bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing broiler chicken health and performance: the impact of phytobiotics on growth, gut microbiota, antioxidants, and immunity
Authors: Urban Jakub , Kareem Karwan Yaseen , Matuszewski Arkadiusz , Bień Damian , Ciborowska Patrycja , Lutostański Kamil , Michalczuk Monika 
Published: July 2024

AbstractThe total ban on antibiotics as growth promoters in livestock nutrition, introduced in EU (European Union) countries on 1 January 2006, presented animal nutritionists with a considerable challenge in finding alternatives. First, the additives had to protect animals’ digestive tracts from pathogenic bacteria, and second, they should be inert in relation to the animals’ bodies. After many experiments, phytobiotics seem like they may be an effective alternative. This article aims to review key scientific articles relating to the use of phytobiotics of various origins in the feeding of chickens for fattening. The review of the available literature brings together the most important research findings on the effects of phytobiotic supplementation on growth performance, gut microbiota, antioxidant status and immune system of broiler chickens. Phytobiotics are natural plant substances produced to protect plants against pathogenic microorganisms. Phytobiotics are classified as a group of biologically active compounds with a broad chemical diversity and may include terpenes, triterpenes and flavonoids. Based on the collected information, it can be concluded that the use of phytobiotics in appropriate quantities and proportions in feed for broiler chickens influences the proper functioning of the digestive tract by, among other things, stimulating beneficial microbiota and secretion of digestive enzymes. In addition, the introduction of such feed additives has an impact on the alleviation of inflammation, supports the functioning of the immune system and has a positive influence on production results.
The Future Process of Japan’s Population Aging: A Cluster Analysis Using Small Area Population Projection Data
Authors: Inoue Takashi , Inoue Nozomu 
Published: July 2024

AbstractJapan’s population aging is the most advanced in the world today. No nationwide study has been conducted using small area population projection data on Japan’s aging population. This is because such projection data was unavailable for Japan before the 2016 launch of the website ‘The Web System of Small Area Population Projections for the Whole Japan’ (SAPP for Japan). SAPP for Japan opened the small-area and long-term projected population of Japan for the first time on the World Wide Web. The purpose of this study is to quantitatively analyze the future aging process using data from the SAPP for Japan and, based on this analysis, to attempt to present the standard aging process that developed countries will experience after the demographic transition, taking advantage of the fact that Japan has the most aged population in the world. Subsequently, a non-hierarchical cluster analysis was performed using two statistics on aging: the elderly population proportion and the elderly population change index, and the small areas were classified into seven clusters. Furthermore, this study examined the demographic and geographical features of the clusters, introduced a new concept of the stage in the population aging process, and analyzed the relationship between the features and the stages. To conclude, the following findings were obtained regarding the future process of Japan’s population aging. In each area of Japan, first, the total population begins to decline, second, the elderly population begins to decrease, and finally, its proportion begins to decrease. These stage shifts generally proceed earlier in areas with a higher elderly population proportion and are attributed to the reduced size of younger cohorts owing to long-term fertility decline. This process would be the norm in many developed countries after the demographic transition.
Till We Have Red Faces: Drinking to Signal Trustworthiness in Contemporary China
Authors: Lin Wanlin , Kang Siqin , Zhu Jiangnan , Ding Li 
Published: July 2024

AbstractInterpersonal networks facilitate business cooperation and socioeconomic exchange. But how can outsiders demonstrate their trustworthiness to join existing networks? Focusing on the puzzling yet common phenomenon of heavy drinking at China’s business banquets, we argue that this costly practice can be a rational strategy intentionally used by entrants to signal trustworthiness to potential business partners. Because drinking alcohol can lower one’s inhibitions and reveal one’s true self, entrants intentionally drink heavily to show that they have nothing to hide and signal their sincere commitment to cooperation. This signaling effect is enhanced if the entrants have low alcohol tolerance, as their physical reactions to alcohol (e.g., red face) make their drunkenness easier to verify. Our theory of heavy social drinking is substantiated by both ethnographic fieldwork and a discrete-choice experiment on Chinese entrepreneurs. This research illuminates how trust can be built absent sufficient support from formal institutions.
Crypto-influencers
Authors: Merkley Kenneth J. , Pacelli Joseph , Piorkowski Mark , Williams Brian 
Published: July 2024

AbstractThis study examines the investment value of information provided by crypto-influencers, that is, social media influencers covering crypto assets on Twitter. We examine the returns associated with approximately 36,000 tweets issued by 180 of the most prominent crypto social media influencers covering over 1,600 crypto assets for the two years spanning through December 2022. Our primary results indicate that crypto-influencers’ tweets are initially associated with positive returns. However, these tweets are followed by significant negative longer-horizon returns, suggesting they generate minimal long-term investment value. These effects are most pronounced for tweets issued by crypto-influencers proclaiming to be crypto experts, for smaller cap crypto asset securities and for self-described experts with many Twitter followers. In an additional analysis, we use machine-learning methods to classify tweets and find that this pattern of results strengthens when the tweets have a more positive sentiment or relate to buy recommendations.
How to measure interdisciplinary research? A systemic design for the model of measurement
Authors: Cantone Giulio Giacomo 
Published: July 2024

AbstractInterdisciplinarity is a polysemous concept with multiple, reasoned and intuitive, interpretations across scholars and policy-makers. Historically, quantifying the interdisciplinarity of research has been challenging due to the variety of methods used to identify metadata, taxonomies, and mathematical formulas. This has resulted in considerable uncertainty about the ability of quantitative models to provide clear insights for policy-making. This study proposes a systemic design, grounded in an advanced literature review, to demonstrate that the quantification of the interdisciplinarity of research can be treated as a process of decision-making in mathematical modelling, where alternatives choices are evaluated based on how closely their mathematical properties align with the theoretical objectives of the research design. The study addresses modeling choices regarding the stylisation of metadata into units of observation, and the operational definition of the conceptual dimensions of interdisciplinarity, presenting both established and novel methods and formulas. The final section discusses advanced topics in modelling the measurement, including a dedicated discussion on the difference in analysing the status of papers versus collective bodies of research; and distinguishing between reflective, formative, and inferential causal models of interdisciplinary research.
The impact of social media use on the relationship between social isolation and connectedness during COVID-19 in Hong Kong
Authors: Rochelle Tina L. , Chan L. M. 
Published: July 2024

AbstractThe emergence of the COVID-19 pandemic has emphasised the importance of social connectedness, whilst the popularity of social media continues to rise. The present study examined the relationship between engagement on social networking sites (SNSs), social connectedness and social isolation in a sample of Hong Kong Chinese adults during the COVID-19 pandemic. A total of 232 participants (65% female) aged 18–65 years were recruited to a cross-sectional online study. SNS engagement was predictive of social connectedness in the present sample. Findings revealed that SNS engagement was associated with lower levels of social isolation. Younger participants reported greater engagement with SNSs, and lower levels of social isolation compared to older participants. However, older respondents reported greater levels of social connectedness. No gender differences were observed in social connectedness, but men reported significantly higher levels of social isolation compared to women. With the COVID-19 pandemic only just at an end, social restrictions have recently been lifted in Hong Kong, resulting in the significance of online communication becoming ever more important as a means of maintaining social connectedness.
Training design for social inclusion: The impact of sociodemographic factors on immigrant learners in Dutch adult education programs
Authors: Bolzonella Francesco , de Greef Maurice , Segers Mien 
Published: July 2024

AbstractThis study explores the impact of adult basic education programs aimed at enhancing social inclusion for immigrant learners in the Netherlands. Basic literacy skills are vital for performing everyday tasks and building human capital, which in turn facilitates employment and skill acquisition. Low adult literacy is often associated with social exclusion and poverty, which can have detrimental effects on mental health and further reinforce marginalization. We analyzed two adult education programs (N = 171) conducted in 2019, within the context of lifelong learning policies designed to support adults with low literacy skills. Our findings confirm the positive effects of these educational programs on social inclusion outcomes. Through logistic regression and moderation analyses, we examined how participants’ sociodemographic backgrounds influenced their social inclusion outcomes following the program. Key pre-training conditions, such as prior education and employment status, influenced how participants engaged with a positively perceived learning environment. Assertiveness emerged as a significant outcome, affecting changes across various aspects of social inclusion. These results suggest that acquiring new skills empowers participants to reshape their self-perceived literacy identity. This study adds to the body of literature on adult education by emphasizing the importance of training design and sociodemographic factors in fostering social inclusion for immigrant learners.
Individual values and inductive risk: remotivating the Bayesian alternative
Authors: Hatchwell Rivkah 
Published: July 2024

AbstractThe argument from inductive risk has become widely accepted as good reason to reject the value-free ideal. The literature that follows is then focused on where inductive risk judgements are required and whose values ought to determine them. The purpose of this paper is twofold. Firstly, to offer motivation for aiming at the value-free ideal, and therefore avoiding inductive risk. To do so I show that there is a tension between principles in science ethics and value encroachment because of inductive risk. Secondly, I offer a renewed defence of Jeffrey’s response to the argument from inductive risk. By appealing to theories in epistemology about rational belief modelling, I argue that the Bayesian belief model offers a suitable alternative to current belief modelling in science, despite criticism that is either explicit in the literature or fairly expected to arise.
Epidemiology and diagnostic accuracy of Clostridium perfringens toxins in the intestinal contents of camels, sheep, and cattle: a cross-sectional study in Dakahlia governorate, Egypt
Authors: Wahdan Ali , Elhaig Mahmoud M. 
Published: July 2024

AbstractThis study aimed to establish an accurate epidemiological surveillance tool for the detection of differentC. perfringenstypes from 76 diseased and 34 healthy animals in Dakhalia Governorate, Egypt. A total of 110 intestinal content samples were randomly collected from camels, sheep, and cattle.C. perfringenswas isolated and biochemically identified by the VITEK2 system. Toxinotyping and genotyping ofC. perfringensisolates were specified by a multiscreen ELISA and real-time qPCR (rt-qPCR). The occurrence ofC. perfringenswas highest among camels (20% in healthy and 25% in diseased) and was lowest in cattle (23.1% and 14.7%). Thecpatoxin was detected in all isolates by rt-qPCR and in 7 isolates by ELISA,exttoxin was detected in 7 isolates by rt-qPCR and in 6 isolates by ELISA, and cpbtoxin was detected in 2 isolates by both rt-qPCR and ELISA. Four types ofC. perfringenswere identified by rt-qPCR, type A (65.2%), B (4.3%), C (4.3%), and D (26.1%), and three types by ELISA, type D (17.4%), A (8.7%) and C (4.3%). Our study indicated the prevalence of infection in Dakahlia byC. perfringenstype A and D, particularly camels, and recommends adopting an appropriate vaccination strategy among the studied animals.
The use of artificial intelligence in musculoskeletal ultrasound: a systematic review of the literature
Authors: Getzmann Jonas M. , Zantonelli Giulia , Messina Carmelo , Albano Domenico , Serpi Francesca , Gitto Salvatore , Sconfienza Luca Maria 
Published: July 2024

Abstract
Purpose
To systematically review the use of artificial intelligence (AI) in musculoskeletal (MSK) ultrasound (US) with an emphasis on AI algorithm categories and validation strategies.

Material and Methods
An electronic literature search was conducted for articles published up to January 2024. Inclusion criteria were the use of AI in MSK US, involvement of humans, English language, and ethics committee approval.

Results
Out of 269 identified papers, 16 studies published between 2020 and 2023 were included. The research was aimed at predicting diagnosis and/or segmentation in a total of 11 (69%) out of 16 studies. A total of 11 (69%) studies used deep learning (DL)-based algorithms, three (19%) studies employed conventional machine learning (ML)-based algorithms, and two (12%) studies employed both conventional ML- and DL-based algorithms. Six (38%) studies used cross-validation techniques with K-fold cross-validation being the most frequently employed (n = 4, 25%). Clinical validation with separate internal test datasets was reported in nine (56%) papers. No external clinical validation was reported.

Conclusion
AI is a topic of increasing interest in MSK US research. In future studies, attention should be paid to the use of validation strategies, particularly regarding independent clinical validation performed on external datasets.
Detection of pulmonary nodules in chest radiographs: novel cost function for effective network training with purely synthesized datasets
Authors: Hanaoka Shouhei , Nomura Yukihiro , Yoshikawa Takeharu , Nakao Takahiro , Takenaga Tomomi , Matsuzaki Hirotaka , Yamamichi Nobutake , Abe Osamu 
Published: July 2024

Abstract
Purpose
Many large radiographic datasets of lung nodules are available, but the small and hard-to-detect nodules are rarely validated by computed tomography. Such difficult nodules are crucial for training nodule detection methods. This lack of difficult nodules for training can be addressed by artificial nodule synthesis algorithms, which can create artificially embedded nodules. This study aimed to develop and evaluate a novel cost function for training networks to detect such lesions. Embedding artificial lesions in healthy medical images is effective when positive cases are insufficient for network training. Although this approach provides both positive (lesion-embedded) images and the corresponding negative (lesion-free) images, no known methods effectively use these pairs for training. This paper presents a novel cost function for segmentation-based detection networks when positive–negative pairs are available.

Methods
Based on the classic U-Net, new terms were added to the original Dice loss for reducing false positives and the contrastive learning of diseased regions in the image pairs. The experimental network was trained and evaluated, respectively, on 131,072 fully synthesized pairs of images simulating lung cancer and real chest X-ray images from the Japanese Society of Radiological Technology dataset.

Results
The proposed method outperformed RetinaNet and a single-shot multibox detector. The sensitivities were 0.688 and 0.507 when the number of false positives per image was 0.2, respectively, with and without fine-tuning under the leave-one-case-out setting.

Conclusion
To our knowledge, this is the first study in which a method for detecting pulmonary nodules in chest X-ray images was evaluated on a real clinical dataset after being trained on fully synthesized images. The synthesized dataset is available at https://zenodo.org/records/10648433.
Diversity of Kordyana species (Brachybasidaceae) on Commelinaceae in Australia
Authors: Zeil-Rolfe Isabel , Gooden Ben , Hunter Gavin C. , Linde Celeste C. , Shivas Roger G. 
Published: July 2024

AbstractThe identity and diversity of Kordyana species on three native species of Commelinaceae in Australia were studied following surveys in 2020–2022 for Kordyana brasiliensis, which had been deliberately released as a biocontrol agent for the environmental weed Tradescantia fluminensis. Three new species of Kordyana are described from Australia based on DNA sequence analysis of the ITS and LSU rDNA regions, morphology, host associations, and geographic distributions. Two new species, Kordyana spectabilis on Aneilema acuminatum and Kordyana luteoalba on Pollia crispata, occur in shaded rainforest habitats in eastern Australia. The third new species, Kordyana occidentalis on Commelina ensifolia, occurs in forests and woodlands of the Kimberley region of Western Australia. Morphological descriptions are provided for these three new species of Kordyana as well as for the conidial stage of K. brasiliensis.
Understanding the Stress-Induced Movement of $$\gamma /\epsilon $$ Interfaces and Coalescence of $$\epsilon $$ Martensite Variants Through Fractal Analysis
Authors: Das Arpan 
Published: July 2024

AbstractThe influence of stress/strain on the movement/rearrangement of $$\gamma /\epsilon $$

γ
/
ϵ

interfaces and the coalescence of $$\epsilon $$
ϵ
plates under a fixed location of a high Mn steel have been investigated through fractal measurement of $$\epsilon $$
ϵ
plates. Image texture analysis has also been implemented to recognize the stored energy and configurational stability of such plates under $$\gamma $$
γ
matrix as a function of tensile deformation. Fractality of $$\epsilon $$
ϵ
variants are correlated with their geometrical configurations at different directions with systematic increment of tensile strain.
Correlation Between Elastic Properties and Phase Transformation of Zr50Pd50−xRux High-Temperature Shape Memory Alloys Designed by DFT
Authors: Shen Yu-Nien , Nkomo D. , Matsunaga S. , Phasha M. J. , Yamabe-Mitarai Y. 
Published: July 2024

AbstractThe effect of Ru addition on the martensitic transformation and mechanical properties of Zr50Pd50−xRux SMAs shape memory alloys has been studied. Strain–temperature experiments, differential scanning calorimeter, and scanning electron microscope analyses were performed to validate the theoretical predictions by DFT calculation regarding the influence of the C′ parameter on martensitic stability. Despite the absence of an observed shape memory effect under the tested conditions, the findings suggest that ZrPdRu alloys hold promise for high-temperature applications.
Tracing the Scientific Legacy: Bibliometric Analysis of LATAM Research in Bariatric Surgery for 33 Years
Authors: Domínguez Alvarado Gonzalo Andrés , López Gómez Luis Ernesto , Serrano Baez Gustavo Adolfo , Serrano Gómez Sergio Eduardo , Vásquez Pineda Andrés , Bustos Lopez Tatiana , Arévalo González María Alejandra , Palomino Peña Carlos Felipe , Chavarría Granda Luis David , Álvarez Leon Daniela , Barrera Arguello Diego Mauricio 
Published: July 2024

Abstract
Introduction
Metabolic and bariatric surgery (MBS) has experienced considerable growth, addressing the challenges of obesity and its complications. The lack of a comprehensive bibliometric analysis in Latin America motivates this study, highlighting the need to understand the evolution of research in this area and its impact on clinical decision-making and health policies.

Methodology
A cross-sectional bibliometric study was carried out using the Scopus database. A structured search strategy was designed to identify articles related to bariatric surgery with authors affiliated with Latin American countries. Inclusion and exclusion criteria were applied, followed by a descriptive and bibliometric analysis of the scientific production found.

Results
A total of 3553 documents published between 1991 and 2024 were included. There was an annual growth of 11%, with an average age of documents of 7.5 years. A concentration was observed in some countries, notably Brazil, Mexico, and Chile. Although scientific output increased, the average number of citations per article showed a downward trend since 2003.

Discussion
Despite the growth in scientific production, the quality and relevance of research is questioned, especially given the decrease in the impact received. It highlights the lack of meaningful regional collaboration, which could limit the sharing of knowledge and resources. Questions are raised about gaps in research capacity and the economic and development implications are discussed.

Conclusions
This study provides valuable information to strengthen future research in bariatric surgery in Latin America. It highlights the importance of promoting regional and international collaboration and improving research training in countries with less participation. Clinical intervention strategies can benefit from better understanding research trends and adopting evidence-based practices in a more informed manner.

Graphical Abstract
Experts’ intuitive mathematical discourses about integration in complex analysis
Authors: Hanke Erik 
Published: July 2024

AbstractAlthough complex analysis is part of the study programs of many mathematics undergraduates, little research has been done on how individuals interpret basic concepts from complex analysis. To address this gap, this paper investigates how experts individually think about complex path integrals. For this purpose, the commognitive framework is used to conceptualize experts’ interpretations of mathematical concepts discursively, namely in terms of so-called intuitive mathematical discourses. A total of nine interpretations of complex path integrals, so-called discursive images, as well as eight sets of rules governing their construction, so-called discursive frames, are derived from expert interviews. These interpretations range from a rejection of intrinsic meaning to connections with real and vector analysis, mean values, and individual formulations of theorems. The paper also raises questions for the inclusion of the results into teaching and addresses further research.