bluuebunny/crossref_metadata_2025_split huggingface dataset:
Safeguarding our roots: natural resources accounting and reporting in the public sector
Authors: Aggestam Pontoppidan Caroline , Bisogno Marco , Caruana Josette , Dabbicco Giovanna 
Published: July 2024

Purpose
This study aims to explore natural resources from a public sector accounting perspective, focusing on their definitions, classifications, recognition criteria and disclosure requirements provided by different standard-setters and regulators at both international and national levels.

Design/methodology/approach
By reviewing accounting frameworks for natural resources, this study extrapolates accounting dilemmas around the debate on natural resource accounting, using the dialogic accounting perspective as a theoretical framework.

Findings
Natural resources cannot be defined as a single category. Various categories have different characteristics, requiring different standards to recognize multiple orientations. This avoids monetary reductionism. Furthermore, uncertainty, both in existence and measurement, may disqualify some of these resources from being considered assets. Perhaps, concentrating on the flow of services derived from natural resources is better than focusing on their valuation. This may lead to a split-asset approach (flows and underlying assets) for certain resources. This study’s findings indicate that public-sector entities should consider preparing a separate non-financial report regarding the management of natural resources with the objective of maintaining inter-generational equity.

Originality/value
This study contributes to the debate on natural resources from an accounting and reporting perspective, highlighting the importance of holding public-sector entities accountable for the use of natural resources.
Optimizing marketing strategy: a video analysis approach
Authors: Agrawal Shiv Ratan , Mittal Divya 
Published: July 2024

PurposeThe current study analyzes product review videos of influencers to determine why they are popular among customers. The study on electrical and electronic appliances covered by YouTubers is an entirely new field of research. Knowing why customers watch their product review videos before purchasing would be interesting.Design/methodology/approachWe analyzed 172 product review videos from influencers on YouTube. Subsequently, the study employed negative binomial regression (NB2) to predict the explanatory power of the independent variables over the dependent variables.FindingsThis paper recommends two different models for viewer engagement in online review videos. One can be used for high and the other for low viewer engagement. Comparatively, viewers put more effort into commenting on a video than liking it. Yet both have their importance as per the requirement.Research limitations/implicationsWe only focused on video content in English and Hindi. The study data considered review videos from various electrical and electronic appliances. Future researchers may replicate this study on different product categories.Practical implicationsThis study makes a remarkable contribution to how firms and their managers can optimize video content when designing marketing strategies, particularly for retailers and e-tailers.Originality/valueThe current paper takes the lead in contributing to the existing literature on marketing in two ways. First, focusing on product review videos from influencers and second, employing a video analysis approach. Furthermore, this study recommends two different viewer engagement models for marketing practices when employing quantitative and qualitative video content.
Predicting student success with and without library instruction using supervised machine learning methods
Authors: Harker Karen , Hargis Carol , Rowe Jennifer 
Published: July 2024

PurposeThe main purpose of this analysis was to demonstrate the value of predictive modeling of student success and identify the key groups of students for which library instruction could provide the most impact.Design/methodology/approachData regarding the attendance of library instruction associated with a first-year writing course were combined with student demographic and academic data over a four year period representing over 10,000 students. We applied supervised machine learning methods to determine the most accurate model for predicting student outcomes, including course outcome, persistence and graduation. We also assessed the impact of library instruction on these outcomes.FindingsThe gradient-boosted decision tree model provided the most accurate predictions. The impact of library instruction was modest but still was second only to the previous grade point average (GPA). The value of this metric, however, was greatest for students who were struggling, especially those who were first-generation students, regardless of ethnicity. More notably, the impact of library instruction was substantially greater for specific student demographics, including students with lower cumulative GPAs.Research limitations/implicationsFeatures of the models were limited to high-level academic metrics, some of which may not be very useful in predicting outcomes. Measures more closely related to learning styles, the course or course of study could provide for greater accuracy.Practical implicationsPrediction modeling could allow for a more selective approach to outreach and offers information that the librarian can use to customize instruction sessions and reference interactions.Social implicationsTargeting students who may be at risk of not succeeding in a course has ethical implications either way. If used to bias the subjective assessments, these predictions could produce self-fulfilling prophecies. Conversely, to ignore indicators of possible difficulties the student may have with the material is a disservice to the education of that student.Originality/valueThere are few studies that have incorporated library instruction into models of predicting student outcomes. Library resources and services can play a major role in the success of students, particularly those who have had less exposure to the resources and skills needed to use these resources.
Investigation of using amine and acetylamine functional units on naphthalimide dyes for photovoltaic devices
Authors: Hosseinnezhad Mozhgan , Nasiri Sohrab , Nutalapati Venkatramaiah , Gharanjig Kamaladin , Arabi Amirmasoud 
Published: July 2024

Purpose
The purpose of this paper is to introduce four new organic dyes based on naphthalimide for dye-sensitized solar cells (DSSCs).

Design/methodology/approach
Four new dyes based on naphthalimide with substitutions of amine and acetylamine in position C4 were designed in conjugation with substituted carbazole as donor–acceptor (D-A) architecture. The absorption and emission characteristics of the prepared dyes were evaluated in H2O, DMF and their mixture (DMF:H2O = 1:1). The feasibility of electron transfer in the DSSCs structure and energy levels were evaluated using electrochemical and density functional theory, which confirm the use of dyes in the DSSCs structure. The DSSCs were prepared using an individual strategy and their optical properties were investigated under the light of AM 1.5.

Findings
The prepared dyes exhibit orange color with strong emission at λem = 530–570 nm due to charge transfer with a positive solvatochromic effect. The efficiency of DSSCs based on Dye1-4 1 is: 3.69%, 3.71%, 4.69% and 4.76%. Therefore, the power efficiency increases by about 29 % in the presence of acetylamine group.

Practical implications
The design of new structures of organic dyes should be accompanied by the development of optical and electrical properties. In other words, in addition to the continuous production of electrons, efficient dyes must also be resistant to light to increase the life of the device.

Social implications
Organic dyes play a key role in the production of electrons in the DSSCs structure. The engineering of these structures and the introduction of widely used but low cost types can play an important role in the development of clean energy production.

Originality/value
The application of organic dyes based on naphthalimide was evaluated in the DSSCs structure and its photovoltaic properties were investigated.
A method for extracting P‐SV‐converted wave angle‐domain common‐image gathers based on elastic‐wave reverse‐time migration
Authors: Ci Qianqian , He Bingshou 
Published: July 2024

AbstractMulticomponent seismic technology utilizes the kinematic and dynamic characteristics of reflected P‐waves and converted S‐waves to reduce ambiguity in seismic exploration. The imaging and inversion accuracy of P‐SV‐converted waves are important in determining whether multicomponent seismic exploration can achieve higher exploration accuracy than conventional P‐wave exploration. Pre‐stack inversion of P‐SV‐converted waves requires precise input of P‐SV‐converted wave angle‐domain common‐image gathers. Consequently, the P‐SV‐converted wave angle‐domain common‐image gather extraction accuracy will significantly affect the P‐SV‐converted wave inversion accuracy. However, existing methods for extracting P‐SV‐converted wave angle‐domain common‐image gathers are constrained by issues such as the P‐ and S‐wave crosstalk artefacts, low‐frequency noises and inaccurate calculation of P‐wave incident angles, leading to poor imaging accuracy. We study an angle‐domain cross‐correlation imaging condition and address three key issues based on this condition: the decoupling of P‐ and S‐waves, the separation of up‐going and down‐going waves and the precise calculation of P‐wave incident angles. Our strategies facilitate high‐precision extraction of P‐SV‐converted wave angle‐domain common‐image gathers using elastic wave reverse‐time migration. In this paper, first, we employ the first‐order velocity‐dilatation‐rotation elastic wave equations to decouple P‐ and S‐waves automatically during source and receiver wavefield extrapolations. Second, we calculate the optical flow vectors of P‐ and S‐waves to ensure stable calculations of wave propagation directions. Based on this, we obtain up‐going and down‐going waves of P‐ and S‐waves. Meanwhile, we calculate the incident angle of the source P‐wave using geometric relations. Lastly, we apply the angle‐domain imaging condition to achieve high‐precision extraction of P‐SV‐converted wave angle‐domain common‐image gathers. Model examples demonstrate the effectiveness and advantages of the proposed method.
Unlocking the path: Exploring parental perception and coping strategies amidst special education challenges within mainstream educational settings in Israel
Authors: Gal Carmit , Ryder Chen Hanna , Raveh Amsalem Shani 
Published: July 2024

AbstractWithin the dynamic context of inclusive education for children with special needs in Israel, parents play a crucial role in addressing these challenges. The present study focuses on the experiences of parents with children who have special needs in inclusive educational frameworks in Israel. Using an interpretive phenomenological approach, qualitative semi‐structured interviews were conducted with 10 parents of children with special needs who are enrolled in inclusive educational settings, either in mainstream classrooms or kindergartens. The interviews were transcribed and analysed using theoretical thematic analysis, which yielded four main themes: persistent conflict, challenges in choosing educational settings, proactive coping strategies and interaction with educational settings. The study highlights conflicts with other parents, difficulties in decision‐making, and lack of adequate support from the system. Findings underscore the necessity for enhanced organizational frameworks, more proficient staff and supportive environments to effectively include children with special needs into mainstream education in Israel.
Post‐dialysis fatigue predicts all‐cause mortality in patients on chronic hemodialysis
Authors: Watanabe Guy , Tanaka Kenichi , Saito Hirotaka , Kimura Hiroshi , Tani Yoshihiro , Asai Jun , Suzuki Hodaka , Sato Keiji , Nakayama Masaaki , Kazama Junichiro James 
Published: July 2024

AbstractIntroductionFatigue is reportedly associated with a poor prognosis in dialysis patients. The aim of the present study was to investigate whether fatigue on dialysis days or non‐dialysis days is associated with mortality in patients on chronic hemodialysis.MethodsThis was a prospective study of 134 hemodialysis patients. The level of fatigue was evaluated using a visual analog scale (VAS). The association between high fatigue evaluated by the highest quartile of the VAS value and all‐cause death was investigated.ResultsThe fatigue scale score was significantly higher on dialysis than on non‐dialysis days. During the follow‐up period (median 6.8 years), 42 patients died. Patients with high post‐dialysis fatigue in the higher quartiles died more frequently compared to those with in the lower quartiles (p = 0.012). Multivariate Cox regression analysis showed that high post‐dialysis fatigue was an independent predictor of all‐cause death (adjusted hazard ratio 2.12, 95% confidence interval 1.10–4.07).ConclusionHigher post‐dialysis fatigue is related to increased mortality.
Single‐operator single‐balloon enteroscopy is safe and effective: A 6‐year retrospective study
Authors: Kou Guan Jun , Liu Chao , Yu Yan Bo , Li Yan Qing , Zuo Xiu Li 
Published: July 2024

ObjectivesSingle‐balloon enteroscopy (SBE) is an effective tool for the detection of small intestine lesions. Because it is conventionally performed by two operators, the efficacy of single‐operator SBE method has not yet been elucidated. We aimed to evaluate the diagnostic yield, total enteroscopy rate, procedure time, and complications of single‐operator SBE for small intestinal disease.MethodsThis was a single‐center, retrospective study including consecutive patients who underwent single‐operator SBE for suspicious small intestinal disorders or required therapeutic interventions between December 2014 and January 2019. The SBE procedures were performed by four endoscopists. Diagnostic yield, total enteroscopy rate, procedure time, incubation depth, and complications were analyzed, and stratification analysis was performed.ResultsAltogether 922 patients with 1422 SBE procedures were included for analysis, among whom 250, 172, and 500 patients underwent SBE via the oral route, the anal route and a combined route, respectively. The overall diagnostic yield was 78.52% (724/922). And 253 patients achieved total enteroscopy, with a total enteroscopy rate of 56.10%. The average procedure time for the oral and anal routes were 69.28 ± 14.72 min and 64.95 ± 13.87 min, respectively. While the incubation depth was 389.95 ± 131.42 cm and 191.81 ± 83.67 cm, respectively. Jejunal perforation was observed in one patient, which was managed by endoclips. Stratification analysis showed that the diagnostic yield and total enteroscopy rate significantly increased with operation experience together with decreased procedure time.ConclusionSingle‐operator SBE is effective and safe for the detection of small intestinal lesions, and is easy to master.
Association of education attainment and risk of connective tissue diseases
Authors: Zeng Yuanyuan , Yang Xiaolan , Tao Shengda , Lei Ling 
Published: July 2024

AbstractObjectiveWe employed two‐sample Mendelian randomization (MR) to assess the genetic causal relationship between educational attainment (EA) and risk of five common connective tissue diseases (CTDs).MethodsEducational attainment (self‐reported at age ≥30 years) was obtained from a meta‐analysis of years of schooling in 766 345 participants of European ancestry from genome‐wide association studies (GWAS). A total of 1265 signals associated with EA were identified. Genetic data for five CTDs [rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), polymyositis (PM), and dermatomyositis (DM)] were obtained from the FinnGen consortium. Two‐sample MR analyses were performed separately for EA and the five CTDs.ResultsWe found a negative causal relationship between EA and RA (ORIVW = 0.627, 95% CI = 0.537–0.732, p < .001), and SLE (ORIVW = 0.341, 95% CI = 0.123–0.944, p = .038). There were no genetic causal association between EA and SSc (ORIVW = 0.647, 95% CI = 0.351–1.195, p = .164), PM (ORIVW = 0.938, 95% CI = 0.320–2.746, p = .907), or DM (ORIVW = 0.754, 95% CI = 0.351–1.619, p = .468). None of the analyses revealed any horizontal pleiotropy or heterogeneity.ConclusionOur findings indicated a potential causal association between EA and RA, SLE, emphasizing the need for further investigation and potential integration of EA into clinical practice to enhance treatment strategies.
Macrophage iron dyshomeostasis promotes aging‐related renal fibrosis
Authors: Wu Lingzhi , Lin Hongchun , Li Shaomin , Huang Yuebo , Sun Yuxiang , Shu Shuangshuang , Luo Ting , Liang Tiantian , Lai Weiyan , Rao Jialing , Hu Zhaoyong , Peng Hui 
Published: July 2024

AbstractRenal aging, marked by the accumulation of senescent cells and chronic low‐grade inflammation, leads to renal interstitial fibrosis and impaired function. In this study, we investigate the role of macrophages, a key regulator of inflammation, in renal aging by analyzing kidney single‐cell RNA sequencing data of C57BL/6J mice from 8 weeks to 24 months. Our findings elucidate the dynamic changes in the proportion of kidney cell types during renal aging and reveal that increased macrophage infiltration contributes to chronic low‐grade inflammation, with these macrophages exhibiting senescence and activation of ferroptosis signaling. CellChat analysis indicates enhanced communications between macrophages and tubular cells during aging. Suppressing ferroptosis alleviates macrophage‐mediated tubular partial epithelial‐mesenchymal transition in vitro, thereby mitigating the expression of fibrosis‐related genes. Using SCENIC analysis, we infer Stat1 as a key age‐related transcription factor promoting iron dyshomeostasis and ferroptosis in macrophages by regulating the expression of Pcbp1, an iron chaperone protein that inhibits ferroptosis. Furthermore, through virtual screening and molecular docking from a library of anti‐aging compounds, we construct a docking model targeting Pcbp1, which indicates that the natural small molecule compound Rutin can suppress macrophage senescence and ferroptosis by preserving Pcbp1. In summary, our study underscores the crucial role of macrophage iron dyshomeostasis and ferroptosis in renal aging. Our results also suggest Pcbp1 as an intervention target in aging‐related renal fibrosis and highlight Rutin as a potential therapeutic agent in mitigating age‐related renal chronic low‐grade inflammation and fibrosis.
Artificial intelligence and clinical guidance in male reproductive health: ChatGPT4.0's AUA/ASRM guideline compliance evaluation
Authors: Gokmen Oya , Gurbuz Tugba , Devranoglu Belgin , Karaman Muhammet Ihsan 
Published: July 2024

AbstractBackgroundMale infertility is defined as the inability of a male to achieve a pregnancy in a fertile female by the American Urological Association (AUA) and the American Society for Reproductive Medicine (ASRM). Artificial intelligence, particularly in language processing models like ChatGPT4.0, offers new possibilities for supporting clinical decision‐making. This study aims to assess the effectiveness of ChatGPT4.0 in responding to clinical queries regarding male infertility, which is aligned with AUA/ASRM guidelines.MethodsThis observational study employed a design to evaluate the performance of ChatGPT4.0 across 1073 structured clinical queries categorized into true/false, multiple‐choice, and open‐ended. Two independent reviewers specializing in reproductive medicine assessed the responses using a six‐point Likert scale to evaluate accuracy, relevance, and guideline adherence.ResultsIn the true/false category, the initial accuracy was 92%, which increased to 94% by the end of the study period. For multiple‐choice questions, accuracy improved from 85% to 89%. The most significant gains were seen in open‐ended questions, where accuracy rose from 78% to 86%. Initially, some responses did not fully align with the AUA/ASRM guidelines. However, by the end of the 60 days, these responses had become more comprehensive and clinically relevant, indicating an improvement in the model's ability to generate guideline‐conformant answers (p < 0.05). The depth and accuracy of responses for higher difficulty questions also showed enhancement (p < 0.01).ConclusionChatGPT4.0 can serve as a valuable support tool in managing male infertility, providing reliable, guideline‐based information that enhances the accuracy of clinical decision‐making tools and supports patient education.
Monitoring Berlin Heart EXCOR by computer vision: A preliminary implementation and evaluation
Authors: Ota Hidehito , Fujimura Tomomi , Kunikata Ayumi , Yamagata Tomosato , Nozawa Hisataka , Ebishima Hironori , Kodera Satoshi , Inuzuka Ryo , Hirata Yasutaka , Matsui Hikoro 
Published: July 2024

AbstractBackgroundEXCOR Pediatric is one of the most commonly used ventricular assist devices (VAD) for small children; it requires visual inspection of the diaphragm movement to assess its operating status. Although this visual inspection can only be performed by trained medical professionals, it can also be attempted by the recent advances in computer vision technology.MethodsMovement of the diaphragm in the operating EXCOR VAD was recorded as movies and annotated frame‐by‐frame in three classes according to the state of the diaphragm: “fill,” “mid,” and “empty.” Three models, MobileNetV3, EfficientNetV2, and MobileViT, were trained using the frames, and their performance was evaluated based on the accuracy and area under the receiver operating characteristic curve (AROC).ResultsA total of 152 movies were available from two participants. Only the 10 mL pumps were used. Ninety‐eight movies were used for annotation and frame extraction, and 7949 frames per class were included in the analysis. The macro‐average accuracies of the three models were 0.88, 0.91, and 0.93, and the AROC were 0.99, 0.98, and 0.99 for MobileNetV3, EfficientNetV2, and MobileViT, respectively.ConclusionImage recognition models based on lightweight deep neural networks could detect the diaphragm state of EXCOR VAD with sufficient accuracy, although there were limited variations in the dataset. This suggests the potential of computer vision for the automated monitoring of the EXCOR diaphragm position.