bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of the effect of pork compositions on freezing points in different pork cuts by measuring thermal properties and water mobility and distribution
Authors: Bai Yun , Guo Yiping , Ding Daming , Ye Keping 
Published: November 2021

AbstractThis work was to compare the difference of freezing point in the four pork cuts (chuck roll, picnic shoulder, loin, and topside) and evaluate the effect of pork compositions on the freezing points. Loin exhibited lower freezing points and accompanied by higher content of unfreezable water, lower relaxation times, and higher proportions of bound water, compared with other pork cuts. Low freezing points of pork may be attributed to high sarcoplasmic protein solubility, due to high sarcoplasmic protein solubility related to increase of bound water proportion and decrease of NMR T2 relaxometry. In addition, correlation analysis revealed that sarcoplasmic protein solubility and ash content were negatively related to the freezing point, which was verified by a quadratic polynomial correlation between the sarcoplasmic protein solubility and the freezing point in vitro. These results could help to better understand the freezing point of pork and provide more theories for improving superchilled storage.
Predictive value of different bilirubin subtypes for clinical outcomes in patients with acute ischemic stroke receiving thrombolysis therapy
Authors: Peng Qiwei , Bi Rentang , Chen Shengcai , Chen Jiefang , Li Zhifang , Li Jianzhuang , Jin Huijuan , Hu Bo 
Published: November 2021

AbstractAimsTo explore the association of total bilirubin (TBIL), direct bilirubin (DBIL), and indirect bilirubin (IBIL) levels with, as well as the incremental predictive value of different bilirubin subtypes for, poor outcomes in acute ischemic stroke patients after thrombolysis.MethodsWe analyzed 588 individuals out of 718 AIS participants, and all patients were followed up at 3 months after thrombolysis. The primary outcome was 3‐month death and major disability (modified Rankin Scale (mRS) score of 3–6). The secondary outcomes were 3‐month mortality (mRS score of 6), moderate‐severe cerebral edema, and symptomatic intracranial hemorrhage (sICH), respectively.ResultsElevated DBIL pre‐thrombolysis was associated with an increased risk of primary outcome (OR 3.228; 95% CI 1.595–6.535; p for trend = 0.014) after fully adjustment. Elevated TBIL pre‐thrombolysis showed the similar results (OR 2.185; 95% CI 1.111–4.298; p for trend = 0.047), while IBIL pre‐thrombolysis was not significantly associated with primary outcome (OR 1.895; 95% CI 0.974–3.687; p for trend = 0.090). Multivariable‐adjusted spline regression model showed a positive linear dose‐response relationship between DBIL pre‐thrombolysis and risk of primary outcome (p for linearity = 0.004). Adding DBIL pre‐thrombolysis into conventional model had greater incremental predictive value for primary outcome, with net reclassification improvement (NRI) 95% CI = 0.275 (0.084–0.466) and integrated discrimination improvement (IDI) 95% CI = 0.011 (0.001–0.024). Increased DBIL post‐thrombolysis had an association with primary outcome (OR 2.416; 95%CI 1.184–4.930; p for trend = 0.039), and it also elevated the incremental predictive value for primary outcome, with NRI (95% CI) = 0.259 (0.066–0.453) and IDI (95% CI) = 0.025 (0.008–0.043).ConclusionIncreased DBIL pre‐thrombolysis had a stronger association with, as well as greater incremental predictive value for, poor outcomes than TBIL and IBIL did in AIS patients after thrombolysis, which should be understood in the context of retrospective design. The effect of DBIL on targeted populations should be investigated in further researches.
Adherence to and persistence with antidiabetic medications and associations with clinical and economic outcomes in people with type 2 diabetes mellitus: A systematic literature review
Authors: Evans Marc , Engberg Susanne , Faurby Mads , Fernandes João Diogo Da Rocha , Hudson Pollyanna , Polonsky William 
Published: November 2021

AbstractWe designed a systematic literature review to identify available evidence on adherence to and persistence with antidiabetic medication in people with type 2 diabetes (T2D). Electronic screening and congress searches identified real‐world noninterventional studies (published between 2010 and October 2020) reporting estimates of adherence to and persistence with antidiabetic medication in adults with T2D, and associations with glycaemic control, microvascular and/or macrovascular complications, hospitalizations and healthcare costs. Ninety‐two relevant studies were identified, the majority of which were retrospective and reported US data. The proportions of patients considered adherent (median [range] 51.2% [9.4%‐84.3%]) or persistent (median [range] 47.7% [16.9%‐94.0%]) varied widely across studies. Multiple studies reported an association between greater adherence/persistence and greater reductions in glycated haemoglobin levels. Better adherence/persistence was associated with fewer microvascular and/or macrovascular outcomes, although there was little consistency across studies in terms of which outcomes were improved. More adherent and more persistent patients were typically less likely to be hospitalized or to have emergency department visits/admissions and spent fewer days in hospital annually than less adherent/persistent patients. Greater adherence and persistence were generally associated with lower hospitalization costs, higher pharmacy costs and lower or budget‐neutral total healthcare costs compared with lower adherence/persistence. In conclusion, better adherence and persistence in people with T2D is associated with lower rates of microvascular and/or macrovascular outcomes and inpatient hospitalization, and lower or budget‐neutral total healthcare expenditure. Education and treatment strategies to address suboptimal adherence and persistence are needed to improve clinical and economic outcomes.
Sensor data fusion for the industrial artificial intelligence of things
Authors: Djenouri Youcef , Belhadi Asma , Srivastava Gautam , Houssein Essam H. , Lin Jerry Chun‐Wei 
Published: November 2021

AbstractThe emergence of smart sensors, artificial intelligence, and deep learning technologies yield artificial intelligence of things, also known as the AIoT. Sophisticated cooperation of these technologies is vital for the effective processing of industrial sensor data. This paper introduces a new framework for addressing the different challenges of the AIoT applications. The proposed framework is an intelligent combination of multi‐agent systems, knowledge graphs and deep learning. Deep learning architectures are used to create models from different sensor‐based data. Multi‐agent systems can be used for simulating the collective behaviours of the smart sensors using IoT settings. The communication among different agents is realized by integrating knowledge graphs. Different optimizations based on constraint satisfaction as well as evolutionary computation are also investigated. Experimental analysis is undertaken to compare the methodology presented to state‐of‐the‐art AIoT technologies. We show through experimentation that our designed framework achieves good performance compared to baseline solutions.
Mass mortalities associated with viral nervous necrosis in Murray cod in China
Authors: Wang Yifan , Xu Liwen , Ma Weixiang , Sun Heng , Huang Zengchao , Cai Shuanghu , Jian Jichang , Huang Yucong 
Published: November 2021

AbstractIn December 2019, a mass mortality among cultured Murray cod (Maccullochella peelii peelii) fry occurred on a freshwater farm located at Foshan city of Guangdong province, China. The cumulative mortality was up to 45% within 15 days. The diseased fish showed clinical signs, including abnormal swimming behaviour, loss of appetite and dark body colouration before mass mortality. Samples of brain and retina tissues were collected from affected fish and subjected to reverse transcriptase polymerase chain reaction detection and virus isolation in cell culture. Approximately 430 bp product was detected from the brain and retina tissues and culture supernatant of betanodavirus‐infected SSN‐1 cells. The typical cytopathic effect of betanodavirus infection, which is characterized by vacuolation, was observed in SSN‐1 cells at three days after inoculating with the tissue filtrate of diseased Murry cod fry, and the TCID50 of the infected SSN‐1 cell supernatant was 107.8. Histopathological examinations revealed vacuolation and necrosis in the brain and retina of naturally and experimentally infected Murray cod fry. Electron microscopic observation also showed the aggregation of numerous spherical, non‐enveloped viral particles measuring 22–28 nm in diameter in the cytoplasm of betanodavirus‐infected SSN‐1 cells. Sequence and phylogenetic analysis based on RdRp and Cp genes further indicated that the betanodavirus isolated from Murray cod belonged to the RGNNV genotype. Much higher mortality was obtained in challenged Murray cod fry compared with the controls through immersion challenge. This study is the first report of the natural infection of betanodavirus in freshwater fish in China.
Combined effects of elevated rearing temperature and dietary energy level on heart morphology and growth performance of Tasmanian Atlantic salmon (Salmo salar L.)
Authors: Foddai Marco , Carter Chris G. , Hilder Pollyanna E. , Gurr Harley , Ruff Nicole 
Published: November 2021

AbstractCardiac abnormalities may pose a threat to salmonid aquaculture due to their potential detrimental effect on fish health and welfare. The teleost heart is an extremely plastic organ with important morphological differences between wild and farmed fish that include ventricular shape, alignment of the bulbus arteriosus and epicardial fat deposition. However, little is known about how different factors and interactions among them may affect cardiac morphology of Atlantic salmon. To determine whether rearing temperature could induce cardiac malformations in large Tasmanian Atlantic salmon, we examined a range of cardiac morphology indicators and growth parameters in a population of 1–2 kg seawater salmon (n = 60 temperature−1 diet−1) exposed to control and elevated temperatures of 15 and 19°C, respectively, while fed one of two commercial feeds with different dietary energy levels. Most fish possessed conspicuous fat around the heart with a tendency towards a rounded ventricle and a more obtuse angle of the bulbus arteriosus. However, fish showed no significant differences in heart shape and bulbus alignment in relation to water temperature and dietary energy. These results suggest that cardiac morphology of large Atlantic salmon is unlikely to be affected by rearing temperature and dietary energy during the grow‐out phase.
Multidimensional factors affecting homebound older adults: A systematic review
Authors: Lee JuHee , Suh Yujin , Kim Yielin 
Published: November 2021

AbstractPurposeTo systematically identify the multidimensional factors affecting homebound older adults.DesignSystematic review.MethodsWe searched PubMed, MEDLINE, Cochrane Library, CINAHL, EMBASE, and PsycINFO from inception to November 15, 2020. This systematic review followed the Preferred Reporting Items for Systematic Review and Meta‐analysis guidelines. The Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross‐Sectional Studies was used for quality assessment.FindingsNineteen studies met the review criteria; the studies were either cross‐sectional or longitudinal. Most studies have focused on personal factors affecting homebound older adults. The individual construct consisted of demographic, biological, psychological, functional, and health‐related factors. The structural construct included architectural, environmental, community, and social factors. Based on the different definitions of homebound used in the studies, the prevalence of homebound status ranged from 3.5% to 39.8%.ConclusionsThe prevalence of homebound status among older adults varied depending on how homebound was defined. Homebound status is the interaction between the individual and structural constructs. Variations in cultural, political, and economic conditions could influence homebound status across countries over time. Comprehensive assessment and interventions for homebound older adults based on multidisciplinary approaches are recommended for nurses.Clinical relevanceThis research will impact the development of nursing strategies to screen homebound older adults and provide targeted preventive interventions so that older adults with many risk factors do not become homebound.
The politics of the production of knowledge on trauma: the Grenfell Tower Inquiry
Authors: OHANA NATALIE 
Published: November 2021

AbstractThrough an analysis of data obtained from research carried out with the bereaved families of Grenfell Tower and residents of North Kensington, this article demonstrates that the Grenfell community's knowledge on the causes that led to the fire is being systematically excluded by the Inquiry. The article discusses the four main ways in which this is happening. Through its exclusionary practices, the Inquiry is representing a diversion from the principles set by the Hillsborough Independent Panel and the Stephen Lawrence Inquiry and is creating conditions that will impede its ability to fulfil the purpose for which it was established. By linking Foucault's power/knowledge theory and critical trauma studies, it is demonstrated that the Inquiry is reflecting a central dynamic that exists in processes of knowledge production on trauma. The lens of knowledge known to people who have undergone trauma is recognized as a critical research tool in revealing legal mechanisms of knowledge exclusion.
cis‐prenyltransferase 3 and α/β‐hydrolase are new determinants of dolichol accumulation in Arabidopsis
Authors: Gawarecka Katarzyna , Siwinska Joanna , Poznanski Jaroslaw , Onysk Agnieszka , Surowiecki Przemyslaw , Sztompka Karolina , Surmacz Liliana , Ahn Ji Hoon , Korte Arthur , Swiezewska Ewa , Ihnatowicz Anna 
Published: November 2021

AbstractDolichols (Dols), ubiquitous components of living organisms, are indispensable for cell survival. In plants, as well as other eukaryotes, Dols are crucial for post‐translational protein glycosylation, aberration of which leads to fatal metabolic disorders in humans and male sterility in plants. Until now, the mechanisms underlying Dol accumulation remain elusive. In this study, we have analysed the natural variation of the accumulation of Dols and six other isoprenoids among more than 120 Arabidopsis thaliana accessions. Subsequently, by combining QTL and GWAS approaches, we have identified several candidate genes involved in the accumulation of Dols, polyprenols, plastoquinone and phytosterols. The role of two genes implicated in the accumulation of major Dols in Arabidopsis—the AT2G17570 gene encoding a long searched for cis‐prenyltransferase (CPT3) and the AT1G52460 gene encoding an α/β‐hydrolase—is experimentally confirmed. These data will help to generate Dol‐enriched plants which might serve as a remedy for Dol‐deficiency in humans.
Why Jefferson Delivered His First Annual Message in Writing: New Historical Evidence
Authors: Laracey Mel 
Published: November 2021

AbstractWhen he delivered his first annual message in 1801, Thomas Jefferson departed from prior presidential practice and delivered the message to Congress in writing rather than as a speech. Scholars have differed over the meaning and significance of his action. This article examines new historical evidence on the question. The evidence is a commentary in Jefferson's presidential newspaper that explained the reasons for his action; a letter Jefferson wrote explaining his action; and commentaries on the action from Federalist Party opposition newspapers.
Therapeutic effects of equine amniotic membrane suspension on corneal re‐epithelialization and haze in a modified lagomorph ex vivo wound healing model
Authors: Boss Christine K. , Gibson Daniel J. , Schultz Gregory , Whitley R. David , Hernandez Jorge A. , Abbott Jeffrey R. , Plummer Caryn E. 
Published: November 2021

AbstractObjectiveTo investigate the therapeutic effects of topical equine amniotic membrane (eAM) suspension following corneal wounding in a controlled experimental setting.ProceduresEquine amniotic membrane was collected, gamma irradiated, homogenized for topical suspension preparation, and cryopreserved. Corneoscleral rims harvested from fresh rabbit globes were wounded via keratectomy and were maintained in an air‐liquid interface ex vivo corneal culture model. Treatment groups included topical gamma irradiated eAM suspension (n = 20) and a control group (n = 20). Re‐epithelialization of the wound was assessed with daily photographic evaluation of area of fluorescein uptake (mm2). Corneal wound haze after a 21‐day period was assessed by photographic analysis of haze area (mm2) and pixel intensity (0–255). Histologic processing of corneal tissue was performed, and protein identification of eAM suspension using Liquid chromatography‐mass spectrometry (LC‐MS).ResultsThe average day of complete corneal re‐epithelialization in controls (5.5 ± 1.1) and topically treated (5.5 ± 0.6) corneas, and rates of reduction in area of fluorescein uptake over time did not significantly differ (p = .44). The corneal wound haze was significantly reduced in mean area by approximately 52% and intensity by 57% in corneas treated with topical eAM suspension (p < .05), compared to controls 21 days following wounding. Protein analysis identified numerous proteins, specifically decorin, dermatopontin, and lumican, which have previously been documented in eAM.ConclusionsArea and intensity of corneal wound haze were significantly reduced in corneas treated with gamma irradiated eAM suspension, which may be due to previously identified therapeutic proteins which promote corneal clarity.
Strut Diameter Uncertainty Prediction by Deep Neural Network for Additively Manufactured Lattice Structures
Authors: Gorguluarslan Recep M. , Ates Gorkem Can , Utku Gungor O. , Yamaner Yusuf 
Published: November 2021

Abstract
Additive manufacturing (AM) introduces geometric uncertainties on the fabricated strut members of lattice structures. These uncertainties result in deviations between the modeled and fabricated geometries of struts. The use of deep neural networks (DNNs) to accurately predict the statistical parameters of the effective strut diameters to account for the AM-introduced geometric uncertainties with a small training dataset for constant process parameters is studied in this research. For the training data, struts with certain angle and diameter values are fabricated by the material extrusion process. The geometric uncertainties are quantified using the random field theory based on the spatial strut radius measurements obtained from the microscope images of the fabricated struts. The uncertainties are propagated to the effective diameters of the struts using a stochastic upscaling technique. The relationship between the modeled strut diameter and the characterized statistical parameters of the effective diameters are used as the training data to establish a DNN model. The validation results show that the DNN model can predict the statistical parameters of the effective diameters of the struts modeled with angles and diameters different from the ones used in the training data with good accuracy even if the training data set is small. Developing such a DNN model with small data will allow designers to use the fabricated results in the design optimization processes without requiring additional experimentations.
Learning to Improve Performance During Non-Repetitive Tasks Performed by Robots
Authors: Yoon Yeo Jung , Gupta Satyandra K. 
Published: November 2021

Abstract
To execute non-repetitive tasks, robots need to learn on the tasks to improve task performance. The performance model cannot be built in advance for such non-repetitive tasks. The robot can execute a small portion of the task with certain process parameters and attractively update the process parameters based on the observations of the task performance. To make the learning process efficient, the trade-off between exploration and exploitation should be explicitly considered. Too much exploration may lead to the waste of time without significant improvement on task performance. On the other hand, stopping exploration prematurely may lead to suboptimal task performance. This paper describes a sequential decision making approach to select the set of parameters to improve task performance. The overall learning approach uses feasibility biased sampling, surrogate model construction and greedy optimization. We implement our approach in the simulation of robotic sanding. We also compare our method with other design of experiments methods.
Improved Anti-Lock Braking System With Real-Time Friction Detection to Maximize Vehicle Performance
Authors: Arricale Vincenzo Maria , Maiorano Antonio , Mosconi Lorenzo , Napolitano Dell’Annunziata Guido , Rocca Ernesto , Albarella Nicola 
Published: November 2021

Abstract
Nowadays, advanced driver assistance systems play a fundamental role to improve vehicle safety and drivability; their capability to reduce the accidents rate was widely demonstrated, but these systems could also be employed to improve vehicle performance if incorporated with other control logics. This work presents an evolved version of the anti-lock braking system, obtained thanks to the combined use of a bicycle model, capable to estimate the actual friction coefficient in different environmental conditions, and a potential friction estimator based on a Magic Formula tire model with a slip-slope approach. With the presented ABS, virtually tested in several conditions, it is possible to reduce the braking distance with the final aim of reducing the braking time and, in this way, improving the vehicle performance.
A Universal Nonlinear Analyzer for Rigid Multibody Systems Based on the Efficient Galerkin Averaging-Incremental Harmonic Balance Method
Authors: Ju Ren , Fan Wei , Zhu Weidong 
Published: November 2021

Abstract
The bridge between the multibody dynamic modeling theory and nonlinear dynamic analysis theory is built for the first time in this work by introducing an efficient Galerkin averaging-incremental harmonic balance (EGA-IHB) method for steady-state nonlinear dynamic analysis of index-3 differential algebraic equations (DAEs) for general rigid multibody systems. The multibody dynamic modeling theory has made significant advances in generality and simplicity, and multibody systems are usually governed by DAEs. Since the fast Fourier transform and EGA are used, the EGA-IHB method has excellent robustness and computational efficiency. Since the Floquet theory cannot be directly used for stability analysis of periodic responses of DAEs, a new stability analysis procedure is developed, where perturbed, linearized DAEs are reduced to ordinary differential equations with use of independent generalized coordinates. A modified arc-length continuation method with a scaling strategy is used for calculating response curves and conducting parameter studies. Three examples are used to show the performance and capability of the current method. Periodic solutions of DAEs from the EGA-IHB method show excellent agreement with those from numerical integration methods. Amplitude-frequency and amplitude-parameter response curves are generated, and stability and period-doubling bifurcations are analyzed. The EGA-IHB method can be used as a universal solver and nonlinear analyzer for obtaining steady-state periodic responses of DAEs for general multibody systems.