bluuebunny/crossref_metadata_2025_split huggingface dataset:
A qualitative exploration of professionals’ perspectives on the implementation of reablement intervention programs in community care
Authors: Mouchaers Ines , Buma Lise E. , Verbeek Hilde , Zwakhalen Sandra , van Haastregt Jolanda C. M. , Vlaeyen Ellen , Goderis Geert , Metzelthin Silke F. 
Published: May 2024

AbstractReablement is considered a complex intervention due to its multicomponent, person-centered, holistic approach promoting older adults’ active participation in daily activities. It is important to consider the unique context in which complex interventions are implemented, as contextual factors may interact and influence implementation outcomes. As part of the European TRANS-SENIOR project, this qualitative study aimed to gain insight into professionals’ experiences with reablement implementation in Dutch community care. Using the Consolidated Framework for Implementation Research, four focus groups were conducted comprising 32 professionals. Two groups were formed: one at operational level, including therapists, nursing staff, social workers, and domestic support; and one at organizational/strategic level, including project leaders, managers, directors, municipality representatives and health insurers. Participating care organizations had at least 6 months of experience with deploying and implementing reablement. Findings reflected three themes: (1) strength of interdisciplinary collaboration; highlighting significance of sharing goals and beliefs, (2) integrating the reablement philosophy into the organization; underscoring managements role in fostering support across all organizational layers, and (3) achieving a culture change in the healthcare system; emphasizing current funding models impeding value-based care tailored to the individual’s goals and needs. The results offer valuable insights for implementation of complex interventions, like reablement.
Disparities in quality of life among patients with breast cancer based on surgical methods: a cross-sectional prospective study
Authors: Wang Yi , He Yibo , Wu Shiyan , Xie Shangnao 
Published: May 2024

AbstractTo determine the impact of breast conservation on quality of life and identify treatment-related and other demographic factors associated with post-breast cancer treatment quality of life. A prospective study was conducted on 392 women who underwent breast cancer surgery at Hangzhou Cancer Hospital from January 1, 2013, to December 31, 2022. Operable breast cancer patients who had completed all treatments except endocrine therapy were included. Patients with tumor recurrence/metastasis, bilateral or male breast cancer, and other primary malignancies were excluded. After enrollment, patients were asked to complete the BREAST-Q scale, and their pathological and medical records were reviewed. Analysis of variance was used to compare the quality of life scores among the groups. Univariate and multivariate linear regression analyses were performed to identify independent factors associated with quality of life scores in different domains. Participants completed the BREAST-Q scale at a median of 4.6 years after surgery. Quality of life scores varied based on the therapeutic strategy. Breast conservation has significant advantages over mastectomy in terms of breast satisfaction, psychosocial, and sexual well-being. Compared to oncoplastic breast-conserving surgery, mastectomy was independently associated with decreased breast satisfaction, psychosocial, and sexual well-being, while conventional breast-conserving surgery showed comparable outcomes to oncoplastic breast-conserving surgery in terms of these factors. Breast conservation leads to an improvement in quality of life compared to mastectomy. Oncoplastic breast-conserving surgery does not lead to a decrease in quality of life compared to conventional breast-conserving surgery and offers better outcomes compared to mastectomy.
Balancing the books of nature by accounting for ecosystem condition following ecological restoration
Authors: Parkhurst Tina , Standish Rachel J. , Prober Suzanne M. , Kobryn Halina , Vardon Michael 
Published: May 2024

AbstractDemand for ecological restoration of Earth’s degraded ecosystems has increased significantly since the adoption of The Kunming-Montreal Global Biodiversity Framework in December 2022, with target 2 aiming to ensure that at least 30% of degraded ecosystems are under effective restoration by 2030. More recently, in December 2023, the Australian Parliament introduced the Nature Repair Act, which establishes a framework for the world’s first legislated, national, voluntary biodiversity market. How can the effectiveness of these ambitious targets be measured? Natural Capital Accounting (NCA) provides a framework to measure changes in ecosystem condition that is applicable across ecosystems and potentially catalogue effects of restoration interventions to drive investment, improvement to practice, and ultimately, to better protect the Earth's ecosystems. However, the framework has not been tested in this context. In this progressive approach, we populated the leading global NCA framework with ecological data to quantify changes in ecosystem condition after restoration. In principle, NCA is fit for purpose, however, methodological refinements and ecological expertise are needed to unlock its full potential. These tweaks will facilitate adoption and standardisation of reporting as efforts ramp up to meet ambitious global restoration targets.
Design of adaptive hybrid MPPT controllers with universal input voltage DC–DC converter for RES’s
Authors: Rafikiran Shaik. , Alsaif Faisal 
Published: May 2024

AbstractAt present, conventional energy production is absent because of the more hazardous gases released into the environment, the high effect on human health, more cost required for maintenance, plus less usefulness for highly populated areas. So, the Renewable Energy Sources are more focused for the present automotive industry application. In this work, the Proton Exchange Membrane Fuel Stack is considered for analyzing the proposed DC–DC converter circuit. The advantages of this fuel stack are high energy density, fast functioning nature, more robustness, and more usefulness for the various water membrane conditions of the fuel stack. However, the disadvantages of the fuel stack are excessive current generation, plus more current conduction losses. So, the wide voltage supply single switch power converter is introduced in this work for optimizing the current production of the fuel stack network. The merits of this converter circuit are high stability, good reliability, low voltage appearing across the switches, plus a uniform power supply. Here, the converter switching pulses are obtained by proposing the Modified Continuous Step Change Adaptive Fuzzy Logic with Grey Wolf Optimization hybrid controller. This controller provides high maximum power extraction efficiency from the fuel stack which is equal to 99.421%. Also, this controller's Maximum Power Point Tracking time is 0.0285 s.
Efficacy of non-pharmacological interventions for individuals with amyotrophic lateral sclerosis: systematic review and network meta-analysis of randomized control trials
Authors: Li Zhao , Kang Hyunsik 
Published: May 2024

AbstractThis network meta-analysis (NMA) aimed to compare the efficacy of five non-pharmacological interventions, including exercise intervention (EI), nutritional intervention (NI), respiratory intervention (RI), psychological intervention (PSI), and integrated physical intervention (IPI), on functional status, quality of life, muscle strength, pulmonary function, and safety in patients with amyotrophic lateral sclerosis (ALS). We searched nine databases, PubMed, Cochrane, Embase, Scopus, Web of Science, CNKI, CBM, WFPD, and CSTJ, for randomized controlled trials of ALS patients. The primary outcome was the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) score. Secondary outcomes were the McGill Quality of Life Questionnaire (McGill-QoL), Medical Research Council (MRC)-sum score, Forced Vital Capacity (FVC), and Fatigue Severity Scale (FSS) score. This NMA was conducted using random-effect models to calculate the standard mean difference (SMD) and 95% confidence interval (CI). All types of supplemental interventions had some benefit for patients with ALS. EI had a beneficial effect on the ALSFRS-R score (SMD: 1.01; 95% CI 0.50–1.51), FVC (SMD: 0.78; 95% CI 0.02–1.55), McGill-QoL (SMD: 0.71 95% CI 0.33–1.08), and MRC (SMD: 1.11; 95% CI 0.08–2.14). RI had a beneficial effect on the ALSFRS-R score (SMD: 0.83 95% CI 0.12–1.55). IPI had a beneficial effect on the ALSFRS-R score (SMD: 0.65 95% CI 0.06–1.24). NI had a beneficial effect on the McGill-QoL (SMD: 0.63 95% CI 0.02–1.23). The current study findings support a multimodal intervention strategy with an emphasis on EI for slowing disease progression in patients with ALS.
Antiepileptic drug-loaded and multifunctional iron oxide@silica@gelatin nanoparticles for acid-triggered drug delivery
Authors: Ghane Nazanin , Khalili Shahla , Khorasani Saied Nouri , Das Oisik , Ramakrishna Seeram , Neisiany Rasoul Esmaeely 
Published: May 2024

AbstractThe current study developed an innovative design for the production of smart multifunctional core-double shell superparamagnetic nanoparticles (NPs) with a focus on the development of a pH-responsive drug delivery system tailored for the controlled release of Phenytoin, accompanied by real-time monitoring capabilities. In this regard, the ultra-small superparamagnetic iron oxide@silica NPs (IO@Si MNPs) were synthesized and then coated with a layer of gelatin containing Phenytoin as an antiepileptic drug. The precise saturation magnetization value for the resultant NPs was established at 26 emu g-1. The polymeric shell showed a pH-sensitive behavior with the capacity to regulate the release of encapsulated drug under neutral pH conditions, simultaneously, releasing more amount of the drug in a simulated tumorous-epileptic acidic condition. The NPs showed an average size of 41.04 nm, which is in the desired size range facilitating entry through the blood–brain barrier. The values of drug loading and encapsulation efficiency were determined to be 2.01 and 10.05%, respectively. Moreover, kinetic studies revealed a Fickian diffusion process of Phenytoin release, and diffusional exponent values based on the Korsmeyer-Peppas equation were achieved at pH 7.4 and pH 6.3. The synthesized NPs did not show any cytotoxicity. Consequently, this new design offers a faster release of PHT at the site of a tumor in response to a change in pH, which is essential to prevent epileptic attacks.
miR-709 exerts an angiogenic effect through a FGF2 upregulation induced by a GSK3B downregulation
Authors: Ueno Koji , Kurazumi Hiroshi , Suzuki Ryo , Yanagihara Masashi , Mizoguchi Takahiro , Harada Takasuke , Morikage Noriyasu , Hamano Kimikazu 
Published: May 2024

AbstractThe aim of this study was to identify angiogenic microRNAs (miRNAs) that could be used in the treatment of hindlimb ischemic tissues. miRNAs contained in extracellular vesicles (EVs) deriving from the plasma were analyzed in C57BL/6 mice, which have ischemia tolerance, and in BALB/c mice without ischemia tolerance as part of a hindlimb ischemia model; as a result 43 angiogenic miRNA candidates were identified. An aortic ring assay was employed by using femoral arteries isolated from BALC/c mice and EVs containing miRNA; as a result, the angiogenic miRNA candidates were limited to 14. The blood flow recovery was assessed after injecting EVs containing miRNA into BALB/c mice with hindlimb ischemia, and miR-709 was identified as a promising angiogenic miRNA. miR-709-encapsulating EVs were found to increase the expression levels of the fibroblast growth factor 2 (FGF2) mRNA in the thigh tissues of hindlimb ischemia model BALB/c mice. miR-709 was also found to bind to the 3′UTR of glycogen synthase kinase 3 beta (GSK3B) in three places. GSK3B-knockdown human artery-derived endothelial cells were found to express high levels of FGF2, and were characterized by increased cell proliferation. These findings indicate that miR-709 induces an upregulation of FGF2 through the downregulation of GSK3B.
Contrast-enhanced ultrasound for differentiating benign from malignant focal solid renal lesions in pediatric patients
Authors: Fu Yusi , Zhong Jia , Tan Yan , Zheng Taiqing , Liu Minghui , Wang Guotao 
Published: May 2024

AbstractThe contrast-enhanced ultrasound (CEUS) has been mainly applied to adults to differentiate benign and malignant renal lesions, however, the characteristics of CEUS in pediatric has not been as well studied as in adults. In the present work, the eligible pediatric patients who underwent renal CEUS between March 2016 and February 2023 were retrospectively analyzed. It included 20 lesions (median diameter, 8.4 cm; range, 1.8–18.0 cm) from 20 patients (median age, 28.0 months; range, 3.0–212.0 months; 9 boys) in malignant group and 5 lesions (median diameter, 3.8 cm; range, 1.3–7.5 cm) from 5 patients (median age, 25.0 months; range, 0.7–216.0 months; 2 boys) in benign group. The diagnostic performance was assessed. Nonparametric and Chi-square tests were performed. With hyperenhancement plus wash-out, CEUS showed a sensitivity of 95.0% [95% confidence interval (CI): 75.1%, 99.9%], a specificity of 80.0% (CI: 28.4%, 99.5%), a positive predictive value of 95.0% (CI: 75.1%, 99.9%) and a negative predictive value of 80.0% (CI: 28.4%, 99.5%). It suggested that CEUS is a valuable technique for identifying between malignant and benign renal lesions in children.
Enhancing drug and cell line representations via contrastive learning for improved anti-cancer drug prioritization
Authors: Lawrence Patrick J. , Burns Benjamin , Ning Xia 
Published: May 2024

AbstractDue to cancer’s complex nature and variable response to therapy, precision oncology informed by omics sequence analysis has become the current standard of care. However, the amount of data produced for each patient makes it difficult to quickly identify the best treatment regimen. Moreover, limited data availability has hindered computational methods’ abilities to learn patterns associated with effective drug-cell line pairs. In this work, we propose the use of contrastive learning to improve learned drug and cell line representations by preserving relationship structures associated with drug mechanisms of action and cell line cancer types. In addition to achieving enhanced performance relative to a state-of-the-art method, we find that classifiers using our learned representations exhibit a more balanced reliance on drug- and cell line-derived features when making predictions. This facilitates more personalized drug prioritizations that are informed by signals related to drug resistance.
Daily singing of adult songbirds functions to maintain song performance independently of auditory feedback and age
Authors: Mizuguchi Daisuke , Sánchez-Valpuesta Miguel , Kim Yunbok , dos Santos Ednei B. , Kang HiJee , Mori Chihiro , Wada Kazuhiro , Kojima Satoshi 
Published: May 2024

AbstractMany songbirds learn to produce songs through vocal practice in early life and continue to sing daily throughout their lifetime. While it is well-known that adult songbirds sing as part of their mating rituals, the functions of singing behavior outside of reproductive contexts remain unclear. Here, we investigated this issue in adult male zebra finches by suppressing their daily singing for two weeks and examining the effects on song performance. We found that singing suppression decreased the pitch, amplitude, and duration of songs, and that those song features substantially recovered through subsequent free singing. These reversible song changes were not dependent on auditory feedback or the age of the birds, contrasting with the adult song plasticity that has been reported previously. These results demonstrate that adult song structure is not stable without daily singing, and suggest that adult songbirds maintain song performance by preventing song changes through physical act of daily singing throughout their life. Such daily singing likely functions as vocal training to maintain the song production system in optimal conditions for song performance in reproductive contexts, similar to how human singers and athletes practice daily to maintain their performance.
Tracing the origins of Plasmodium vivax resurgence after malaria elimination on Aneityum Island in Vanuatu
Authors: Sekine Sho , Chan Chim W. , Kalkoa Morris , Yamar Sam , Iata Harry , Taleo George , KC Achyut , Kagaya Wataru , Kido Yasutoshi , Kaneko Akira 
Published: May 2024

Abstract
Background
Five years after successful malaria elimination, Aneityum Island in Vanuatu experienced an outbreak of Plasmodium vivax of unknown origin in 2002. Epidemiological investigations revealed several potential sources of P. vivax. We aimed to identify the genetic origin of P. vivax responsible for the resurgence.

Methods
Five P. vivax microsatellite markers were genotyped using DNA extracted from archived blood samples. A total of 69 samples from four P. vivax populations was included: 29 from the outbreak in 2002, seven from Aneityum in 1999 and 2000, 18 from visitors to Aneityum in 2000, and 15 from nearby Tanna Island in 2002. A neighbour-joining phylogenetic tree was constructed to elucidate the relationships among P. vivax isolates. STRUCTURE and principal component analysis were used to assess patterns of genetic structure.

Results
Here we show distinct genetic origins of P. vivax during the outbreak on Aneityum. While the origin of most P. vivax lineages found during the outbreak remains unidentified, limited genetic diversity among these lineages is consistent with a rapid expansion from a recent common ancestor. Contemporaneous P. vivax from neighboring Tanna and potential relapse of P. vivax acquired from other islands in 1999 and 2000 are also identified as minor contributors to the outbreak.

Conclusions
Multiple reintroductions of P. vivax after elimination highlight the high receptivity and vulnerability to malaria resurgence in island settings of Vanuatu, despite robust surveillance and high community compliance to control measures.
Characteristics of perfluoromethyl vinyl ether: A new eco‐friendly alternative gas for SF6
Authors: Xiao Song , Chen Yijiang , Tang Mingjun , Tian Shuangshuang , Xia Haoran , Wang Yifan , Tang Ju , Li Yi , Zhang Xiaoxing 
Published: May 2024

AbstractThe exploration of eco‐friendly insulating gas to substitute the most potent greenhouse gas sulphur hexafluoride (SF6) has consistently garnered significant attention. Herein, the authors evaluated the feasibility of utilising perfluoromethyl vinyl ether (PMVE, C3F6O) as a new branch of eco‐friendly insulating gas for the first time. The primary dielectric and stability characteristics of PMVE regarding AC breakdown, partial discharge, dielectric recovery, and decomposition properties were revealed under various gas pressure and electrical field conditions. It was found that PMVE demonstrated superior dielectric strength, with the AC breakdown and PD inception voltage (PDIV) 1.10 and 1.14 times that of pure SF6. Furthermore, the dielectric strength of PMVE exhibits stability even after undergoing 100 cycles of AC breakdowns, and there is no observable formation of solid precipitation on the electrode surface. The discharge decomposition of PMVE mainly generates fluorocarbon (CF4, C2F6, C3F6, C3F8, etc.) and CO. Overall, the exceptional insulation stability and no absence of solid precipitation features endow PMVE to be utilised as a new eco‐friendly gas for SF6‐free gas‐insulated equipment.
Transfer learning method for specific emitter identification based on pseudo‐labelling and meta‐learning
Authors: Ling Qing , Yan Wenjun , Zhang Yuchen , Yu Keyuan , Wang Chengyu 
Published: May 2024

AbstractSpecific emitter identification (SEI) represents a prominent research direction within the electronic countermeasures domain aimed at discerning carrier identity attributes by analysing subtle radar characteristics. At present, most established SEI techniques assume that both the source and target domain (TD) data adhere to the same distribution. However, this assumption is invalidated by semantic drift which frequently occurs between TD and source domain (SD) samples owing to variations in the collection environment, equipment, and other factors. Considering the aforementioned challenges, this article introduces a transfer learning approach for SEI to leverage pseudo‐label integration within the framework of meta‐learning. This approach employs the bispectral perimeter integral for extracting emitter signal features to construct a feature extractor and basic learner based on CNN13. To label and filter the TD samples, the proposed approach utilises the multiple pseudo‐label serial filtering mechanism, which comprises positive and negative pseudo‐labelling strategies, label uncertainty prediction methods, and hard sample filtering strategies. Ultimately, to address algorithmic real‐time requirements, the labelled TD samples are integrated into the feature extractor and learner of the SD through meta‐learning to facilitate the transfer of TD features to the SD training model. Experimental validation conducted on a real radar dataset demonstrated that the proposed algorithm significantly enhances identification accuracy, exhibiting an improvement from approximately 50% to approximately 90%. Furthermore, the algorithm exhibits a short runtime and robust adaptability, effectively catering to the demands of practical scenarios.
A deep learning based communication traffic prediction approach for smart monitoring of distributed energy resources in virtual power plants
Authors: Hou Meng , Liu Shidong , Zheng Qingrong , Liu Chuan , Zhang Xi , Kang Chongqing 
Published: May 2024

AbstractVirtual power plants (VPPs) have been widely recognized as a key enabler for energy system neutrality. The communication traffic of a VPP fundamentally indicates its activeness in interacting with the power system, thus providing a new dimension in depicting the behaviour characteristics of distributed energy resources in VPPs. Therefore, the prediction of communication traffic is significant in improving the control efficiency of VPPs. However, due to the involvement of numerous interactive agents characterised by both individual randomness and coordinative characteristics, traditional prediction models are no longer capable of fitting VPP communication traffic effectively. Therefore, a novel prediction model is introduced that enhances the prediction accuracy by integrating long short‐term memory (LSTM) and variational mode decomposition (VMD). This model employs VMD as the initial step for extracting the intrinsic modes from the traffic sequence, thereby mitigating the impact of incidental noise. Then, LSTM is applied to fit each intrinsic mode individually. Additionally, considering the outer influencing factors, the attention mechanism is incorporated. Finally, all sub‐prediction algorithms are neatly integrated as a whole prediction model. The proposed model is evaluated through simulation prediction using realistic VPP communication traffic data, and the results demonstrate its effectiveness.