bluuebunny/crossref_metadata_2025_split huggingface dataset:
Establishing an expert opinion framework for lung volume reduction in Ireland: a Delphi consensus technique
Authors: Mulryan Kathryn , Sorensen Jan , Redmond Karen 
Published: August 2023

Abstract
Background
Lung volume reduction (LVR) is an effective treatment option offered to patients with emphysema. There is no formalised LVR referral network in Ireland. A rigorous approach to agreeing and implementing a LVR referral framework in an Irish context is required. A Delphi process was used to provide a basis for a framework of multi-disciplinary teams (MDTs) which can provide LVR as a management option. A Delphi process offers a framework for understanding variations and developing a consensus from expert opinion.

Aim
The aim of this study was to develop consensus on recommendations for LVR referral guidelines in an Irish context and provide a national scope based on current practice and evidence.

Design
In accordance with Guidance on Conducting and Reporting Delphi Studies, a consensus-building Delphi study was performed. Thirty-three statements informed from review of research literature were identified and presented to participants. Evaluation of the statements was performed by an expert panel using a 5-point Likert scale. ≥ 70% agreement was defined as consensus and items with a consensus rating of < 70% were revised during the process. In total, Delphi questionnaires were distributed to 18 experts with a response rate of 78% (n = 14) and a follow-up response-rate of 50% (n = 7).
Setting/participants.
The expert panel in Ireland consisted of representatives from respiratory medicine, cardiothoracic surgery and allied-health professionals with expertise in COPD care.

Results
Of the initial 33 statements in five dimensions, there were consensus regarding 31 statements.

Conclusions
The 31 statements agreed through this Delphi study clarify a coherent direction for development of a LVR framework in Ireland. The Delphi study methodology described is a useful process to reach consensus among multi-disciplinary experts.
Respiratory deposition dose of PM2.5 and PM10 during night and day periods at an urban environment
Authors: Cipoli Yago Alonso , Furst Leonardo , Feliciano Manuel , Alves Célia 
Published: August 2023

Abstract
Inhalation of particulate matter (PM) has been extensively associated with the worsening and onset of cardiorespiratory diseases, being responsible for millions of deaths annually. Assessment of PM deposition in the human respiratory tract is critical to better understand the health risks from environmental exposure of vulnerable age groups. In this study, PM2.5 and PM10 day-night monitoring campaigns during the cold season were carried out in Bragança, Portugal. The multiple-path particle dosimetry (MPPD) model was used to quantify total and regional depositions in the human respiratory tract for four different age groups: infant (3 months), child (9 years), adult (21 years) and elderly (65 years). The results showed that concentrations for both PM fractions were higher during the night, a period marked by the burning of biomass for residential heating. Regional deposition fractions (DF) for PM2.5 were in the ranges 17–38% (head), 4–14% (tracheobronchial) and 20–28% (pulmonary), while for PM10 were 24–67% (head), 4–27% (tracheobronchial) and 12–22% (pulmonary). Children and the elderly were found to be the most vulnerable groups to PM deposition, especially for the TB and H regions, respectively. The lifetime cancer and non-cancer risks associated with exposure to PM2.5 exceeded the recommended limits, especially for children <10 years old. These findings provide useful information to alert authorities to the need to take action to reduce the pollution burden and protect the health, in particular of those most susceptible.

Graphical Abstract
The Leipzig Leadership Model: Measuring leadership orientations
Authors: Meynhardt Timo , Steuber Josephina , Feser Maximilian 
Published: August 2023

AbstractThe Leipzig Leadership Model (LLM) connects theory and practice. Building on actor-world relations and insights from motivational psychology (actor-action relations), the LLM proposes a holistic framework able to integrate the existing plethora of leadership theories and styles. This opens up a new perspective on a comprehensive understanding of leadership roles. With its four leadership orientation dimensions of purpose, entrepreneurial spirit, responsibility, and effectiveness, the LLM enables leaders to identify and reflect on relevant leadership competencies. In order to facilitate future research on the LLM and its dimensions, we report on two studies that are developing and validating a 32-item LLM-based scale. We applied oblique bifactor target rotation in a bifactor Exploratory Structural Equation Model within CFA approach in a German sample (N = 309) with robust WLSMV-estimates to fit an LLM-based model to the data. The results suggest a good fit. Furthermore, as ECV, PUC and ARPB support the multidimensional nature of the scale, we report the appropriate bifactor statistical indices. After parallel back translation, an English version of the scale was tested in a second sample (N = 311) to replicate our earlier findings. This study facilitates future empirical research by providing a concise and integrative self-rating measure of leadership orientations. We further strengthen the scientific foundation of the LLM by empirically testing its conceptually developed four-factor structure. The scale provides a starting point for further research into leadership orientations (also as standalone subscales), and offers an applicable guideline for self-reflection and decision-making.
Debate and well-being in self-managed groups: the moderating role of divergent status perceptions
Authors: Röllmann Laura Frederike , Weiss Mona , Zacher Hannes 
Published: August 2023

AbstractResearch suggests that debate, that is, open discussion behavior in work groups, can affect group-level outcomes. Yet, little is known about how debate may affect group member well-being. Drawing from the literature on debate and open conflict norms, we hypothesize that debate and well-being are positively associated because differing views can be shared and discussed openly. Additionally, based on theories on status conflicts and diversity, we expect that this relationship is moderated by the divergence of status perceptions within the group. Specifically, we propose that the positive relationship between group-level debate and well-being is stronger when group members’ perceptions of the hierarchical social status distribution in their group diverge strongly (rather than little) because in this situation debate can help resolve differing status construals. Data for this study came from 163 members of 29 self-organized activist groups that pursued social and/or ecological goals. Group members reported the level of debate within their group, perceived status distribution, and their individual well-being. Results of multilevel modeling showed that debate and well-being were positively related and that divergence of status perceptions moderated this relationship. With our study, we expand research on debate by investigating its relationship with well-being. Our study adds to the literature on status dynamics by showing that not only the distribution of social status, but also the divergent perception of its distribution is an important feature of status dynamics. Finally, we advance the literature by applying constructs from work and organizational psychology to activist well-being.
Hope, career competency, and social well-being among non-engaged youth in Hong Kong: a longitudinal network analysis
Authors: Ngai Steven Sek-yum , Cheung Chau-Kiu , Zhou Qiushi , Zhang Jihong , Ng Yuen-hang , Yu Elly Nga-hin , Zhang Xuyang , Wong Laing-ming 
Published: August 2023

AbstractAlthough it has been widely acknowledged that hope, career competency, and outcomes of social well-being (i.e., social integration, social contribution, and civic engagement) are key components of youth’s career and life development (CLD), those interrelationships, their predictive relationships, and the relative importance of the variables in the relationships remain poorly understood. To fill that gap, we conducted two network analyses on three waves of data collected in the CLAP@JC Community Intervention Project. A total of 4,220 non-engaged youth (NEY) from Hong Kong participated in the project, all of whom were 13–29 years old (M = 18.66, SD = 3.20) and 53.3% of whom were boys and young men. The first network analysis, conducted on the data at baseline, revealed a moderate correlation between career competency and hope and a strong correlation between civic engagement and social contribution. The second network analysis, conducted on the aggregated three-wave data, showed that career competency could predict all other variables and that only hope could positively impact career competency over time. We also observed that social contribution can positively influence hope. Overall, our findings highlight the central role of career competency in networks while also revealing the different roles of the examined variables within the networks. Our new findings on the functions of and the relationships among those variables provide insights for further theorizing CLD, while the information obtained can also help practitioners to develop effective intervention strategies for promoting CLD among NEY.
Vincristine-based nanoformulations: a preclinical and clinical studies overview
Authors: Shukla Rahul , Singh Ajit , Singh Kamalinder K. 
Published: August 2023

AbstractVincristine (VCR) is a chemotherapeutic agent obtained from natural alkaloid plant sourceCatharanthus roseus.VCR has been significantly useful in treatments of lung cancer, lymphocyte-based leukaemia, glioblastomas and acute myeloid leukaemia. VCR attaches to tubulin fibrils and prevents filament polymerization that permanently led to mitosis inhibition in cancer cells. Clinically, VCR is administered to patients in multidrug combination to reduce adverse drug effects and potential blockage of bone marrow inhibition due to prescribed monotherapy. However, VCR possesses low cancer tissue affinity and at higher dose often led to irreversible neurotoxicity. Conventional VCR injectables are successfully used in clinics, but lack of controlled release, non-specific biodistribution and consequent off-target side effects are still major challenges. Currently, nanotechnological drug delivery systems are being explored for improvement of VCR pharmacokinetic profile and tumour-specific targeting. Various nanomedicine formulations such as liposomes, lipid nanoparticles, and polymeric nanocarriers of VCR have been studied under various in vitro and in vivo models. In this review, we have summarised the chemotherapeutic role of VCR, evaluated the mechanism of action, pharmacokinetics and challenges associated with VCR delivery. Moreover, application of VCR in nanomedicine and effect on anticancer efficacy in preclinical and clinical setting are also being discussed.Graphical Abstract
Platforms and possibilities: a scoping study of curriculum resources for global citizenship education
Authors: Phillips Louise Gwenneth , de Rivera Liberty , Harris Pauline 
Published: August 2023

AbstractThe Alice Springs (Mparntwe) Education Declaration Goal two argues for young Australians ‘to understand their responsibilities as global citizens’. In these precarious times, children and youth require (and are demanding) education on how to address the myriad of convergent global challenges that is the focus of global citizenship education (GCE); however, perceived ambiguity is recognised as a barrier to greater GCE uptake. To support teacher uptake of global citizenship education, we searched for and mapped open-access GCE materials to create a systematic, research-based resource catalogue for teachers and students. We employed a scoping study to examine each resource’s alignments with Australian Curricula and global GCE frameworks and identified the areas where there is insufficient resourcing. Results showed that most resources were targeted to primary and secondary school students. More materials are needed for early childhood education as well as materials that engage learners of all ages to en/act on their understanding of what global citizenship entails.
Utilizing genetic diversity to select tomato lines tolerant of tomato yellow leaf curl virus based on genotypic coefficient of variation, heritability, genotypic correlation, and multivariate analyses
Authors: Mahmoud Ahmed M. A. , Osman Neama H. 
Published: August 2023

AbstractTomato yellow leaf curl virus (TYLCV) is one of the most destructive pathogens for tomato crops. The development of TYLCV-tolerant tomato lines (TLs) requires a thorough understanding of their genetic variability and relationships among lines and in traits of interest. Twelve F9 TLs were evaluated for phenotypic TYLCV tolerance, vegetative growth, yield, and fruit quality during the 2018 and 2019 fall seasons to identify elite breeding lines. TLs were selected by a bulk selection method from segregating generations of the commercial F1 hybrids TH99802 (TLs 1–6) and TH99806 (TLs 7–12). TLs exhibited either mild or no symptoms. The TYLCV titer varied between 0.8 × 105 and 3.9 × 105 in symptomless TLs plants compared to 56.7 × 105 in severely symptomatic plants of susceptible ‘Castlerock.’ Across both seasons, TL-3, TL-5, and TL-8 exhibited the highest total and marketable plant yields, TYLCV tolerance, and acceptable fruit quality. Most traits had high estimates of genetic variance, genotypic coefficient of variance, and broad sense heritability. Our results indicated that there was sufficient genetic variability for selection of the best lines. Principal component analysis and hierarchical cluster analysis indicated that the TLs were highly diverse of the evaluated traits and could be divided into three clusters. Cluster 1, which included TL-1, TL-3, and TL-8, performed better for TYLCV tolerance and economically important traits. Clusters 1 and 2 showed the greatest degree of dissimilarity. Therefore, crossing parents from Cluster 1 with 2 is predicated to maximum recombination for improve genotypes.
Mitochondrial DNA-Sensing Pathogen Recognition Receptors in Systemic Sclerosis-Associated Interstitial Lung Disease: a Review
Authors: Ghincea Alexander , Woo Samuel , Yu Sheeline , Pivarnik Taylor , Fiorini Vitoria , Herzog Erica L. , Ryu Changwan 
Published: August 2023

Abstract
Purpose of the Review
Systemic sclerosis (SSc) is a condition of dermal and visceral scar formation characterized by immune dysregulation and inflammatory fibrosis. Approximately 90% of SSc patients develop interstitial lung disease (ILD), and it is the leading cause of morbidity and mortality. Further understanding of immune-mediated fibroproliferative mechanisms has the potential to catalyze novel treatment approaches in this difficult-to-treat disease.

Recent Findings
Recent advances have demonstrated the critical role of aberrant innate immune activation mediated by mitochondrial DNA (mtDNA) through interactions with toll-like receptor 9 (TLR9) and cytosolic cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS).

Summary
In this review, we will discuss how the nature of the mtDNA, whether oxidized or mutated, and its mechanism of release, either intracellularly or extracellularly, can amplify fibrogenesis by activating TLR9 and cGAS, and the novel insights gained by interrogating these signaling pathways. Because the scope of this review is intended to generate hypotheses for future research, we conclude our discussion with several important unanswered questions.
Entrepreneurship education in the era of generative artificial intelligence
Authors: Bell Robin , Bell Heather 
Published: August 2023

AbstractGenerative artificial intelligence has seen fast paced developments, with it being utilised in numerous contexts, including both entrepreneurship and education. This has led to calls to integrate generative artificial intelligence into entrepreneurship education, to help prepare students to take advantage of future entrepreneurial opportunities. The technology also has the potential to influence pedagogy, teaching practice, and assessment and has raised concerns and questions within education about how educators can train students to use the latest technology to prepare them for the future, whilst managing potential changes to teaching practice. However, given the rapid emergence of the technology, discussion as to the implications for education and particularly entrepreneurship education is limited and there have been calls for further exploration and discussion. This paper addresses these calls by discussing some of the potential implications which generative artificial intelligence brings to entrepreneurship education and the entrepreneurship classroom, at both a macro and curricular level. The advancement of generative artificial intelligence furthers the need for entrepreneurship educators to embrace the technology in a managed way, develop students critical and reflective thinking, and foster the development and assessment of practical and technical entrepreneurial skills, to support student’s effective utilisation of generative artificial intelligence. Educators should also be aware of the potential effects which generative artificial intelligence poses to teaching and assessment.
Leakage of Nutrients Into The Soil Due to Carrion Decomposition Can Enhance Plant Growth
Authors: Wenting Elke , Jansen Patrick A. , Laugeman Mathijs J. B. , van Langevelde Frank 
Published: August 2023

AbstractCarrion decomposition has potentially far-reaching effects on nutrient cycles. Recent studies have demonstrated changes in soil-nutrient dynamics and enhanced plant growth because of nutrient leakage from decomposing carrion. However, only macronutrients have been evaluated so far, overlooking effects on a wide range of other essential or ecotoxic elements. This study aimed to examine how leakage affects the chemical composition of soil below decomposing carrion for a wide range of chemical elements, and how this in turn affects plant growth. We performed an experiment in which we let carrion fluid leak from dead mice for different periods of time and measured 22 elemental concentrations in the soils underneath. Then, we grew F1 maize plants on these soils and measured plant biomass. We found that leakage elevated concentrations of 13 essential elements (C, Ca, Co, Fe, K, Mg, Mn, Mo, Na, Ni, P, Se, and Zn) beneath the carrion. None of the potential ecotoxic elements turned out significant. Plant growth was up to nine times higher in soils enriched by carrion fluid. Our results demonstrate that a wide range of chemical elements leak into the soil as result of carrion decomposition, in concentrations that enhanced net plant growth. Our study must be considered as a first step towards a more comprehensive approach for investigating elemental leakage in the soil due to carrion decomposition. Further research may consider larger carcasses, more comprehensively examine the effects of multiple elements on plant growth, and examine how factors like scavenger activity, which may intercept carrion before elemental leakage can happen, affects leakage into the soil.
Revolutionizing Vehicle Cruise Control: An Elite Opposition-Based Pattern Search Mechanism Augmented INFO Algorithm for Enhanced Controller Design
Authors: Ekinci Serdar , Izci Davut , Abualigah Laith , Hussien Abdelazim G. , Thanh Cuong-Le , Khatir Samir 
Published: August 2023

AbstractThis paper presents a groundbreaking approach to enhance the performance of a vehicle cruise control system—a crucial aspect of road safety. The work offers two key contributions. Firstly, a state-of-the-art metaheuristic algorithm is proposed by augmenting the performance of the weighted mean of vectors (INFO) algorithm using pattern search and elite opposition-based learning mechanisms. The resulting boosted INFO (b-INFO) algorithm surpasses the original INFO, marine predators, and gravitational search algorithms in terms of performance on benchmark functions, including unimodal, multimodal, and fixed-dimensional multimodal functions. Secondly, a novel proportional, fractional order integral, derivative plus double derivative with filter ($$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$PIλDND2N2) controller is proposed as a more efficient control structure for vehicle cruise control systems. An objective function is utilized to determine the optimal values for the controller parameters, and the proposed method's performance is compared against a range of recent approaches. Results demonstrate that the b-INFO algorithm-based$$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$PIλDND2N2controller is the most efficient and superior method for controlling a vehicle cruise control system. Moreover, this work represents the first report of a$$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$PIλDND2N2controller’s implementation for vehicle cruise control systems, underscoring the novelty and significance of this research. The proposed method's exceptional ability is further confirmed by comparisons with the genetic algorithm, ant lion optimizer, atom search optimizer, arithmetic optimization algorithm, slime mold algorithm, Lévy flight distribution algorithm, manta ray foraging optimization, and hunger games search-based proportional–integral–derivative (PID), along with Harris hawks optimization-based PID and fractional order PID controllers. This work marks a remarkable milestone toward safer and more efficient vehicle cruise control systems.
RETRACTED ARTICLE: A Computational Model for Predicting Customer Behaviors Using Transformer Adapted with Tabular Features
Authors: Nguyen Khang , Mai T. Nga , Nguyen H. An , Nguyen V. Anh 
Published: August 2023

AbstractThe recent decade has seen an explosion in the e-commerce industry with the support of modern technologies (e.g., artificial intelligence) to maximize conversion rates. Many recommendation systems, therefore, have been developed to predict the customer behaviors to take appropriate actions. Customization of promotions or items for distinct groups of online customers considerably contributes to enhancing the sales. The purchasing records are essential information that can be used to investigate the customer behaviors. These kinds of information, however, are mainly expressed in tubular forms. Several computational models were developed using conventional machine learning algorithms to deal with that data type. However, these approaches struggle with large-volume and high-dimensional data, feature engineering, and high computational cost. In our study, we propose a deep learning model based on the Feature Tokenizer Transformer architecture to predict the customer purchasing intention. This novel architecture is a simplified adaptive version of the Transformer tabular data. The results demonstrated that our model showed better performance compared to conventional machine learning models. Furthermore, the model’s stability was also confirmed by the results of multiple repeated experiments.