bluuebunny/crossref_metadata_2025_split huggingface dataset:
From postconsumer cotton towels to new cotton textile fibers
Authors: Schlapp‐Hackl Inge , Rissanen Marja , Ojha Krishna , Sawada Daisuke , Gorniak Kasia , Onkinen Elina , Niinimäki Kirsi , Sixta Herbert 
Published: April 2024

AbstractThe chemical recycling of cotton towels via the Ioncell® technique is demonstrated. Cotton is the most common natural fiber. The season's value jumped 31% to 54.3 billion US$ in 2020/2021, and annually the average value in quota‐free periods accounts to 46.3 billion US$. Consequently, enormous amounts of cotton wastes are emerging. Especially, European countries are forced by the new legislation of the union to develop new recycling strategies. Due to uncountable cotton applications, various types of garments exist, which require different recycling strategies. The recycling of an additional cotton waste side stream of Lindström Oy white pre and dyed and white postconsumer cotton roll towels was pursued. The mechanical properties of the fibers and yarns have been evaluated. Thereby, the following elongations and tenacities of conditioned fibers produced at DR11 have been achieved: 10.4%/59.5 cN/tex for preconsumer and 10.6%/60.4 cN/tex for postconsumer white cotton, 10.4%/60.0 cN/tex for postconsumer blue cotton. The achieved elongations at break are close to values reported in literature (7%–14%), however, the tenacities exceed reported values (40–58 cN/tex). Highly oriented fibers of high quality have been produced and with regards to the mechanical properties, a technique to perform fiber‐to‐fiber upcycling is illustrated.
Enhancing the piezoelectric performance of composite PVDF flexible films through optimizing β phase content, investigating additive effects, step‐wise polarization, and thermal pressing time for energy harvesting applications
Authors: Oflaz Kamil , Özaytekin İlkay , Sadasivuni Kishor Kumar 
Published: April 2024

AbstractPolyvinylidene fluoride (PVDF), known for its piezoelectric versatility, emerges as a key contender for advancing efficient and sustainable energy harvesting in nanogenerators. This study explores the potential enhancement of piezoelectric properties in flexible PVDF polymers, employing a comprehensive approach through the solution casting method. The investigation integrates diverse additives, thermal treatments, and polarization methods to optimize performance, focusing on the impact of the β phase transition on electrical voltage generation. Utilizing the Taguchi experimental design, the study identifies optimal conditions for the composite PVDF film (OPT‐PVDF) through FT‐IR, XRD, and DSC analyses, with output voltage measurements confirming superior performance compared to pure PVDF (P‐PVDF). Specifically, BN‐doped PVDF films, with an 80% β phase content, achieve an impressive 6.48 V output voltage. This research underscores PVDF's potential for energy harvesting, emphasizing the pivotal role of optimizing β phase content, additive strategies, and the effects of polarization and thermal treatments. The study further evaluates the effect and necessity of subsequent thermal treatment and step‐wise polarization effects on the composite PVDF film material. The findings indicate that BN‐doped composite PVDF films, produced under optimal conditions, exhibit advanced piezoelectric properties.
Multiscale mechanics of polydimethylsiloxane: A comparison of meso‐ and micro‐cyclic deformation behavior
Authors: Lou Lihua , Bacca Nicole , Ma Marshall S. , Nautiyal Pranjal , Bifano Thomas G. , Agarwal Arvind 
Published: April 2024

AbstractDespite plenty of static and dynamic mechanical measurements and modeling for bulk polydimethylsiloxane (PDMS) specimens, a notable gap exists in comprehensively understanding the dynamic mechanics under large cycle, low strain conditions, especially for microscale samples. This study integrates tensile testing and nanoindentation techniques to compare dynamic mechanical response for bulk PDMS samples and μ‐pillars. The results from cyclic tensile testing, which involved up to 10,000 cycles at a strain range of 10%–20%, indicate a stabilization of energy dissipation rate after the initial 25 cycles. This attributes to stress relaxation and strain hardening, validating by rapid dual‐phase exponential decay in maximum stress, coupled with an incremental increase in elastic modulus. In comparison to tensile testing, μ‐pillars exhibited a 0.82% reduction in stiffness, stabilizing ~600th cycle. Concurrently, there was an approximately twofold increase in approaching distance during the initial 120 cycles, and an approximately fourfold increase in dissipated energy over the first 80 cycles, before reaching a plateau. This lagging hysteresis effect attributes to the distribution of the resultant force, including top tension, bottom compression, and base tilt. Overall, this study illuminates temporal mechanical deformations in PDMS under two application scenarios, enhancing our understanding of PDMS mechanical behavior.
Cellulose nanowhiskers‐reinforced polymer nanofibers for photoresponsive authentication
Authors: Gouda Mohamed , Khalaf Mai M. , Abou Taleb Manal F. , Abd El‐Lateef Hany M. 
Published: April 2024

AbstractThe objective of the current study is to develop novel photochromic polyurethane (PUR) nanofibrous films supported with cellulose nanowhiskers (CNW) and immobilized with nanoparticles of alkaline‐earth doped aluminate (NAEA) using the highly efficient and low‐cost solution blowing spinning (SBS) technique. CNW revealed a crystal diameter of 4–8 nm, and a crystal length of 55–105 nm. The solution blown spun nanofibers exhibited diameters of 250–450 nm. In order to prepare a transparent film, CNW and NAEA must be dispersed efficiently in the PUR composite. When supported with CNW, the efficiency of PUR nanofibrous films was strengthened. Cellulose paper sheets were coated with the colorless NAEA/CNW@PUR films to emit a green light at 518 nm upon excitation at 365 nm as proved by photoluminescence spectra. The prepared nanofibrous films exhibited efficient optical photochromic characteristics for potential security encoding applications. The nanofibers‐coated papers showed high photochromic reversibility without fatigue. The current approach can be reported as an efficient technology for authentication of commercial products.
Optimizing the preparation parameters of eco‐friendly flexible polyurethane foams derived from a corn‐based bio‐polyol
Authors: Park Jun Hak , Jo Kyung Il , Kim Il Jin , Kwon Taehoon , Yu Seunggun , Ko Jae Wang , Lee Jin Hong 
Published: April 2024

AbstractCorn‐based bio‐polyol is employed as an alternative for petroleum‐based polyol to prepare an eco‐friendly polyurethane (PU) foam via a one‐shot method. By varying ratio of gelling catalyst, blowing catalyst, and surfactant during the preparation process, the compression performance, cell morphology, and thermal stability of the PU foam are analyzed. The results obtained indicate that an increase in surfactant content yielded improved foam stability, whereas increased amounts of blowing and gelling catalysts resulted in enhanced compression performance. An optimized foaming process is determined with an NCO/OH ratio of 1.2, 0.2 parts per hundred polyols (pphp) of gelling catalyst, 0.1 pphp of blowing catalyst, and 0.1 pphp of surfactant. Under these specific conditions, the PU foam exhibits a uniform cell structure, exceptional compression performance, and good thermal stability, comparable to those of a reference foam derived from petroleum‐based polyol.
Improving performance of aerosol jet printing using machine learning‐driven optimization
Authors: Pandey Prashantkumar , Ziesche Steffen , Meghanathi Gauranggiri 
Published: April 2024

AbstractAerosol jet printing is a promising technology for printing functional materials on a variety of substrates with high precision and resolution. This technology has the potential to revolutionize the manufacturing industry by providing a low‐cost, high‐resolution printing technique that can be used to produce additively printed electronics, sensors, and energy devices. However, the optimization of this process has traditionally relied on time‐consuming trial‐and‐error methods, hampering its efficiency and scalability. Machine learning (ML) models have the potential to overcome these challenges and improve the quality, speed, and efficiency of the printing process. In this paper, we propose an approach that leverages ML algorithms to streamline and enhance the aerosol jet printing optimization process. Our methodology involves data collection through systematic experimentation with various parameter settings. This data set serves as the foundation for training different ML model capable of predicting printed line characteristics and optimal printing process parameter. We validate our approach by performing experiments on different inks, and we compare the results of our ML‐based optimization approach to those obtained using traditional trial‐and‐error methods. The results demonstrate that our approach offers significantly higher accuracy and efficiency. To enhance our approach's accessibility and ease of use, we incorporate AutoML techniques which automates the process of selecting the most suitable ML algorithms and hyperparameters, reducing the burden of manual configuration. Furthermore, we introduce a user‐friendly web‐based interface that facilitates the entire ML pipeline, from data preprocessing to prediction and batch processing. This interface empowers users to efficiently manage and manipulate their data, select appropriate ML algorithms, and execute predictions, ultimately improving accuracy and model performance.
A machine learning approach to study plant functional trait divergence
Authors: Majumder Sambadi , Mason Chase M. 
Published: April 2024

AbstractPremisePlant functional traits are often used to describe the spectra of ecological strategies used by different species. Here, we demonstrate a machine learning approach for identifying the traits that contribute most to interspecific phenotypic divergence in a multivariate trait space.MethodsDescriptive and predictive machine learning approaches were applied to trait data for the genus Helianthus, including random forest and gradient boosting machine classifiers and recursive feature elimination. These approaches were applied at the genus level as well as within each of the three major clades within the genus to examine the variability in the major axes of trait divergence in three independent species radiations.ResultsMachine learning models were able to predict species identity from functional traits with high accuracy, and differences in functional trait importance were observed between the genus and clade levels indicating different axes of phenotypic divergence.ConclusionsApplying machine learning approaches to identify divergent traits can provide insights into the predictability or repeatability of evolution through the comparison of parallel diversifications of clades within a genus. These approaches can be implemented in a range of contexts across basic and applied plant science from interspecific divergence to intraspecific variation across time, space, and environmental conditions.
Persistence of changed attitudes among students in an integrated anatomy curriculum
Authors: Rosenberg Martina J. , Hartley Rebecca S. 
Published: April 2024

AbstractMany medical schools in the United States have integrated anatomy into an organ‐based preclinical curriculum with some schools using anatomy as the cornerstone of their reorganization efforts. Curricular change could affect one or more of the three domains of learning, with the cognitive domain often scrutinized exclusively. A previous study reported the impact of anatomy integration on the affective domain, specifically, student attitudes toward learning anatomy. This mixed methods follow‐up study asked if the observed attitudinal changes and lack of effect on student knowledge and confidence persisted using knowledge and confidence surveys, focus groups, internal and national surveys, and United States Medical Licensing Examination® performance metrics. Results evidenced the persistence of specific attitudinal differences between cohorts with blocked versus integrated anatomy with no apparent short‐ or long‐term differences in anatomy learning or confidence in this learning. Altered attitudes included lower value placed on working in teams and reflective practices, and less recognition of anatomy's contribution (or less contribution of anatomy learning) to professional identity formation. These attitudinal changes could result in a weaker foundation for building collaborative skills throughout the medical curriculum. A decreased sense of student engagement also followed curricular change, as assessed by data from the American Association of Medical Colleges Year 2 Questionnaire. Overall, results emphasized the necessity of anticipating, monitoring, and if necessary, addressing changes in the affective domain when undertaking curricular change.
To persist or not? Examining the relations between parental education, self‐regulation, school engagement and persistence in post‐compulsory education
Authors: Katsantonis Ioannis , Gibbons Ryan Alberto , Symonds Jennifer E. , Costello Niall 
Published: April 2024

AbstractThere are few longitudinal studies of adolescent students’ choice to persist in post‐compulsory education. Hence, the present study introduces a longitudinal model that describes the interplay between sociological and psychological explanations of adolescents’ choice to persist in post‐compulsory education in the UK. Data on parental education, early childhood self‐regulation (age 5), sustained school engagement (ages 7, 11, 14) and persistence in education after the end of compulsory schooling (age 17) were utilised. The sample comprised 8333 (51.1% females, 89.5% white) children from the Millennium Cohort Study. Statistical analyses included state–trait modelling, longitudinal mediation and multigroup moderation. A trait–state–occasion model was run to disentangle the trait from state variance in school engagement. Afterwards, two hypotheses were formulated, namely the ‘instilment’ and the ‘differential’. The ‘instilment’ hypothesis involved a longitudinal predictive model, whereby parental education predicted early childhood self‐regulation which, in turn, predicted sustained school engagement which predicted students’ choice to persist. The ‘differential’ hypothesis examined whether higher vs. lower parental education changed the nature of the predictive relations between self‐regulation, sustained school engagement and persistence. The results were in favour of an ‘instilment’ hypothesis, whereby higher parental education was translated to higher levels of early self‐regulation which predicted higher sustained engagement, which, in turn, predicted greater probability of persisting in post‐compulsory education. The findings suggest a pathway from early childhood experiences to educational outcomes via the development of a trait of engaging with school.
Beta spending function based on conditional power in group sequential design
Authors: Ni Senmiao , Zhong Zihang , Jiang Zhiwei , Zhao Yang , Wu Jingwei , Yu Hao , Bai Jianling 
Published: April 2024

AbstractConditional power (CP) serves as a widely utilized approach for futility monitoring in group sequential designs. However, adopting the CP methods may lead to inadequate control of the type II error rate at the desired level. In this study, we introduce a flexible beta spending function tailored to regulate the type II error rate while employing CP based on a predetermined standardized effect size for futility monitoring (a so‐called CP‐beta spending function). This function delineates the expenditure of type II error rate across the entirety of the trial. Unlike other existing beta spending functions, the CP‐beta spending function seamlessly incorporates beta spending concept into the CP framework, facilitating precise stagewise control of the type II error rate during futility monitoring. In addition, the stopping boundaries derived from the CP‐beta spending function can be calculated via integration akin to other traditional beta spending function methods. Furthermore, the proposed CP‐beta spending function accommodates various thresholds on the CP‐scale at different stages of the trial, ensuring its adaptability across different information time scenarios. These attributes render the CP‐beta spending function competitive among other forms of beta spending functions, making it applicable to any trials in group sequential designs with straightforward implementation. Both simulation study and example from an acute ischemic stroke trial demonstrate that the proposed method accurately captures expected power, even when the initially determined sample size does not consider futility stopping, and exhibits a good performance in maintaining overall type I error rates for evident futility.
Proteomic analysis reveals that the co‐ordination of cytosolic and mitochondrial pathways is beneficial for sabinene biosynthesis in engineered Saccharomyces cerevisiae
Authors: Hou Rui , Shan Mengying , Liu Xinxin , Yao Mingdong , Yang Kaiguang , Wang Ying , Sui Zhigang , Liang Zhen , Zhang Yukui , Zhang Lihua 
Published: April 2024

AbstractReconstruction and optimization of biosynthetic pathways can help to overproduce target chemicals in microbial cell factories based on genetic engineering. However, the perturbation of biosynthetic pathways on cellular metabolism is not well investigated and profiling the engineered microbes remains challenging. The rapid development of omics tools has the potential to characterize the engineered microbial cell factory. Here, we performed label‐free quantitative proteomic analysis and metabolomic analysis of engineered sabinene overproducing Saccharomyces cerevisiae strains. Combined metabolic analysis andproteomic analysis of targeted mevalonate (MVA) pathway showed that co‐ordination of cytosolic and mitochondrial pathways had balanced metabolism, and genome integration of biosynthetic genes had higher sabinene production with less MVA enzymes. Furthermore, comparative proteomic analysis showed that compartmentalized mitochondria pathway had perturbation on central cellular metabolism. This study provided an omics analysis example for characterizing engineered cell factory, which can guide future regulation of the cellular metabolism and maintaining optimal protein expression levels for the synthesis of target products.
Transcriptomic analysis provides an insight into the function of CmGH9B3, a key gene of β‐1, 4‐glucanase, during the graft union healing of oriental melon scion grafted onto squash rootstock
Authors: Zhu Yulei , Hu Shengwei , Min Jiahuan , Zhao Yingtong , Yu Hanqi , Irfan Muhammad , Xu Chuanqiang 
Published: April 2024

AbstractThe melon (Cucumis melo L.) is a globally cherished and economically significant crop. The grafting technique has been widely used in the vegetative propagation of melon to promote environmental tolerance and disease resistance. However, mechanisms governing graft healing and potential incompatibilities in melons following the grafting process remain unknown. To uncover the molecular mechanism of healing of grafted melon seedlings, melon wild type (Control) and TRV‐CmGH9B3 lines were obtained and grafted onto the squash rootstocks (C. moschata). Anatomical differences indicated that the healing process of the TRV‐CmGH9B3 plants was slower than that of the control. A total of 335 significantly differentially expressed genes (DEGs) were detected between two transcriptomes. Most of these DEGs were down‐regulated in TRV‐CmGH9B3 grafted seedlings. GO and KEGG analysis showed that many metabolic, physiological, and hormonal responses were involved in graft healing, including metabolic processes, plant hormone signaling, plant MAPK pathway, and sucrose starch pathway. During the healing process of TRV‐CmGH9B3 grafted seedlings, gene synthesis related to hormone signal transduction (auxin, cytokinin, gibberellin, brassinolide) was delayed. At the same time, it was found that most of the DEGs related to the sucrose pathway were down‐regulated in TRV‐CmGH9B3 grafted seedlings. The results showed that sugar was also involved in the healing process of melon grafted onto squash. These results deepened our understanding of the molecular mechanism of GH9B3, a key gene of β‐1, 4‐glucanase. It also provided a reference for elucidating the gene mechanism and function analysis of CmGH9B3 in the process of graft union healing.
Atomically precise metal nanoclusters for energy conversion
Authors: Seong Hoeun , Lee Dongil 
Published: April 2024

AbstractAtomically precise metal nanoclusters (NCs) have emerged as a new frontier in electrocatalysis, enabling the study of electrocatalytic reactions on well‐defined stable surfaces and rational electrocatalyst design based on atomic‐level tailoring. In this review, we focus on the recent applications of these NCs to energy conversion reactions, including those involved in water splitting (hydrogen and oxygen evolution reactions), fuel cell operation (oxygen reduction and hydrogen oxidation reactions), and electrochemical CO2 reduction. Emblematic examples are used to highlight the roles of different NC parts, for example, core metal and surrounding ligands, and the significance of the electrode substrate. Finally, we discuss the perspectives of the future development and implementation of NC‐based energy conversion systems.
A double‐edged sword: The complex interplay between engineered nanoparticles and platelets
Authors: Asaad Yathreb , Nemcovsky‐Amar Danielle , Sznitman Josué , Mangin Pierre H. , Korin Netanel 
Published: April 2024

AbstractNanoparticles (NP) play a crucial role in nanomedicine, serving as carriers for localized therapeutics to allow for precise drug delivery to specific disease sites and conditions. When injected systemically, NP can directly interact with various blood cell types, most critically with circulating platelets. Hence, the potential activation/inhibition of platelets following NP exposure must be evaluated a priori due to possible debilitating outcomes. In recent years, various studies have helped resolve the physicochemical parameters that influence platelet‐NP interactions, and either emphasize nanoparticles' therapeutic role such as to augment hemostasis or to inhibit thrombus formation, or conversely map their potential undesired side effects upon injection. In the present review, we discuss some of the main effects of several key NP types including polymeric, ceramic, silica, dendrimers and metallic NPs on platelets, with a focus on the physicochemical parameters that can dictate these effects and modulate the therapeutic potential of the NP. Despite the scientific and clinical significance of understanding Platelet‐NP interactions, there is a significant knowledge gap in the field and a critical need for further investigation. Moreover, improved guidelines and research methodologies need to be developed and implemented. Our outlook includes the use of biomimetic in vitro models to investigate these complex interactions under both healthy physiological and disease conditions.