of intention to return.ResultsFirst‐time donors were young with 87·4% below 35 years of age, male (72·5%), single (73·3%), Christian (93·7%), employed (58·8%), with at least a basic education (98%). Factors that positively predicted intention to return included: motivational incentives (OR = 1·67, 95%CI: 1·01–2·78; P = 0·045); ease of access to the donation site (OR = 2·65, 95%CI: 1·48–4·73; P = 0·001); SMS and email reminders (OR = 2·84, 95%CI: 1·60–5·06; P < 0·001); and television, radio or newspaper advertisements (OR = 2·97, 95%CI: 1·66–5·31; P < 0·001). Factors that negatively predicted intention included preferential access to transfusions (i.e. ‘blood credits’) (OR = 0·43, 95%CI: 0·23–0·83; P = 0·012); getting to know test results (OR = 0·40, 95%CI: 0·20–0·80; P = 0·010); and not knowing and/or trusting what happens to the blood after donating (OR = 0·50, 95%CI: 0·28–0·88; P = 0·016).ConclusionMotivational incentives, convenient access to donation sessions, reminders and mass media advertisements appear to positively influence intention to return to donate. Conversely not knowing what happens to the blood after donation negatively influenced intention to return. Interventions to promote repeat blood donation should consider the identified factors.
Rock-Paper-Scissors Lattice Model
Authors: Ganikhodjaev Nasir , Hee Pah Chin 
Published: November 2020

In this work, we introduce Rock-Paper-Scissors lattice model on Cayley tree of second order generated by Rock-Paper-Scissors game. In this strategic 2-player game, the rule is simple: rock beats scissors, scissors beat paper, and paper beats rock. A payoff matrix of this game is a skew-symmetric. It is known that quadratic stochastic operator generated by this matrix is non-ergodic transformation. The Hamiltonian of Rock-Paper-Scissors Lattice Model is defined by this skew-symmetric payoff matrix . In this paper, we discuss a connection between three fields of research: evolutionary games, quadratic stochastic operators, and lattice models of statistical physics. We prove that a phase diagram of the Rock-Paper-Scissors model consists of translation-invariant and periodic Gibbs measure with period 3.
Preparation and characterization of p-sulfonated calix[4]arene functionalized chitosan hydrogel beads and their preliminary adsorption study towards removal of lead(II) and zinc(II) ions
Authors: Mohamad Zubir Hamizah Syahirah , Wahid Mohd Haniff , Ling Irene , Lim Hong Ngee , Kamaruzaman Sazlinda , Zainal Zulkarnain 
Published: November 2020

p-sulfonated calix[4]arene functionalized chitosan hydrogel beads have been successfully prepared by mixing p-sulfonated calix[4]arene and chitosan in dilute acetic acid solution (1% v/v), followed by dropping the mixture into sodium hydroxide solution to form beads with diameters of ~0.1 cm. The presence of the active sulfonate groups and the unique structure of calixarene render the material useful as an adsorbent for heavy metal ions. Metal adsorption on p-sulfonated calix[4]arene is possible through a combination of physical and ionic interactions. Atomic Absorption Spectroscopy (AAS) results showed that the amount of adsorbed metal ion is optimum at 10 ppm for all samples. The overall percentage of metal ion removal shows that p-sulfonated calix[4]arene modified chitosan is the best adsorbent with up to 98% removal achieved for Pb(II) and 90% removal for Zn(II). This is followed by p-sulfonated calix[4]arene and graphene oxide (GO) modified chitosan with up to 90% removal for Pb(II) and 89% removal for Zn(II) and pure chitosan hydrogel beads with up to 60% removal for both Pb(II) and Zn(II). The results clearly prove that the presence of p-sulfonated calix[4]arene can enhance the adsorption of heavy metal ions. In addition, the adsorbent shows higher Pb(II) removal compared to Zn(II).
An LSTM-Based Ensemble Learning Approach for Time-Dependent Reliability Analysis
Authors: Li Mingyang , Wang Zequn 
Published: November 2020

Abstract
This paper presents a long short-term memory (LSTM)-based ensemble learning approach for time-dependent reliability analysis. An LSTM network is first adopted to learn system dynamics for a specific setting with a fixed realization of time-independent random variables and stochastic processes. By randomly sampling the time-independent random variables, multiple LSTM networks can be trained and leveraged with the Gaussian process (GP) regression to construct a global surrogate model for the time-dependent limit state function. In detail, a set of augmented data is first generated by the LSTM networks and then utilized for GP modeling to estimate system responses under time-dependent uncertainties. With the GP models, the time-dependent system reliability can be approximated directly by sampling-based methods such as the Monte Carlo simulation (MCS). Three case studies are introduced to demonstrate the efficiency and accuracy of the proposed approach.
PaDGAN: Learning to Generate High-Quality Novel Designs
Authors: Chen Wei , Ahmed Faez 
Published: November 2020

Abstract
Deep generative models are proven to be a useful tool for automatic design synthesis and design space exploration. When applied in engineering design, existing generative models face three challenges: (1) generated designs lack diversity and do not cover all areas of the design space, (2) it is difficult to explicitly improve the overall performance or quality of generated designs, and (3) existing models generally do not generate novel designs, outside the domain of the training data. In this article, we simultaneously address these challenges by proposing a new determinantal point process-based loss function for probabilistic modeling of diversity and quality. With this new loss function, we develop a variant of the generative adversarial network, named “performance augmented diverse generative adversarial network” (PaDGAN), which can generate novel high-quality designs with good coverage of the design space. By using three synthetic examples and one real-world airfoil design example, we demonstrate that PaDGAN can generate diverse and high-quality designs. In comparison to a vanilla generative adversarial network, on average, it generates samples with a 28% higher mean quality score with larger diversity and without the mode collapse issue. Unlike typical generative models that usually generate new designs by interpolating within the boundary of training data, we show that PaDGAN expands the design space boundary outside the training data towards high-quality regions. The proposed method is broadly applicable to many tasks including design space exploration, design optimization, and creative solution recommendation.
METASET: Exploring Shape and Property Spaces for Data-Driven Metamaterials Design
Authors: Chan Yu-Chin , Ahmed Faez , Wang Liwei , Chen Wei 
Published: November 2020

Abstract
Data-driven design of mechanical metamaterials is an increasingly popular method to combat costly physical simulations and immense, often intractable, geometrical design spaces. Using a precomputed dataset of unit cells, a multiscale structure can be quickly filled via combinatorial search algorithms, and machine learning models can be trained to accelerate the process. However, the dependence on data induces a unique challenge: an imbalanced dataset containing more of certain shapes or physical properties can be detrimental to the efficacy of data-driven approaches. In answer, we posit that a smaller yet diverse set of unit cells leads to scalable search and unbiased learning. To select such subsets, we propose METASET, a methodology that (1) uses similarity metrics and positive semi-definite kernels to jointly measure the closeness of unit cells in both shape and property spaces and (2) incorporates Determinantal Point Processes for efficient subset selection. Moreover, METASET allows the trade-off between shape and property diversity so that subsets can be tuned for various applications. Through the design of 2D metamaterials with target displacement profiles, we demonstrate that smaller, diverse subsets can indeed improve the search process as well as structural performance. By eliminating inherent overlaps in a dataset of 3D unit cells created with symmetry rules, we also illustrate that our flexible method can distill unique subsets regardless of the metric employed. Our diverse subsets are provided publicly for use by any designer.
A Theoretical Investigation on the Performance and Combustion Parameters in an Spark Ignition Engine Fueled With Different Shale Gas Mixtures
Authors: Gürbüz Habib , Köse Şerife 
Published: November 2020

Abstract
In this paper, a zero-dimensional (0D) single-zone combustion model was applied for predicting combustion and indicated engine parameters in a spark ignition (SI) engine. Three different shale gas mixtures, methane, and liquefied petroleum gas (LPG) (30% C3H8–70% C4H10), were studied as SI engine fuel. The shale gas compositions included shale gas-1 (86% CH4–14% C2H6), shale gas-2 (81% CH4–10% C2H6–9% N2), and shale gas-3 (58% CH4–20% C2H6–2% C3H8–10% CO2). Experimental results of the SI engine operated with LPG were used in the model verification phase and provided to the validation of the theoretical model. In addition, the operational parameters of the LPG engine were used as the model input values. The results show that shale gas-1 has the potential to be a good alternative fuel to LPG for SI engines. Shale gas-1 has an indicated mean effective pressure (IMEP) value of 5.7–7.3%, which is lower than LPG in the range of ϕ = 0.83–1.2. Furthermore, LPG has a 27.7% higher indicated specific fuel consumption (ISFC) compared to shale gas-1. On the other hand, LPG has 1.2–2.4 units lower indicated thermal efficiency (ITE) values than shale gas-1 in the range of ϕ = 0.83–1.2. However, Methane, Shale gas-2, and Shale gas-3 have 7.55–9.62%, 20.35–20%, 22.19–21.47 lower IMEPs than LPG in the range of ϕ = 0.83–1.2, respectively.
Transitioning From Net-Zero Energy Homes to Carbon-Neutral Grid-Connected Communities
Authors: Fathy Angelique , Salib Amir , Krarti Moncef 
Published: November 2020

AbstractIn this study, optimal carbon-neutral designs are evaluated for grid-connected communities that include net-zero energy (NZE) homes in Boulder, CO. Specifically, the economic and environmental benefits are assessed for residential communities with various mixtures of both NZE and non-NZE homes. Optimization techniques based on life cycle costs including both capital costs and operating costs are used to design NZE homes as well as carbon-neutral communities. Using both energy efficiency measures and rooftop PV systems, the analysis estimates the capital costs required for NZE homes. Moreover, optimally sized distributed renewable systems are determined to achieve carbon-neutral operation for various types of residential communities. First, the impact of occupancy behavior in designing NZE homes as well as carbon-neutral communities is evaluated using three use patterns of appliances (i.e., refrigerator, television, dishwasher, and clothes washer) as well as domestic hot water. Then, different fractions of NZE homes are considered when designing carbon neural communities. The analysis indicates that occupant behavior can significantly affect the design of NZE homes as well as the capital costs to achieve this design. For instance, good behavior can result in 21.28% capital cost savings while bad behavior can result in a 10.42% increase in capital cost. Moreover, the analysis indicates while the communities made up partially or fully of NZE homes can attain carbon-neutral target with lower distributed generated (DG) capacities than non-NZE communities, they require high total capital costs at least based on current costs for distributed renewable technologies and utility electricity prices. Finally, it is found to be more cost-effective to share distributed power systems for communities rather than individual homes with their own rooftop PV system to attain carbon-neutral design.
Using the GAD-7 and GAD-2 Generalized Anxiety Disorder Screeners With Student-Athletes: Empirical and Clinical Perspectives
Authors: Tran Alisia G.T.T. 
Published: November 2020

With the aim of supporting anxiety screening of student-athletes, this study examined the psychometric performance of the GAD-7 and GAD-2 for assessing anxiety and other clinical mental health concerns (depression, past-year and recent suicidality) in student-athletes. Data from intercollegiate varsity athletes (N = 7,584) were drawn from the Healthy Minds Study. Reliability estimates were good in the sample. Area under the curve values were excellent for anxiety and fair to good for depression and suicidality. Across all clinical indicators, a cutoff of 6 (GAD-7) and 2 (GAD-2), respectively, yielded the most balanced sensitivity and specificity rates. Both measures positively correlated with functional impairment, academic impact, and perceived mental health and negatively correlated with positive mental health. Overall, results supported the reliability, accuracy, and construct validity of the GAD-7 and GAD-2 in a national student-athlete sample. Discussion focuses on clinical implications and practical usage of the GAD-7 and GAD-2 with student-athletes.
Low-dose or no aspirin administration in acute-phase Kawasaki disease: a meta-analysis and systematic review
Authors: Chiang Ming-Hsiu , Liu Hsingjin Eugene , Wang Jinn-Li 
Published: November 2020

ObjectiveTo compare the efficacy of low-dose or no aspirin with conventional high-dose aspirin for the initial treatment in the acute-phase of Kawasaki disease (KD).DesignA meta-analysis and systematic review of randomised control trials and cohort studies.MethodsAll available articles that compared different dosage of aspirin in the acute-phase of KD published until 20 September 2019 were included from the databases of PubMed, Embase and Cochrane Central Register of Controlled Trials Central without language restrictions. Extracted data from eligible studies were reviewed by two authors independently and analysed by using RStudio software.ResultsNine cohorts with a total of 12 182 children were enrolled. We found that low-dose (3–5 mg/kg/day) or no aspirin in the acute-phase KD was associated with reducing the risk of coronary artery lesions (CALs, OR=0.81, 95% CI 0.69 to 0.95). No differences were observed in intravenous immunoglobulin resistance, length of hospital stay and fever days after admission (OR=1.35, 95% CI 0.91 to 1.98; standard mean difference (SMD)=0.17, 95% CI −1.07 to 1.4; SMD=0.3, 95% CI −1.51 to 2.11) in the low-dose/no aspirin subgroup compared with the high-dose (≥30 mg/kg/day) aspirin subgroup. We did not identify any potential factors affecting the homogeneity of CAL risk as well as clinical important effects in all included studies.ConclusionsPrescribing low-dose or no aspirin in the acute-phase of KD might be associated with a decreased incidence of CAL. However, additional well-designed prospective trials are required to support the theory.
Is health politically irrelevant? Experimental evidence during a global pandemic
Authors: Acharya Arnab , Gerring John , Reeves Aaron 
Published: November 2020

ObjectiveTo investigate how health issues affect voting behaviour by considering the COVID-19 pandemic, which offers a unique opportunity to examine this interplay.DesignWe employ a survey experiment in which treatment groups are exposed to key facts about the pandemic, followed by questions intended to elicit attitudes toward the incumbent party and government responsibility for the pandemic.SettingThe survey was conducted amid the lockdown period of 15–26 April 2020 in three large democratic countries with the common governing language of English: India, the United Kingdom and the United States. Due to limitations on travel and recruitment, subjects were recruited through the M-Turk internet platform and the survey was administered entirely online. Respondents numbered 3648.ResultsOur expectation was that respondents in the treatment groups would favour, or disfavour, the incumbent and assign blame to government for the pandemic compared with the control group. We observe no such results. Several reasons may be adduced for this null finding. One reason could be that public health is not viewed as a political issue. However, people do think health is an important policy area (>85% agree) and that government has some responsibility for health (>90% agree). Another reason could be that people view public health policies through partisan lenses, which means that health is largely endogenous, and yet we find little evidence of polarisation in our data. Alternatively, it could be that the global nature of the pandemic inoculated politicians from blame and yet a majority of people do think the government is to blame for the spread of the pandemic (~50% agree).ConclusionsWhile we cannot precisely determine the mechanisms at work, the null findings contained in this study suggest that politicians are unlikely to be punished or rewarded for their failures or successes in managing COVID-19 in the next election.Trial registrationInitial research hypotheses centred on expected variation between two treatments, as set forth in a detailed pre-analysis plan, registered at E-Gap:http://egap.org/registration/6645. Finding no difference between the treatments, we decided to focus this paper on the treatment/control comparison. Importantly, results that follow the pre-analysis plan strictly are entirely consistent with results presented here: null findings obtained throughout.
Prevalence and health correlates of anaemia among community-dwelling Chinese older adults: the China Health and Retirement Longitudinal Study
Authors: Wang Ying , Ping Yong-Jing , Jin Hai-Yu , Ge Ning , Wu Chenkai 
Published: November 2020

ObjectivesTo identify the prevalence of anaemia among older adults in China by sociodemographic and geographical regions, and cross-sectionally examine the associations between anaemia and several geriatric outcomes.DesignCross-sectional study.Setting and participantsParticipants were 6656 older adults aged at least 60 years with haemoglobin data from the 2015 to 2016 wave of the China Health and Retirement Longitudinal Study.MethodsWe examined the prevalence of anaemia by sociodemographics (age, sex, residence, education, marital status) and geographical regions, adjusting for age. We investigated the associations between anaemia and geriatric conditions.ResultsThe prevalence of anaemia was 20.6% among adults ≥60 years and was higher at advanced ages, among those who were females, living in rural areas, and those who were unmarried. The southern region of China had a higher burden of anaemia than the north. Anaemic adults had a higher age-adjusted prevalence of falls, activities of daily living (ADL) disability, instrumental ADL disability, lower extremely functional limitation, upper extremely functional limitation, low gait speed, low grip strength and low self-reported memory.ConclusionsAnaemia affected approximately one in five older adults in China, particularly in those with disadvantaged sociodemographics, and anaemia was associated with a higher burden of geriatric conditions. Huge geographical disparities of anaemia prevalence between northern and southern regions reflected the dietary variations in different regions. Efforts on preventing anaemia and reducing regional disparities of anaemia were needed to improve older adults’ health in China.
Key stakeholders’ perspectives and experiences with defining, identifying and displaying gaps in health research: a qualitative study
Authors: Nyanchoka Linda , Tudur-Smith Catrin , Porcher Raphaël , Hren Darko 
Published: November 2020

IntroductionMapping the current body of evidence including what is missing helps provide a better understanding of what research is available, ongoing and needed and should be prioritised. Identifying research gaps can inform the design and conduct of health research by providing additional context information about the body of evidence in a given topic area. Despite the commonly used term ‘research gap’ in scientific literature, little is written on how to find a ‘research gap’ in the first place. Moreover, there is no clear methodological guidance to identify and display gaps.ObjectiveThis study aimed to explore how key stakeholders define research gaps and characterise methods/practices used to identify and display gaps in health research to further advance efforts in this area.DesignThis was an exploratory qualitative study using semistructured in-depth interviews. The study sample included the following stakeholder groups: researchers, funders, healthcare providers, patients/public and policy-makers. Interview transcripts were subjected to thematic analysis.ResultsAmong the 20 interviews conducted (20 participants), a variety of research gap definitions were expressed (ie, five main themes, including gaps in information, knowledge/evidence gaps, uncertainties, quality and patient perspective). We identified three main themes for methods used to identify gaps (primary, secondary and both primary and secondary) and finally six main themes for the methods to display gaps (forest plots, diagrams/illustrations, evidence maps, mega maps, 3IE gap maps and info graphics).ConclusionThis study provides insights into issues related to defining research gaps and methods used to identify and display gaps in health research from the perspectives of key stakeholders involved in the process. Findings will be used to inform methodological guidance on identifying research gaps.