bluuebunny/crossref_metadata_2025_split huggingface dataset:
Free sorting task of chocolate proteins bars: Pilot study and comparison between trained and untrained panelists
Authors: Marque Céline , Motta Caroline , Richard Thibaud J. C. 
Published: April 2022

AbstractA free sorting task was applied to sort chocolate proteins bars by trained and untrained panelists. Trained and untrained panelists sorted the nine chocolate proteins bars samples into groups. They were then asked to describe in their own words after the sorting was done. Multidimensional Scaling and Correspondence Analysis were performed on these data. Results showed that trained and untrained panels sorted the chocolate proteins bars in a similar way (RV coefficient value). The results also show that the trained panel was significantly more objective than the untrained panel. However, comparable terms were used similarly by both panels and statistical results indicated that untrained and trained panels could be used for free sorting tasks as both panels were able to perform the test being discriminative.Practical ApplicationsThe free sorting task method was used for the first time to differentiate a complex food product with trained and untrained panelists. This task associated with word association was a success and enable the use of this sensory method to potentially understand a strategic local market with consumer feedback.
Peer support in small towns: A decentralized mobile Hepatitis C virus clinic for people who inject drugs
Authors: Midgard Håvard , Bjørnestad Ronny , Egeland Maren , Dahl Eivin , Finbråten Ane‐Kristine , Kielland Knut B. , Blindheim Martin , Dalgard Olav 
Published: April 2022

AbstractBackground & AimsNew models of HCV care are needed to reach people who inject drugs (PWID). The primary aim was to evaluate HCV treatment uptake among HCV RNA positive individuals identified by point‐of‐care (POC) testing and liver disease assessment in a peer‐driven decentralized mobile clinic.MethodsThis prospective study included consecutive patients assessed in a mobile clinic visiting 32 small towns in Southern Norway from November 2019 to November 2020. The clinic was staffed by a bus driver and a social educator offering POC HCV RNA testing (GeneXpert®), liver disease staging (FibroScan® 402) and peer support. Viremic individuals were offered prompt pan‐genotypic treatment prescribed by local hospital‐employed specialists following a brief telephone assessment.ResultsAmong 296 tested individuals, 102 (34%) were HCV RNA positive (median age 51 years, 77% male, 24% advanced liver fibrosis/cirrhosis). All participants had a history of injecting drug use, 71% reported past 3 months injecting, and 37% received opioid agonist treatment. Treatment uptake within 6 months following enrolment was achieved in 88%. Treatment uptake was negatively associated with recent injecting (aHR 0.60; 95% CI 0.36–0.98), harmful alcohol consumption (aHR 0.44; 95% CI 0.20–0.99), and advanced liver fibrosis/cirrhosis (aHR 0.44; 95% CI 0.25–0.80). HCV RNA prevalence increased with age (OR 1.81 per 10‐year increase; 95% 1.41–2.32), ranging from 3% among those <30 years to 55% among those ≥60 years.ConclusionsA peer‐driven mobile HCV clinic is an effective and feasible model of care that should be considered for broader implementation to reach PWID outside the urban centres.
Evidence for tissue‐specific defence‐offence interactions between milkweed and its community of specialized herbivores
Authors: López‐Goldar Xosé , Hastings Amy , Züst Tobias , Agrawal Anurag 
Published: April 2022

AbstractCoevolution between plants and herbivores often involves escalation of defence‐offence strategies, but attack by multiple herbivores may obscure the match of plant defence to any one attacker. As herbivores often specialize on distinct plant parts, we hypothesized that defence‐offence interactions in coevolved systems may become physiologically and evolutionarily compartmentalized between plant tissues. We report that roots, leaves, flower buds and seeds of the tropical milkweed (Asclepias curassavica) show increasing concentrations of cardenolide toxins acropetally, with latex showing the highest concentration. In vitro assays of the physiological target of cardenolides, the Na+/K+–ATPase (hereafter “sodium pump”), of three specialized milkweed herbivores (root‐feeding Tetraopes tetrophthalmus, leaf‐feeding Danaus plexippus, and seed‐feeding Oncopeltus fasciatus) show that they are proportionally tolerant to the cardenolide concentrations of the tissues they eat. Indeed, molecular substitutions in the insects’ sodium pumps predicted their tolerance to toxins from their target tissues. Nonetheless, the relative inhibition of the sodium pumps of these specialists by the concentration versus composition (inhibition controlled for concentration, what we term “potency”) of cardenolides from their target versus nontarget plant tissues revealed different degrees of insect adaptation to tissue‐specific toxins. In addition, a trade‐off between toxin concentration and potency emerged across plant tissues, potentially reflecting coevolutionary history or plant physiological constraints. Our findings suggest that tissue‐specific coevolutionary dynamics may be proceeding between the plant and its specialized community of herbivores. This novel finding may be common in nature, contributing to ways in which coevolution proceeds in multispecies communities.
Environment‐driven shifts in interindividual variation and phenotypic integration within subnetworks of the mussel transcriptome and proteome
Authors: Tanner Richelle L. , Gleason Lani U. , Dowd W. Wesley 
Published: April 2022

AbstractThe environment can alter the magnitude of phenotypic variation among individuals, potentially influencing evolutionary trajectories. However, environmental influences on variation are complex and remain understudied. Populations in heterogeneous environments might exhibit more variation, the amount of variation could differ between benign and stressful conditions, and/or variation might manifest in different ways among stages of the gene‐to‐protein expression cascade or among physiological functions. Here, we explore these three issues by quantifying patterns of inter‐individual variation in both transcript and protein expression levels among California mussels, Mytilus californianus Conrad. Mussels were exposed to five ecologically relevant treatments that varied in the mean and interindividual heterogeneity of body temperature. To target a diverse set of physiological functions, we assessed variation within 19 expression subnetworks, including canonical stress‐response pathways and empirically derived coexpression clusters that represent a diffuse set of cellular processes. Variation in expression was particularly pronounced in the treatments with high mean and heterogeneous body temperatures. However, with few exceptions, environment‐dependent shifts of variation in the transcriptome were not reflected in the proteome. A metric of phenotypic integration provided evidence for a greater degree of constraint on relative expression levels (i.e., stronger correlation) within expression subnetworks in benign, homogeneous environments. Our results suggest that environments that are more stressful on average – and which also tend to be more heterogeneous – can relax these expression constraints and reduce phenotypic integration within biochemical subnetworks. Context‐dependent “unmasking” of functional variation may contribute to interindividual differences in physiological phenotype and performance in stressful environments.
Revealing historical perspectives on the professionalization of nursing education in Norway—Dilemmas in the past and the present
Authors: Nyborg Vibeke Narverud , Hvalvik Sigrun 
Published: April 2022

AbstractThe professionalization of modern nursing education from 1850 and forward is closely linked to values and virtues underpinned by Christian ideals, sex‐based stereotypes and class. Development in the late 19th century of modern hospital medicine, combined with a scientific understanding of antisepsis and asepsis, hygiene, contagion prevention and germ theory, were highly influential insights to the dominant position of modern medicine in health care. This development constituted a key premise for what nurses, by virtue of being women, and combined with their education, could offer in terms of medical assistance. It enabled them to challenge the prevailing sex‐based stereotypes‐ and class‐based hierarchies, allowing modern nursing to retain aspects of both traditional Christian and womanly values, while at the same time adhering to the medical science paradigm. In this paper, we argue that modern nursing education developed in a context characterized by traditional female and religious values, while at the same time being increasingly dominated by the influence of scientific and medical progress. This conflict between traditional and modern values caused dilemmas and tensions as the nursing profession developed. We argue further that similar dilemmas and tensions continue to pervade contemporary nursing and nursing education.
Nasolabial appearance in unilateral cleft lip and palate patients: A comparison of aesthetics using two scoring systems: A cross‐sectional study
Authors: Talwar Aditya , Duggal Isha , Duggal Ritu , Chaudhari Prabhat Kumar , Samrit Vilas 
Published: April 2022

AbstractObjectiveThe objective of the study was to assess nasolabial aesthetics in patients with complete unilateral cleft lip, with or without cleft palate (UCL ± P) using two scoring systems.DesignA cross‐sectional study conducted in a tertiary care government hospital.PatientsPhotographic records of 91 patients with complete UCL ± P from the age group of 5–18 years (mean age = 13.2 ± 3.14 years) were included.MethodA panel of three orthodontists with varying experience in cleft management rated nasolabial aesthetics using two scoring systems, that is Asher Mc‐Dade index (AMAI) and Cleft Aesthetic Rating Scale (CARS). Intraclass correlation coefficient, Fleiss' kappa and Cronbach's alpha were used to measure the internal consistency amongst three raters and Spearman–Brown formula was used for measuring overall reliability. Time required for assessment of each photograph was compared with ANOVA.ResultsOverall, both AMAI and CARS showed high reliability and outcome assessment with good inter‐rater reliability and internal consistency, when used independently by orthodontists having varied experience. Statistically significant difference was present in time taken for assessment of nasolabial aesthetics with CARS index (8.75 ± 1.65 seconds) as compared to AMAI (18.62 ± 3.49 seconds).ConclusionAsher Mc‐Dade index and CARS are equally reliable and consistent for the assessment of nasolabial aesthetics in patients with UCL ± P. However, considerably less time was taken for the assessment using CARS index as compared to AMAI. The use of CARS index is recommended for the initial assessment and screening of patients by orthodontists using two dimensional photographs.
Distance of doing business and outward foreign direct investment: An empirical study of China
Authors: Qian Xinbei , Liu Dexue , Huang Liangxiong , Li Hanchao 
Published: April 2022

AbstractDifferences between the business environment in the home country and the host country are an important factor when enterprises consider their location choice with regard to outward foreign direct investment (OFDI). However, this is ignored by much existing literature. Based on the trade‐off framework of international firms between exporting and participation in OFDI under the condition of heterogeneous enterprises, this paper constructs a theoretical model of the impact of distance of doing business (DDB) on OFDI. We take China's OFDI as an example and use the World Bank Group's Ease of Doing Business Index to construct the DDB indicator, as well as test the impact of the DDB on China's OFDI by combining the macro‐location panel data of China's OFDI between 2004 and 2017. The results showed that increasing DDB significantly reduces the scale of China's OFDI. The effect is robust. The mechanism is that DDB significantly decreases the success rate of OFDI and increases the cost of OFDI, thereby decreasing the scale of OFDI. Further analysis then finds that official acts, such as building partnerships, and folk acts, such as increasing cultural identity, can significantly reduce the negative effect of DDB on OFDI.
Sucrose synthase activity is not required for cellulose biosynthesis in Arabidopsis
Authors: Wang Wei , Viljamaa Sonja , Hodek Ondrej , Moritz Thomas , Niittylä Totte 
Published: April 2022

SUMMARYBiosynthesis of plant cell walls requires UDP‐glucose as the substrate for cellulose biosynthesis, and as an intermediate for the synthesis of other matrix polysaccharides. The sucrose cleaving enzyme sucrose synthase (SUS) is thought to have a central role in UDP‐glucose biosynthesis, and a long‐held and much debated hypothesis postulates that SUS is required to supply UDP‐glucose to cellulose biosynthesis. To investigate the role of SUS in cellulose biosynthesis of Arabidopsis thaliana we characterized mutants in which four or all six Arabidopsis SUS genes were disrupted. These sus mutants showed no growth phenotypes, vascular tissue cell wall defects, or changes in cellulose content. Moreover, the UDP‐glucose content of rosette leaves of the sextuple sus mutants was increased by approximately 20% compared with wild type. It can thus be concluded that cellulose biosynthesis is able to employ alternative UDP‐glucose biosynthesis pathway(s), and thereby the model of SUS requirements for cellulose biosynthesis in Arabidopsis can be refuted.
Modelling global value chains: From trade costs to policy impacts
Authors: Shepherd Ben 
Published: April 2022

AbstractI use an approach from the family of ‘new quantitative trade models’ to explore the links between trade costs and integration in Global Value Chains (GVCs). The model conceptualises GVC trade through a multi‐country, multi‐sector Ricardian model that nests the standard structural gravity model. It provides a general framework in which to assess the impacts of changes in iceberg trade costs on GVC trade, understood as the sum of backward linkages and pure double counting, in line with recent work on trade in value added. As an example, I use the model to show that observed changes in trade facilitation performance between 2015 and 2019 have strong explanatory power for observed changes in GVC trade during the same period: the model accounts for over one‐third of the observed change, albeit with substantial variation across countries and sectors.
Adaptive Design of Experiments for Automotive Engine Applications Using Concurrent Bayesian Optimization
Authors: Zhu Ling , Wang Yan , Pal Anuj , Zhu Guoming G. 
Published: April 2022

Abstract
Most practical automotive problems require the design of experiments (DoEs) over a number of different operating conditions to deliver optimal calibration parameters. DoE is especially crucial for automotive engine calibration problems due to its increasing complexity and nonlinearity. As the complexity of the system increases, the DoE applications require a significant amount of expensive testing. However, only a limited number of testings are available and desired. The current work addresses this issue by presenting an adaptive DoE method based on Bayesian optimization to find optimal parameter settings with a significantly reduced number of physical testings (or function evaluations). To further improve optimization efficiency, this work presents a new approach: concurrent Bayesian optimization, which searches for optimal DoE under multiple operating conditions simultaneously. The method utilizes a surrogate model and a novel concurrent evolutionary multi-objective optimization method: concurrent non-dominated sorting genetic algorithm-II, to solve adaptive DoE in multiple operating conditions with a limited number of function evaluations. The experimental study is carried out on a gasoline engine calibration problem using a high-fidelity GT-SUITE™ engine model. The experimental results demonstrate the effectiveness of the algorithm by optimizing engine performance with a significantly reduced number of expensive testings to achieve accurate optimal solutions. The method simultaneously performs engine calibration at eight different operating conditions using only 500–600 testings, compared to the traditional approach, where each operating condition requires 300–500 testings independently to achieve optimal results.
Experimental Investigation on the Concentration Polarization and Power Output of a Reverse Electrodialysis Stack With Permselective Spacers for Different Factors
Authors: Li Mei , Guo Jiabin , Wang Yiwei , Guo Pengcheng , Li Xiaoliang , Liu Xiaoqian 
Published: April 2022

Abstract
The use of permselective spacers in reverse electrodialysis (RED) stack introduces a more severe concentration polarization phenomenon at membrane–solution interfaces in spite of effectively suppressing the spacer shadow effect. In this paper, the concentration polarization phenomenon in RED with permselective spacers is analyzed for different membrane types, numbers of cell pairs, solution concentrations, and temperatures by measuring non-ohmic resistance based on direct and alternating current methods combined with theoretical formula. Experiments on direct current method are further made to determine the influence of concentration polarization on power output and power generation performance of stack for different factors. The results show that the non-ohmic resistance accounts for less than 40% of the total stack resistance. Increasing the flowrate and solution temperature effectively suppresses the concentration polarization in stack and thus is beneficial to improving the power output. However, the membrane type, number of cell pairs, and solution concentration hardly affect concentration polarization. In spite of this, these factors all have a considerable impact on the power generation performance of the stack. Among them, increasing the concentration of concentrated and diluted solutions is most beneficial to improving the power density.
Employing Deep Learning Neural Networks for Characterizing Dual-Porosity Reservoirs Based on Pressure Transient Tests
Authors: Kumar Pandey Rakesh , Kumar Anil , Mandal Ajay , Vaferi Behzad 
Published: April 2022

Abstract
The deep learning model constituting two neural network models (i.e., densely connected and long short-term memory) has been applied for automatic characterization of dual-porosity reservoirs with infinite, constant pressure, and no-flow external boundaries. A total of 16 different prediction paradigms have been constructed (one classifier to identify the reservoir models and 15 regressors for predicting the dual-porosity reservoir characteristics). Indeed, wellbore storage coefficient, CDe2S, skin factor, interporosity flow coefficient, and storativity ratio have been estimated. The training pressure signals have been simulated using the analytical solution of the governing equations with varying noise percentages. The pressure drop and derivation of the noisy synthetic signals serve as the input signals to the intelligent scenario. The hyperparameters of the intelligent model have been carefully adjusted to improve its prediction performance. The trained classification model attained 99.48% and 99.32% accuracy over the training and testing datasets. The separately trained 15 regressors converged well to estimate the reservoir parameters. The model performance has been demonstrated with three uniquely simulated and real-field cases. The results indicate that the compiled prediction model can accurately identify the reservoir model and estimate the corresponding characteristics.
Nondestructive Microstructure Characterization of Tempered Martensitic Steels Through Data Fusion
Authors: Mawhin M. A. , Seuaciuc-Osorio T. 
Published: April 2022

Abstract
Determination of the present condition of grade 91 steels commonly used in fossil plants presents an ongoing challenge for the industry. Current individual methods of nondestructive evaluations (NDEs) are challenged to reliably determine steel microstructures and are impractical for deployment over large areas such as piping systems. This work investigates the discriminatory potential of an integral assessment combining multiple NDE techniques: magnetic methods (including coercive field, incremental permeability, and Barkhausen noise), thermoelectric power, and ultrasonic methods (including attenuation, backscatter, and absorption). Using a sample inventory of manufactured representative microstructure conditions in thin-walled tubes, five of the eight microstructure conditions could be identified by data fusion. Combined magnetic methods appeared as a primary technique, as this can identify four out of the eight conditions, while the ultrasonic methods can be seen as complimentary tests to increase confidence in classification and identify a fifth condition.
Development and Extrinsic Calibration of a 3D Optical Multisensor Platform Using Laser Line Scanner and a Three-Axis Linear Motion Unit
Authors: Gollee Christian , Seidel André , Schenke Christer-Clifford , Hellmich Arvid , Ihlenfeldt Steffen 
Published: April 2022

Abstract
The area-based three-dimensional optical inspection of workpiece geometries is the basis for quality control, maintenance tasks, and many other typical applications in mechanical engineering and automation such as adaptive manufacturing. In the context of a cyber–physical approach for semi-autonomous post-processing of additively manufactured parts, this method provides the basis for an iterative manufacturing approach. Commercially available systems for optical inspections often rely on camera-based methods, which are, however, susceptible to reflections. This article describes an approach for developing an optical scanstation that uses blue laser line scanners in combination with a Cartesian three-axis motion system and a turntable. The focus of the work is on the development of a method for the fast extrinsic calibration of the entire scanstation.
Uncovering Human Errors Associated With System-User Interactions Using Functional Modeling
Authors: Soria Zurita Nicolás F. , Tensa Melissa Anne , Ferrero Vincenzo , Stone Robert B. , DuPont Bryony , Onan Demirel H. , Tumer Irem Y. 
Published: April 2022

AbstractDesigners should adequately develop user considerations such as usability, safety, and comfort during the design process of new systems. Nevertheless, incorporating human factors engineering principles during early design phases is not simple. The objective of this work is to assist designers in implementing human factors engineering principles during early design phases using a functional model framework. This effort expands our previous work on automating the function-human error design method (FHEDM) implementation. In this work, we use data mining techniques in a design repository to explore the construction of association rules between components, functions, flows, and user interactions. Such association rules can support designers assessing user-system interactions during the early design stages. To validate this approach, we compare the associations generated by expert designers using the FHEDM while designing a new product to those generated by an algorithm using the repository data. The results show notable similarities between the associations extracted by the algorithm and the associations identified by designers. Thus, the overall results show that association rules extracted from a rich dataset can be used to distinguish user-product interactions, demonstrating the potential of automating the identification of user-product interactions from a functional model.