bluuebunny/crossref_metadata_2025_split huggingface dataset:
Photoluminescence Quenching in Metal Doped Graphitic Carbon Nitride: Possibilities Toward Metal Sensors
Authors: Chauhan Karuna , Banerjee Diptonil , Srivastava Vishnu Prasad , Prabahar AE 
Published: October 2024

AbstractThe present work describes the synthesis of graphitic carbon nitride (GCN) via simple two‐step thermal decomposition of urea at a moderate temperature of 550 °C. The as‐synthesized GCN is further doped with transition metals like nickel, and both the pure and doped GCN are characterized by X‐ray diffraction (XRD), field emission scanning electron microscope (FESEM), X‐ray photoelectron spectroscopy (XPS), and Fourier transformed infrared (FTIR) spectroscopy. XRD shows the perfect phase formation in the pure GCN, which also remains in the doped sample but with much lesser crystallinity. FESEM shows that after doping, the small chips‐like structure of GCN gets transformed to an elongated one. XPS confirms the successful doping by keeping the signature of both nickel 2P1/2 and 2P3/2 oxidation states in the spectra, whereas FTIR gave an idea about different bonding present in the sample. The pure sample, when irradiated with an excitation wavelength of 350 nm, gives an intense peak at 457 nm, which gets considerably quenched in the case of the doped sample. However, a new peak appears in the photoluminescence (PL) spectra of the doped sample at 624 nm. The quenching of PL intensity in the doped sample is assumed to be due to the fact that the dopant‐induced state traps the electron, hindering them from immediate recombination. This quenching of PL intensity generates the possibilities of sensing the presence of different metals and thus taking measurable steps for removing them. The CIE chromaticity diagrams for the doped and undoped samples confirm that the emission color changes from blue to cyan region after the doping.
Ion Conduction Mechanism in Polymer Blend Electrolyte Films
Authors: Kumar Kailash , Sharma Prabhakar , Dhapola Pawan Singh , Pandey Shri Prakash 
Published: October 2024

AbstractThis paper presents the development of the blend polymer solid electrolyte films (BPSE) for potential applications in electrochemical devices. Two host polymers, polyvinyl alcohol (PVA) and polymethyl methacrylate (PMMA), along with the salt KI, are employed to create the solid polymer electrolytes (SPEs). The synthesis involves varying the weight percentage of salt within the SPEs to investigate its impact on the material properties. Conductivity measurements are conducted using AC impedance spectroscopy, unveiling the conductivity behavior of the BPSEs. Additionally, surface morphology is characterized using polarized optical microscopy (POM) at 10 pixel resolution, offering a detailed examination of the film's microstructure. This comprehensive study not only contributes to the understanding of the fundamental properties of BPSEs but also opens avenues for their utilization in various electrochemical applications.
Synthesis of Graphene Oxide by Modified New Hummer Method
Authors: Chawla Kanhaiya , Pooja  , Sharma Sandeep , Lal Nathu , Rathore Bhupendra Singh , Lal Chhagan 
Published: October 2024

AbstractGraphene oxide (GO) has been synthesized by modified new Hummer's method with the help of Graphite flakes with sodium nitrite due to its various applications in physical, chemical, and medical sciences. The structure and morphology of GO are characterized using XRD, FTIR, RAMAN spectroscopy, and SEM. The results confirm that the synthesized material is graphene oxide (GO). The synthesized graphene oxide is used in perovskite solar cell as ETL layer.
Kinetic Investigation of the Emulsion Polymerization of Vinylidene Fluoride
Authors: Hanamirian Burak , Agostini Azzurra , Chaduc Isabelle , Brinati Giulio , Kent Bradley , Storti Giuseppe , Sponchioni Mattia 
Published: October 2024

AbstractPoly(vinylidene fluoride) (PVDF) is among the most produced fluoropolymers, second only to polytetrafluoroethylene. Despite its popularity, the complex microstructural properties achieved during the polymerization are not well documented in the literature. In particular, available models only track the chain length distribution of the polymer, while neglecting the distribution of other important properties, affecting the final behavior of the product. In this work, a 2D kinetic model, evaluating not only the chain length but also the number of terminal double bonds (TDBs) per chain, is developed. The numerical solution of the model is achieved by fractionating the population of polymer chains into classes with a specific number of TDBs and using the method of moments for each class. The model results are compared with experimental evidences for the amount of produced polymer, moles of main chain‐ends, number, and weight average molecular weight as well as full molecular weight distribution. Based on this comparison, kinetic parameters are estimated by optimization using genetic algorithm. The model reliability is finally verified using additional experimental data at different temperatures and amounts of initiator.
Investigating the relationship between moral courage and caregiving behaviours among nurses working in COVID‐19 wards in Iran
Authors: Seyedfatemi Naima , Bahrami Raheleh , Hamidi Sajjad , Hamooleh Marjan Mardani , Khorin Zahra Siahmansour , Abbasi Zahra 
Published: October 2024

AbstractAimTo examine the correlation between moral courage and caregiving behaviour among nurses who are employed in the COVID‐19 ward in Iran.DesignThis study is a descriptive‐correlational and cross‐sectional research conducted in 2021 in the city of Tehran, Iran.MethodsA total of 270 nurses employed in COVID‐19 wards, who had been working in these wards for at least 1 month, were recruited from XXX hospitals and XXX Hospital. Data collection was conducted from September to November 2021. The data collection tools included a demographic information form, the Caring Dimension Inventory (CDI‐25), and the Professional Moral Courage Scale (PMC). The designed questionnaire links were provided to the participants virtually through the Persian platform ‘Pars Line’ and via WhatsApp. Descriptive statistics and inferential statistics were used to examine the relationship between moral courage and care behaviour.ResultsThere was a significant difference in the mean of caring behaviour between the age groups (<30 and >40 years old), and the work experience groups (<5 years and >15 years) (p < 0.05). Ethical values also varied significantly between certain age and experience groups (p < 0.05), but no significant differences were found in ethical behaviour across most ages (30–40 years) and work experience categories (>10 years) (p > 0.05). The level of moral courage among the nurses was higher than the median score of the instrument (87.31 ± 10.37). Among the dimensions of moral courage, the highest score was related to the dimension of ethical factors (17.64 ± 2.64), and the lowest score was related to the dimension of multiple values (17.26 ± 2.78). The level of caring behaviours among the nurses was lower than the median score of the instrument (46.11 ± 10.84). Among the dimensions of caring behaviours, the highest score was related to physical‐technical behaviours (19.22 ± 5.27), and the lowest score was related to professional behaviours (1.35 ± 0.67). Based on the analysis, moral courage had a weak and inverse correlation with caring behaviours among nurses. The higher moral courage does not necessarily result in improved caregiving behaviours, emphasizing the need for further research to explore and address this relationship.PatientNo Patient or Public Contribution.
Vein Visualisation Technology for Peripheral Intravenous Access in Paediatric Patients: A Clinical Decision‐Making Tool
Authors: Weathers Elizabeth , Cazzell Mary , Thompson Julie A. , Grieser Kathy , Caraveo Leticia 
Published: October 2024

ABSTRACTAimThe aim of this study is to develop a clinical decision‐making tool to guide utilisation of vein visualisation technologies and enhance chances of successful peripheral intravenous catheter (PIVC) insertion, using data collected from a vascular access team in a large paediatric medical centre in the United States.DesignQuantitative two‐phase, cluster analysis design.MethodsThe study consisted of the following two phases: (1) a quantitative retrospective chart review to evaluate clinician utilisation and preference for vein visualisation technologies and (2) a quantitative prospective design, including a post‐discharge retrospective chart review, to confirm utilisation of vein visualisation technologies and factors influencing clinician decision‐making.ResultsA total of 16 groups were created based on the cluster analysis and expert clinician input. The results of first‐attempt success analyses identified optimal device recommendations for each of the 16 patient groups. For patients older than 2 years old, the NIR device was more likely to result in first‐attempt success regardless of BMI or access site and the NIR device was most optimal for almost all categories of paediatric patients regardless of BMI or access site. The transilluminator was found to be the most optimal device to use with younger patients (< 2 years old) who are underweight.ConclusionVein visualisation technology is recommended by professional nursing organisations to improve PIV access. Yet, adoption of this useful technology to aid selection of an optimal vein for insertion and visualisation during insertion is limited. This is the first study to develop a clinical decision‐making tool for vein visualisation technology in PIVC insertion.Implications for the Profession and Patient CareVein visualisation technology allows for a rapid, thorough assessment of patients' vasculature to determine an optimal site for PIVC placement beyond what is visible to the naked eye or achievable using traditional methods. The tool was designed to guide healthcare professionals towards successful first attempt PIVC insertions, thereby improving patient outcomes and efficiency of care.Patient or Public ContributionNone.
Sleep Disturbances in Health Professional Students During the COVID‐19 Pandemic: A Concept Analysis
Authors: Chen Pei , Cao Yuhao , Tanglai Wirampa , Zhu Bingqian , Fink Anne M. , Izci‐Balserak Bilgay 
Published: October 2024

ABSTRACTAimThe aim is to delineate the concept of sleep disturbances in health professional students during the COVID‐19 pandemic.DesignA concept analysis was conducted.MethodsA systematic search was conducted for relevant articles published and performed from inception to July 5, 2024. Electronic databases searched included PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase and Web of Science. Rodgers' method of evolutionary concept analysis was used.ResultsA total of 50 pertinent articles were included in our analysis. Utilising inductive thematic analysis, this study identified attributes, antecedents and consequences of sleep disturbances. Important attributes included insomnia, disrupted sleep patterns, altered sleep duration/nocturnal sleep duration and poor sleep quality. Antecedents encompassed factors such as gender, age/grade levels, physical activity, screen time of digital production, mental health issues, COVID‐19‐related stressors, financial strain and academic stress. Consequences included both mental and physical health implications. By addressing sleep disturbances and promoting better sleep health among students, we can enhance their learning and performance, which could translate to improved patient care outcomes. Additionally, understanding and mitigating sleep disturbances can contribute to the development of a more resilient and effective health care workforce, capable of providing high‐quality care even during crises like the COVID‐19 pandemic.Patient or Public ContributionNo patient or public contribution.
Can strategic integration of cultivated pasture legumes into temperate agricultural systems provide stability to honey bee populations and associated industries?
Authors: Wisdom Joanne J. M. , Kidd Daniel R. , Ryan Megan H. , Barbour Liz , Hockey Alistair , Cawthray Gregory R. , Foster Kevin J. 
Published: October 2024

Societal Impact StatementHumans and honey bees have a long history of interaction to yield valued products and services. However, honey bees are under pressure from changes in vegetation, agricultural practices and climate change. We investigate if pasture legumes can be harnessed to support honey bees. We use a diverse set of species that originated from the Mediterranean and western Europe but are now developed as commercial cultivars for the southern Australian livestock industries. We find that pasture legumes show great promise as a means to support honey bees and suggest that further targeted research is warranted.Summary
Globally, humans and honey bees (Apis mellifera) have a long history of interaction and this is now under pressure. In temperate southern Australia, exotic honey bees rely on an unstable native floral resource base, yet a diverse set of exotic pasture legume species are sown as staple rotational or permanent crops. We investigated if these pasture legumes could be strategically used to support honey bee populations for the apiary and horticulture industries in this region.
A literature review on temperate pasture legumes and honey bees was undertaken and integrated with data from an Australian industry case study. Comparisons were made to the widely‐grown red clover (Trifolium pratense) and white clover (T. repens).
We found that many southern Australian pasture legumes could provide significant floral resources as well as enhanced temporal and spatial stability for honey bees due to phenological variability and broad adaptation. Honey bees will likely recognise and be attracted to their flowers and other characteristics are comparable, or potentially superior, to red and white clover, such as floret number per inflorescence, floret length, nectar volume and sucrose‐dominance and pollen protein. The floral resource diversity from pasture legume mixes could aid honey bee health and support pollinator services for adjacent crops.
We conclude that the exotic pasture legumes of temperate Australia show promise for development as a sown floral resource for honey bees. Globally, further investigation is merited to maximise benefits from the integration of a diverse range of pasture legumes into agricultural landscapes.
Selection for domestication favored taxa characterized by fast growth and tolerance of high intraspecific density
Authors: de Casas Rafael Rubio , Martín‐Brull Irene , Milla Ruben , Ocaña‐Calahorro Francisco J. 
Published: October 2024

Societal Impact StatementTo understand why certain plants have been domesticated into crops, we need to recognize that the environmental conditions plants experience in wild populations are totally different from those of agricultural fields. In this study, we investigated whether the characteristics that promote growth and survival in these different environments may have influenced domestication. Our results revealed that ancestral crops were selected because they developed better than other plants in dense single‐species stands, with selection for increased yield likely occurring after domestication. These insights shed light on the origins of agriculture and offer valuable guidance for future crop breeding efforts.Summary

In spite of a large history of research, it is still unclear which functional traits may have mediated plant domestication. Solving this problem requires consideration of the ecological and demographic disparities between natural plant populations and cultivated fields. Since population density tends to be higher in the latter, we hypothesized that traits facilitating growth and survival in dense, monospecific populations might have been relevant for initial domestication.
We investigated whether functional traits that respond to population density varied across three different domestication stages: undomesticated crop wild relatives, natural populations of crop progenitors, and landraces. To do this, we compared traits influencing competition (lodging; growth rate), resource acquisition (plant height; total aerial and root biomass) and yield (fruit number) in three annual legume crops—lentil, grasspea, and vetch—grown without resource limitation at three different densities.
Our results showed clear differences among species, likely reflective of the distinct uses of the crops and their domestication pathways. Nevertheless, undomesticated relatives consistently differed from crop progenitors and landraces, producing smaller, slower‐growing plants that were more prostrate and allocated less biomass to roots. The effect of selection under domestication on these vegetative traits appeared to be largely negligible. Conversely, landraces produced more fruits.
We conclude that early agriculturalists selected for domestication wild legumes that performed well in dense monocultures and were more effective in resource capture. Later domestication and breeding efforts likely had more significant effects on reproductive traits, such as fruit and seed production.
Proteomic Analysis of Fibroblasts Exposed to Resin Composite Release
Authors: Flottes Yohann , Dursun Elisabeth 
Published: October 2024

ABSTRACTObjectiveTo investigate the potential effects of products released by a resin composite on the proteome of human gingival fibroblasts.MethodsFifteen resin composite cylinders of a Bis‐GMA‐based resin composite (Tetric EvoCeram, Ivoclar) were made and placed in a culture medium for 24 h. Then, 30 mL of this medium was placed for 72 h in contact with human gingival fibroblasts and a second control group consisted of cells placed in culture medium only. Afterward, cells were collected, washed, and their proteins extracted. Three two‐dimensional electrophoresis were performed per condition. Image analysis of the gels was carried out to highlight the differential protein spots. These spots were then analyzed by an ESI/qTOF mass spectrometer. Finally, specific databases provided protein identification, their interactions, and the pathways where they are implicated.ResultsDelta2D software allowed the detection of 21 spots of different proteins. The MASCOT identified 28 proteins. Five proteins from four spots were upregulated, 23 proteins from 17 spots were downregulated. The UniProt database showed that all these proteins were involved in cellular architecture, structural modifications and quality control of proteins, cellular homeostasis, and metabolic pathways. The STRING database revealed the interactions between the regulated proteins. The GO enrichment analysis showed that 19 pathways were affected.SignificanceThe products released from the resin composite tested led to changes in the fibroblast proteome. Under the conditions of this study, resin composite released products can cause early adverse effects on cells, but without complete inhibition of their cellular functions.
Deep learning in disease vector image identification
Authors: Bai Shaowen , Shi Liang , Yang Kun 
Published: October 2024

AbstractVector‐borne diseases (VBDs) represent a critical global public health concern, with approximately 80% of the world's population at risk of one or more VBD. Manual disease vector identification is time‐consuming and expert‐dependent, hindering disease control efforts. Deep learning (DL), widely used in image, text, and audio tasks, offers automation potential for disease vector identification. This paper explores the substantial potential of combining DL with disease vector identification. Our aim is to comprehensively summarize the current status of DL in disease vector identification, covering data collection, data preprocessing, model construction, evaluation methods, and applications in identification spanning from species classification to object detection and breeding site identification. We also discuss the challenges and possible prospects for DL in disease vector identification for further research. © 2024 Society of Chemical Industry.
Nano‐pesticide delivery system based on UiO‐66 with pH sensitivity for precise control of Spodoptera frugiperda
Authors: Hou Chaoqun , Wei Nuo , Liang Qianwei , Tan Yifei , Li Xiang , Feng Jianguo 
Published: October 2024

AbstractBACKGROUNDMetal–organic frameworks have the advantages of easy synthesis, high loading capacity and good biocompatibility, making them essential materials for constructing pesticide nano‐delivery systems. In this study, a pH‐responsive nano‐controlled‐release formulation Chl@UiO‐66 was prepared using UiO‐66 as the nano‐scale carrier for adsorbing chlorantraniliprole (Chl).RESULTSThe appearance, pesticide loading, release behaviour, insecticidal activity, long‐term control efficacy and safety of Chl@UiO‐66 for non‐target organisms were extensively evaluated. The results showed that the prepared Chl@UiO‐66 was a regular octahedron with a uniform particle size of 230 nm and pesticide loading of 15.62%. The release of pesticides under alkaline conditions was superior to that under acidic and neutral conditions, which showed pH‐responsive performance. Chl@UiO‐66 had an excellent ability to protect pesticides from ultraviolet degradation. Compared with chlorantraniliprole suspension concentrate, Chl@UiO‐66 had a better control effect against Spodoptera frugiperda and long‐term control efficacy. The prepared nano‐controlled‐release formulation had low toxicity to zebrafish, earthworms and human BEAS‐2B cells.CONCLUSIONChl@UiO‐66 is a new pesticide formulation with high efficacy and low toxicity that provides a smart controlled‐release solution. © 2024 Society of Chemical Industry.
FG‐UNet: fine‐grained feature‐guided UNet for segmentation of weeds and crops in UAV images
Authors: Lin Jianwu , Zhang Xin , Qin Yongbin , Yang Shengxian , Wen Xingtian , Cernava Tomislav , Chen Xiaoyulong 
Published: October 2024

AbstractBACKGROUNDSemantic segmentation of weed and crop images is a key component and prerequisite for automated weed management. For weeds in unmanned aerial vehicle (UAV) images, which are usually characterized by small size and easily confused with crops at early growth stages, existing semantic segmentation models have difficulties to extract sufficiently fine features. This leads to their limited performance in weed and crop segmentation of UAV images.RESULTSWe proposed a fine‐grained feature‐guided UNet, named FG‐UNet, for weed and crop segmentation in UAV images. Specifically, there are two branches in FG‐UNet, namely the fine‐grained feature branch and the UNet branch. In the fine‐grained feature branch, a fine feature‐aware (FFA) module was designed to mine fine features in order to enhance the model's ability to segment small objects. In the UNet branch, we used an encoder–decoder structure to realize high‐level semantic feature extraction in images. In addition, a contextual feature fusion (CFF) module was designed for the fusion of the fine features and high‐level semantic features, thus enhancing the feature discrimination capability of the model. The experimental results showed that our proposed FG‐UNet, achieved state‐of‐the‐art performance compared to other semantic segmentation models, with mean intersection over union (MIOU) and mean pixel accuracy (MPA) of 88.06% and 92.37%, respectively.CONCLUSIONThe proposed method in this study lays a solid foundation for accurate detection and intelligent management of weeds. It will have a positive impact on the development of smart agriculture. © 2024 Society of Chemical Industry.