bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reduced Platelet Adhesion for Blended Electrospun Meshes with Low Amounts of Collagen Type I
Authors: Sameti Mahyar , Clarke Kai , Dewan Prerona , Washington Kenyatta S. , Talebzadeh Somayeh , Liao Yi , Bashur Chris A. 
Published: October 2021

AbstractA clinically approved, tissue engineered graft is needed as an alternative for small‐diameter artery replacement. Collagen type I is commonly investigated for naturally derived grafts. However, collagen promotes thrombosis, currently requiring a graft pre‐seeding step. This study investigates unique impacts of blending low collagen amounts with synthetic polymers on scaffold platelet response, which would allow for viable acellular grafts that can endothelialize in vivo. While platelet adhesion and activation are confirmed to be high with 50% collagen samples, low collagen ratios surprisingly exhibit the opposite, anti‐thrombogenic effect. Different platelet interactions in these blended materials can be related to collagen structure. Low collagen ratios show homogenous distribution of the components within individual fibers. Importantly, blended collagen scaffolds exhibit significant differences from gelatin scaffolds, including retaining percentage of collagen after incubation. These findings correlate with functional benefits including better endothelial cell spreading on collagen versus gelatin blended materials. This appears to differ from the current paradigm that processing with harsh solvents will irreversibly denature collagen into less desirable gelatin, but an important distinction is the interaction between collagen and synthetic materials during processing. Overall, excellent anti‐thrombogenic properties of low collagen blends and benefits after grafting show promise for this vascular graft strategy.
Oxygen‐Tolerant RAFT Polymerization Catalyzed by a Recyclable Biomimetic Mineralization Enhanced Biological Cascade System
Authors: Yuan Bolei , Huang Tingting , Wang Xinghuo , Ding Yi , Jiang Lin , Zhang Yunhe , Tang Jun 
Published: October 2021

AbstractAn enzyme cascade system including glucose oxidase (GOx) and iron porphyrin (DhHP‐6) is encapsulated in a metal–organic framework called zeolitic imidazolate framework‐8 (ZIF‐8) through one‐step facile synthesis. The composite (GOx&DhHP‐6@ZIF‐8) is then used to initiate oxygen‐tolerant reversible addition‐fragmentation chain‐transfer polymerization for different methacrylate monomers, such as 2‐diethylaminoethyl methacrylate, 2‐hydroxyethyl methacrylate, and poly(ethylene glycol) methyl ether methacrylate (Mn = 500 g mol−1). The composite shows the robustness toward solvent and temperatures, all polymerizations using above monomers and catalyzing by GOx&DhHP‐6@ZIF‐8 exhibits high monomer conversion (>85%) and narrow molar mass dispersity (<1.3). Besides, acrylic and acrylamide monomers such as 2‐hydroxyethyl acrylate and N,N‐dimethylacrylamide are also carried to demonstrate the broad applicability. Proton nuclear magnetic resonance characterization and chain extension experiments confirm the retaining end groups of the resultant polymers, which is a significant feature of living polymerization. More importantly, the process of recycling the composite through a centrifuge is simplistic, and the composite still maintains similar activity compared to the original composites after five times. This low‐cost and easily separated composite catalyst represents a versatile strategy to synthesize well‐defined functional polymers suitable for industrial‐scale production.
Recent Advances in Diversity‐Oriented Polymerization Using Cu‐Catalyzed Multicomponent Reactions
Authors: Lee In‐Hwan , Bang Ki‐Taek , Yang Hee‐Seong , Choi Tae‐Lim 
Published: October 2021

AbstractDiversification of polymer structures is important for imparting various properties and functions to polymers, so as to realize novel applications of these polymers. In this regard, diversity‐oriented polymerization (DOP) is a powerful synthetic strategy for producing diverse and complex polymer structures. Multicomponent polymerization (MCP) is a key method for realizing DOP owing to its combinatorial features and high efficiency. Among the MCP methods, Cu‐catalyzed MCP (Cu‐MCP) has recently paved the way for DOP by overcoming the synthetic challenges of the previous MCP methods. Here the emergence and progress of Cu‐MCP, its current challenges, and future perspectives are discussed.
Farmer identities influence wildlife habitat management in the US Corn Belt
Authors: Dixon Adam P. , Arbuckle J. Gordon , Ellis Erle C. 
Published: October 2021

Abstract

Farmer wildlife management practices are critical to conserve biodiversity and ecosystem functions across intensively used agricultural landscapes. Policies and initiatives aimed at encouraging these practices have generally focused on economic incentives, with limited effectiveness.

Farmer identity theory addresses the emergence of norms, values and perceptions in farm management and can contribute to the development of policies and initiatives that engage more effectively with farmers and farming communities.

Here we evaluate linkages between farmer identity and wildlife habitat management practices in the intensively farmed US state of Iowa.

We conducted an exploratory factor analysis using data from a survey of over 1,300 Iowa farmers that asked their opinions on what constitutes ‘a good farmer’. We use logistic regression to model relationships between farmer identity factor scores and contextual variables against participation in a set of habitat management practices.

Four ‘good farmer’ identity types were identified and labelled as productivist, soil conservationist, wildlife conservationist and civic‐minded. Logistic regression results indicated that these farmer identity types have highly divergent responses to wildlife habitat management practices among Iowa farmers. Recreational factors may supplement identity and are also influential towards habitat production on farms.

We conclude that farmer identity theory offers a critical link between social and ecological processes on Iowa farms. The research presented here quantitatively associates farmer identity theory with wildlife habitat management, increasing our understanding of how wildlife habitat practices and individual‐level farmer identities interact.

A free Plain Language Summary can be found within the Supporting Information of this article.
Quantitative proteomic analysis of hepatic tissue in allotetraploid hybridized from red crucian carp and common carp identified crucial proteins and pathways associated with metabolism and growth rate
Authors: Yan Yujie , Wang Junting , Dong Xiaoping , Cai Yisheng , Wang Yude , Ren Li , Zhang Chun , Tao Min , Luo Kaikun , Zeng Yong , Liu Shaojun 
Published: October 2021

AbstractAllotetraploid is a new species produced by distant hybridization between red crucian carp (Carassius auratus red var., abbreviated as RCC) and common carp (Cyprinus carpio L., abbreviated as CC). There is a significant difference in growth rate between allotetraploid and its parents. However, the underlying molecular mechanism is largely unknown. In this study, to find direct evidence associated with metabolism and growth rate in protein level, we performed quantitative proteomics analysis on liver tissues between allotetraploid and its parents. A total of 2502 unique proteins were identified and quantified by SWATH‐MS in our proteomics profiling. Subsequently, comprehensive bioinformatics analyses including gene ontology enrichment analysis, pathway and network analysis, and protein–protein interaction analysis (PPI) were conducted based on differentially expressed proteins (DEPs) between allotetraploid and its parents. The results revealed several significant DEPs involved in metabolism pathways in liver. More specifically, the integrative analysis highlighted that the DEPs ACSBG1, OAT, and LDHBA play vital roles in metabolism pathways including “pentose phosphate pathway,” “TCA cycle,” and “glycolysis and gluconeogenesis.” These could directly affect the growth rate in fresh water fishes by regulating the metabolism, utilization, and exchange of substance and energy. Since the liver is the central place for metabolism activity in animals, we firstly established the comprehensive and quantitative proteomics knowledge base for liver tissue from freshwater fishes, our study may serve as an irreplaceable reference for further studies regarding fishes’ culture and growth.
Host‐mediated attenuation of gut sucrase in mustard aphid Lipaphis erysimi impaired its parthenogenetic reproduction on Indian mustard Brassica juncea
Authors: Dhatwalia Deepa , Aminedi Raghavendra , Kalia Vinay , Pande Veena , Bhattacharya Ramcharan 
Published: October 2021

AbstractBACKGROUNDThe nefarious hemipteran mustard aphid (Lipaphis erysimi) inflicts colossal yield losses in Brassica crops including Indian mustard (Brassica juncea). Lack of an accessible resistance source has been the primary impediment in breeding varietal resistance against aphids. In recent years, in planta RNAi‐mediated resistance has been demonstrated in model plants as a potential tool for protection against insect pests. However, translational application in crop species is imperative for critical assessment of this technology in breeding effective resistance.RESULTSThe essential role of sucrase 1 (SUC1) in mitigating osmotic pressure imposed by sucrose‐rich phloem sap inside the insect gut is corroborated by its expression pattern in L. erysimi. Transgenic lines of Indian mustard were developed expressing SUC1 hairpin RNA for its host‐mediated delivery into the infesting aphids. The expression of the dsRNA encoding cassette, and generation of siRNA molecules in transgenic B. juncea lines were verified by quantitative reverse transcription (RT)‐PCR, stem‐loop RT‐PCR and Northern hybridization. Rearing of L. erysimi on the transgenic lines resulted in 22–40% reduction in aphid fecundity. The observed retardation in aphid reproduction was coherent with the detection of SUC1‐specific siRNA molecules and attenuation of the SUC1 transcript level in L. erysimi fed on the transgenic lines.CONCLUSIONAugmenting varietal resistance can substantially reduce usage of toxic agrochemicals in crop protection. This attempt was the first successful demonstration of host‐mediated RNAi of an aphid gene in any Brassica crop. It paves the way for more rigorous attempt of engineering RNAi‐based resistance against aphids in Brassica crops. © 2021 Society of Chemical Industry.
A parameter‐free exponential control chart based on Kullback‐Leibler information for time‐between‐events monitoring
Authors: Chang Yu‐Ching , Wu Yi‐Cheng 
Published: October 2021

AbstractThis paper proposes a Kullback‐Leibler information (KLI) control chart for monitoring the occurrence rate of a process that follows an exponential distribution. The chart is designed for detecting a decrease, an increase, or both in the occurrence rate. Due to the skewness of the plotted statistic, the performance of the chart is investigated separately when the occurrence rate is estimated by the maximum likelihood estimator, the uniformly minimum variance unbiased estimator, and the minimum mean squared error estimator. The KLI chart is effective for a wide range of shifts of the occurrence rate. Its performance is slightly behind cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) charts around sizes of shift where these two charts are optimized. It outperforms these two charts elsewhere. The relative mean index (RMI) values show that the KLI chart has better overall performance. A backward empirical sequential test is used for the plotted statistic of the chart. It is shown equivalent to the cumulative sum scheme and the change point method for the generalized likelihood ratio chart in terms of run length. The use of KLI chart does not require any design parameter other than the control limit.
Building greener motorhomes: How dual‐purpose technical and relational capabilities affect component and full product innovation
Authors: Parmigiani Anne , Irwin Jennifer , Lahneman Brooke 
Published: October 2021

AbstractResearch SummaryThis study investigates how dual‐purpose technical and relational capabilities influence two types of product innovation: component and full product. We consider product modification, manufacturing, supplier relationship, and customer relationship capabilities, analyzing their interactions and interrelationships through an inductive study set in the motorhome industry. We find patterns between capabilities and types of product innovations and then use a descriptive qualitative comparative analysis to refine and explore the nuances of these relationships, uncovering combinations of capabilities that enable and inhibit different types of product innovation. We thus provide empirical evidence for how dual‐purpose capabilities are deployed dynamically, in that skills can be used in both the normal course of business and to create something new.Managerial SummaryFirms strive to innovate and create new full products and new components. Skills related to innovation include product modification, manufacturing, supplier management, and customer relations, all of which are also important for normal activities. While an adequate level of these capabilities can support the day‐to‐day business, a superior level is required to innovate. Our study of the motorhome industry indicates that supplier management is most important for component innovation and manufacturing expertise is most critical for full product innovation. However, we also find that a lack in some capabilities can be compensated for by superior capabilities in other areas, which could be important in situations of scarce resources and shows different possible paths toward product innovation.
Novel machine learning framework for thermal conductivity prediction by crystal graph convolution embedded ensemble
Authors: Sun Yajing , Hu Wenping 
Published: October 2021

AbstractWith the advent of the big data era, artificial intelligence technology has penetrated and deeply affected our daily life. In addition, data‐based machine learning algorithms have been applied to physics, chemistry, material science, and other basic science fields. However, the scarcity of data sets is known as the main obstacle to its development. Mining effective information from the limited data samples and building an appropriate machine learning algorithms framework are the major breakthroughs. For solid materials, the intrinsic properties are closely related to their atomic composition and relative positions, namely crystal structures. Here, inspired by the emerging of graph convolution neural network and material crystal graph, we proposed an integrated algorithms framework embedded crystal graph to train and predict the lattice thermal conductivities of crystal materials. This machine learning algorithms framework showed superior learning and generalization ability. In addition, not only in predicting thermal conductivities, but our framework also has great performance in predicting other phonon or electron‐related properties. This strategy provided a new approach in the design of machine learning framework, which indicated the great potential for the application of machine learning in material science.
A metaheuristic‐based data replica placement approach for data‐intensive IoT applications in the fog computing environment
Authors: Taghizadeh Jaber , Ghobaei‐Arani Mostafa , Shahidinejad Ali 
Published: October 2021

AbstractOver the past few years, Internet of Things (IoT) applications have grown rapidly. The data‐intensive IoT applications that take advantage of cloud servers for computations and data storage will result in higher latency and other network traffic in the Internet core. IoT applications are characterized by their sensitivity to latency. As an example, delays will result in irreparable damage in the medical and healthcare industries. Cloud servers are no longer necessary because cloud computing utilizes fog nodes that are closer to users. Nodes with different hardware capabilities pose a significant challenge since they differ significantly in latency and traffic reduction. This article presented a metaheuristic‐based method using the non‐dominated sorting genetic algorithm II for data‐intensive IoT applications in fog infrastructure. Besides, we provide a new automatic method for managing data replica transmissions, including deploying them in a fog cloud environment. The proposed solution was evaluated in the iFogSim simulator and compared with two other data replica placement methods in different scenarios. The results showed a decrease in latency and cost for data access and an increase in data availability.
Effects of compatibilizers on microstructural and viscoelastic properties of polypropylene/polybutadiene thermoplastics vulcanizates
Authors: Rafiei Somayeh , Soudbar Davood , Sadri Minoo , Shafiei Fatemeh 
Published: October 2021

AbstractCompatibilized thermoplastic vulcanizates (TPVs) based on polypropylene (PP) and polybutadiene rubber (PBR) were developed through the melt‐mixing method, and their morphological, rheological, and dynamic mechanical properties were investigated. The composition of PBR/PP blends (30/70 and 40/60) was designed in a way to study the interrelationship between the compatibilizer content and blend composition. In this study, a hydrocarbon resin (MS 40) was employed as the compatibilizer. Based on morphological analysis, the addition of compatibilizer in both blend compositions led to a finer and more uniform distribution of rubber domains; however, only for 40/60 composition, the higher content of compatibilizer caused the formation of a co‐continuous morphology. Both dynamic and static rheology results were highly susceptible to the compatibilizer content and blend composition. According to the storage and loss modulus curves, the incorporation of PBR into PP resulted in a significantly enhanced elastic response with 30/70 composition showing lower elasticity. The viscosity upturn in complex viscosity curves indicated the formation of a three‐dimensional network of dispersed rubber domains within the matrix, which led to the appearance of a highly elastic response. Based on the dynamic mechanical analysis, the highly restricted macromolecular motions upon the addition of a compatibilizer confirmed the enhanced compatibility of TPVs.
Science in Transition Reduced to Practice
Authors: Miedema Frank 
Published: October 2021

AbstractIn the true spirit of Dewey and pragmatism, knowledge, insights and experience have to be translated into interventions and actions. Only when knowledge is ‘reduced to practice’ its social robustness and value will be determined. In light of the conclusions of the previous Chapter, to be able to have more impact and to hold up our promise to society we have to reflect who our science is organized and how it could be improved. From these reflections, several interventions in the practice of research have been proposed. When we, the Science in Transition Team, started to make public our critical accounts of the practice of science, I was ‘friendly advised’ by influential older scientists to first clean up the mess in my own institution, instead of pointing to others and to the system. As a matter of fact, that is what we have been doing at University Medical Centre Utrecht (UMC Utrecht) since 2009. In this chapter I present a brief outline of our actions ‘on the ground’ in UMC Utrecht and some early actions to promote these activities abroad.
Vanishing or non-vanishing rainbow? Reduction formulas of electric dipole moment
Authors: Fujiwara Motoko , Hisano Junji , Toma Takashi 
Published: October 2021

Abstract
In this paper, we derive a simplified formula of electric dipole moments (EDMs) of a fermion. In the Standard Model, it is well-known that non-trivial cancellations between some rainbow-type diagrams induced by W boson exchanges occur in the calculation of the neutron EDM at the two-loop level due to the gauge symmetry. The fermion self-energy and the vertex correction are related through the Ward-Takahashi identity, and this relation causes the exact cancellation of the EDM. We derive EDM formulas for a more general setup by introducing the form factors for the fermion self-energy and the vertex correction so that the derived formulas can be applicable to a larger class of models. We conclude that the non-zero EDM contributions are induced from rainbow-type diagrams with the chirality flipping effects for internal fermions. We also discuss the other possible generalization of the EDM calculation which is applicable to the other classes of models.
Machine learning to guide clinical decision-making in abdominal surgery—a systematic literature review
Authors: Henn Jonas , Buness Andreas , Schmid Matthias , Kalff Jörg C. , Matthaei Hanno 
Published: October 2021

Abstract

Purpose
An indication for surgical therapy includes balancing benefits against risk, which remains a key task in all surgical disciplines. Decisions are oftentimes based on clinical experience while guidelines lack evidence-based background. Various medical fields capitalized the application of machine learning (ML), and preliminary research suggests promising implications in surgeons’ workflow. Hence, we evaluated ML’s contemporary and possible future role in clinical decision-making (CDM) focusing on abdominal surgery.

Methods
Using the PICO framework, relevant keywords and research questions were identified. Following the PRISMA guidelines, a systemic search strategy in the PubMed database was conducted. Results were filtered by distinct criteria and selected articles were manually full text reviewed.

Results
Literature review revealed 4,396 articles, of which 47 matched the search criteria. The mean number of patients included was 55,843. A total of eight distinct ML techniques were evaluated whereas AUROC was applied by most authors for comparing ML predictions vs. conventional CDM routines. Most authors (N = 30/47, 63.8%) stated ML’s superiority in the prediction of benefits and risks of surgery. The identification of highly relevant parameters to be integrated into algorithms allowing a more precise prognosis was emphasized as the main advantage of ML in CDM.

Conclusions
A potential value of ML for surgical decision-making was demonstrated in several scientific articles. However, the low number of publications with only few collaborative studies between surgeons and computer scientists underpins the early phase of this highly promising field. Interdisciplinary research initiatives combining existing clinical datasets and emerging techniques of data processing may likely improve CDM in abdominal surgery in the future.