bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gunshot Residue Deposition With and Without Firearm Suppressors (Silencers)
Authors: Prahlow Samuel P. , Morgan Lee , Prahlow Joseph A. 
Published: October 2024

Abstract
Forensic pathologists recognize the importance of estimating the range of fire for gunshot entrance wounds. Classically described ranges of fire include contact, close range, medium (or intermediate) range, and indeterminate (or distant) range. The presence or absence of gunshot residue (smoke/soot and/or gunpowder) and the characteristics of the gunshot residue are evaluated in order to estimate the range of fire. It is well known that interposed targets can block or otherwise alter gunshot residue deposition. In this preliminary study, a comparison is made between gunshot defects produced on targets using firearms with and without an attached suppressor device (so-called “silencer”). Comparisons are made at various distances from the targets, using multiple weapon/ammunition calibers.
Lymphadenopathy Secondary to Metastatic Squamous Cell Carcinoma Mistaken for Malignant Lymphoma
Authors: Jang Hye-Bin , Lee Dong Hoon , Lee Joon Kyoo , Lim Sang Chul 
Published: October 2024

Objective:
It is difficult to identify disease entities underlying lymphadenopathy in the head and neck region based solely on imaging. This often results in metastatic squamous cell carcinoma (Sqcc)–induced lymphadenopathy being mistaken for lymphoma. This study aimed to analyze clinical characteristics and computed tomographic features that aid in distinguishing between metastatic Sqcc and lymphoma when lymphadenopathy resembles a large solitary lymphoma.

Methods:
The authors retrospectively enrolled 5 patients, managed between 2010 and 2024, with metastatic Sqcc mistaken for lymphoma and 9 patients with lymphadenopathy of 2 cm or larger due to lymphoma.

Results:
Among the 5 patients, 3 exhibited a homogeneous lymphadenopathy phenotype, whereas the remaining 2 displayed heterogeneous enhancement with multiple small necrotic areas within the affected masses. Measurement of the Hounsfield units (HU) for lymphadenopathy, the sternocleidomastoid muscle, and the submandibular gland (SMG) was conducted for each patient. The ratio of lymphadenopathy HU to the average HU of the sternocleidomastoid muscle and the SMG was significantly higher in patients diagnosed with metastatic Sqcc compared with those with lymphoma (P = 0.01).

Conclusion:
In computed tomography scans, heterogeneous lymphadenopathy or enhancement levels that approach or exceed those of the SMG may indicate the likelihood of Sqcc rather than lymphoma.
Data-driven inference of Boolean networks from transcriptomes to predict cellular differentiation and reprogramming
Authors: Chevalier Stéphanie , Becker Julia , Gui Yujuan , Noël Vincent , Su Cui , Jung Sascha , Calzone Laurence , Zinovyev Andrei , del Sol Antonio , Pang Jun , Sinkkonen Lasse , Sauter Thomas , Paulevé Loïc 
Published: October 2024

ABSTRACTBoolean networks provide robust explainable and predictive models of cellular dynamics, especially for cellular differentiation and fate decision processes. Yet, the construction of such models is extremely challenging, as it requires integrating prior knowledge with experimental observation of transcriptome, potentially relating thousands of genes. We present a general methodology, implemented in the software tool BoNesis, for the qualitative modeling of gene regulation behind the observed state changes from transcriptome data and prior knowledge of the gene regulatory network. BoNesis allows computing ensembles of Boolean networks, where each of them is able to reproduce the modeled differentiation process. We illustrate the scalability and versatility of BoNesis with two applications: the modeling of hematopoiesis from single-cell RNA-Seq data, and modeling the differentiation of bone marrow stromal cells into adipocytes and osteoblasts from bulk RNA-seq time series data. For this later case, we took advantage of ensemble modeling to predict combinations of reprogramming factors for trans-differentiation that are robust to model uncertainties due to variations in experimental replicates and choice of binarization method. Moreover, we performed an in silico assessment of the fidelity and efficiency of the reprogramming, and conducted preliminary experimental validation.
Deciphering Metabolic Pathways and Protein-Protein Interaction Networks in Ankylosing Spondylitis through Single-Cell RNA Sequencing
Authors: Yarıcı Merve , Karabekmez Muhammed Erkan 
Published: October 2024

AbstractAnkylosing Spondylitis (AS) is a common autoimmune disease affecting spinal joints and causing chronic pain. Understanding the roles of different cell types in AS can facilitate the development of effective treatments. In this study, we analyzed scRNA-seq data of peripheral blood mononuclear cells (PBMC) from AS patients and healthy controls collected from the literature. Using the GIMME algorithm, we created genome-scale metabolic models for each cell type to analyze reaction fluxes varying between patient and healthy conditions. Our findings revealed increased purine metabolism flux, fatty acid degradation, and glycolysis in CD14 monocytes, CD4 memory, CD4 naive, and CD8 T cells in AS patients compared to healthy individuals. Additionally, by integrating multi-omics approaches we generated cell- type-specific protein-protein interaction (PPI) networks, uncovering 63 rewired hubs across nine cell types. RPS11 emerged as the most significant hub, essential in translation and there are evidences in the literature that implicate it in AS. These results provide a detailed understanding of the metabolic and protein interaction changes in specific immune cell types in AS, highlighting RPS11 as a critical regulatory hub that could serve as a potential biomarker or therapeutic target for developing more precise and effective treatments.
When evidence is not enough: A qualitative exploration of healthcare workers’ perspectives on expansion of two-way texting (2wT) for post-circumcision follow-up in South Africa
Authors: Fabens Isabella , Makhele Calsile , Igaba Nelson , Moyo Khumbulani , Ndebele Felex , Pienaar Jacqueline , Setswe Geoffrey , Feldacker Caryl 
Published: October 2024

AbstractAs per national guidelines, in-person follow-up visits after voluntary medical male circumcision (VMMC) are required but may be unnecessary. Two-way texting (2wT) engages clients in post-operative care and triages those with complications to in-person review. 2wT-based telehealth was found to be safe, effective, and efficient. In South Africa, to understand provider perspectives on the 2wT approach and potential for expansion, 20 key informant interviews were conducted with management, clinicians, data officials and support staff involved in 2wT scale-up. Interviews were analyzed using rapid qualitative methods and informed by two implementation science frameworks: the Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) framework and the Pragmatic, Robust, Implementation and Sustainability Model (PRISM). Participants submitted mixed and multi-faceted feedback, including that 2wT improves monitoring and evaluation of clients and clinical outcomes while also reducing follow-up visits. Challenges included duplicative routine and 2wT reporting systems and perceptions that 2wT increased workload. To improve the likelihood of successful 2wT scale-up in routine VMMC settings, respondents suggested: further 2wT sensitization to ensure clinician and support staff buy-in; a dedicated clinician or nurse to manage telehealth clients; improved dashboards to better visualize 2wT client data; mobilizing 2wT champions at facilities to garner support for 2wT as routine care; and, updating VMMC guidelines to support VMMC telehealth. As attendance at follow-up visits may not be as high as reported, implementing 2wT may require more effort but also brings added benefits of client verification and documented follow-up. The transition from research to routine practice is challenging, but use of RE-AIM and PRISM indicate that it is not impossible. As VMMC funding is decreasing, more effort to share the evidence base for 2wT as a safe, cost-effective, high-quality approach for VMMC follow-up is needed to encourage widespread uptake and adoption.
Multimodal Foundation Models for Medical Imaging - A Systematic Review and Implementation Guidelines
Authors: Huang Shih-Cheng , Jensen Malte , Yeung-Levy Serena , Lungren Matthew P. , Poon Hoifung , Chaudhari Akshay S 
Published: October 2024

AbstractAdvancements in artificial intelligence (AI) offer promising solutions for enhancing clinical workflows and patient care, potentially revolutionizing healthcare delivery. However, the traditional paradigm of AI integration in healthcare is limited by models that rely on single input modalities during training and require extensive labeled data, failing to capture the multimodal nature of medical practice. Multimodal foundation models, particularly Large Vision Language Models (VLMs), have the potential to overcome these limitations by processing diverse data types and learning from large-scale unlabeled datasets or natural pairs of different modalities, thereby significantly contributing to the development of more robust and versatile AI systems in healthcare. In this review, we establish a unified terminology for multimodal foundation models for medical imaging applications and provide a systematic analysis of papers published between 2012 and 2024. In total, we screened 1,144 papers from medical and AI domains and extracted data from 97 included studies. Our comprehensive effort aggregates the collective knowledge of prior work, evaluates the current state of multimodal AI in healthcare, and delineates both prevailing limitations and potential growth areas. We provide implementation guidelines and actionable recommendations for various stakeholders, including model developers, clinicians, policymakers, and dataset curators.
Polarization-insensitive state preparation for trapped-ion hyperfine qubits
Authors: Leu A. D. , Smith M. C. , Gely M. F. , Lucas D. M. 
Published: October 2024

Quantum state preparation for trapped-ion qubits often relies on high-quality circularly polarized light, which may be difficult to achieve with chip-based integrated optics technology. We propose and implement a hybrid optical and microwave scheme for intermediate-field hyperfine qubits which instead relies on frequency selectivity. Experimentally, we achieve 99.94% fidelity for linearly polarized (σ+/σ−) light, using Ca+43 at 28.8 mT. We find that the fidelity remains above 99.8% for a mixture of all polarizations (σ+/σ−/π). We calculate that the method is capable of 99.99% fidelity in Ca+43, and even higher fidelities in heavier ions such as Ba+137.

Published by the American Physical Society
2024
Evolution of creases on the event horizon of a black hole merger
Authors: Gadioux Maxime , Hennigar Robie A. , Reall Harvey S. 
Published: October 2024

A generic black hole merger occurs through a restructuring of creases (sharp edges) on the event horizon. This process is studied for a black hole merger in the limit of infinite mass ratio, for which constructing the event horizon reduces to finding a null hypersurface that asymptotes to a Rindler horizon in the Kerr spacetime. Geometrical properties of the creases on this horizon are determined and the results are compared with the predictions of an exact local description of the event horizon in a generic merger. The crease set is shown to have finite area. A recently proposed expression for the gravitational entropy of a crease is shown to diverge at the instant of merger. Caustics on (and off) the event horizon are determined by exploiting the correspondence with the problem of gravitational lensing by a Kerr black hole. Caustics form an “astroid tube” in spacetime, two edges of which lie on the event horizon of the merger. Perturbative expressions for the location of this tube are presented, extending previous work to much higher perturbative order.

Published by the American Physical Society
2024
How should social media influencers tell compelling stories through video blogs? A study of storytelling features on live comments
Authors: Dong Xuebing , Wang Biao , Liu Yan , Xi Nannan , Zhu Donghong 
Published: October 2024

PurposeUtilizing the extended transportation-imagery model, this study categorizes three storytelling elements into six distinct factors – character types, influencer-character congruence, imaginable titles, concrete details, replication difficulty and artistic processing – to explore how these factors enhance influencer engagement.Design/methodology/approachThis study utilized a quantitative research design, analyzing 1,660 influencer-created videos over a six-month period. Narrative elements were examined through manual coding, and their impact on live comments was assessed using negative binomial regression to identify key factors driving audience engagement.FindingsResearch results show that non-fictional characters, imaginable titles and concrete details significantly increased live comments. Conversely, high replication difficulty negatively influenced engagement. Notably, influencer-character congruence and artistic processing showed no significant effect.Originality/valueThis study advances the extended transportation-imagery model by integrating narrative elements with live comments, offering new perspectives on real-time audience engagement. The findings deepen our understanding of how storytelling techniques enhance the effectiveness of influencer marketing. From a managerial standpoint, this research provides strategic insights for influencers and brands to refine their content strategies, ultimately boosting audience engagement.
The effect of intellectual capital and venture capital on enterprise values: evidence from China
Authors: Wang Pang Paul , Zhang Ruolin , Zhang Qilin 
Published: October 2024

PurposeIntellectual capital (IC) and venture capital (VC) play an important role in enterprise development. While the literature has investigated the relationship between IC and the profitability of companies, the relationship among IC, VC and enterprise value (EV) is still not well understood.Design/methodology/approachDrawing insights from the literature, we develop a few testable hypotheses about the relationships among IC, VC and EV. Using the panel data of companies listed in the Chinese stock market from 2009 to 2019, we employ fixed-effects regression models to test these hypotheses.FindingsWe find that IC has a significant positive effect on long-term EV. VC is found to have a positive direct effect on long-term EV but has a negative direct effect when its moderating effect with IC is considered. To explain this finding, we develop a simple economic model and provide an over-investment perspective.Originality/valueWe believe this paper can shed light on pro-venture investment policies in China, as well as provide indications for similar policies around the world.
Assessing the internationalization dynamics of emerging markets: a comprehensive analysis utilizing SWARA-WASPAS techniques
Authors: Sarihan Ahmed Yusuf , Ozdemir Kadir 
Published: October 2024

Purpose
This paper aims to evaluate the internationalization of countries represented in the MSCI Emerging Markets Index. The evaluation considers high-technology product imports, foreign direct investments, research and development expenditures, patent and industrial design applications, exports and gross domestic product (GDP) data, representing production.

Design/methodology/approach
This paper uses the Step-Wise Weight Assessment Ratio Analysis (SWARA) method to assess and rank the criteria for evaluating emerging markets. Four academics who are authorities in the field of foreign trade were consulted to weigh the criteria. The Weighted Aggregated Sum Product Assessment (WASPAS) method, considered one of the most reliable and robust MCDM techniques, was then used to evaluate and rank the countries.

Findings
The findings obtained during the research process reveal the internationalization dynamics of these countries based on the indicators they possess. As a result, it is observed which countries achieve higher performance in the internationalization process based on relevant criteria.

Originality/value
This study is theoretically unique and valuable as it simultaneously offers the potential for development to macro-level international trade theories, such as the technologic deficit hypothesis, and meso-level internationalization theories, such as the Uppsala model. Additionally, integrated multiple criteria decision-making (MCDM) methods, which are not frequently used in cross-country studies, have been used, and the performance of emerging markets has been ranked. The findings obtained from this application distinguish the research from the existing literature by transforming it into a performance ranking rather than focusing on the antecedents or consequences of internationalization and their interactions.
Unveiling the effects of influencing factors on PPP project capital structure in China using machine learning
Authors: Hou Wenhua , Ran Wenlu 
Published: October 2024

PurposeThis study aims to investigate the determinants of the capital structure of public–private partnership (PPP) projects in China and the nonlinear relationship between them.Design/methodology/approachFirst, this study identifies potential factors that can influence the capital structure of PPP projects based on literature and theoretical analysis. Second, this paper collects data from PPP projects in China and empirically investigates them using multiple linear regression and machine learning methods. Finally, for machine learning model results, this paper adopts the Shapley additive explanations to interpret them.FindingsThe results show that project size, contract duration, number of sponsors, urbanization level and regional openness are key factors influencing project capital structure, and there is a nonlinear relationship between all these factors and capital structure.Research limitations/implicationsTheoretically, this study complements the influencing factors of PPP project capital structure and reveals their nonlinear relationship. Practically, the findings of this study can help PPP project participants formulate project capital structure more scientifically.Practical implicationsPractically, the findings of this study can help project managers to recognize the important factors affecting the capital structure of PPP projects and formulate capital structure more scientifically. Moreover the results are conducive to policymakers to predict a reasonable capital structure for PPP projects and better control project risks. These research findings can also help creditors make more accurate loan decisions and promote project success to meet the needs of the general public.Originality/valueMost existing literature has studied the linear relationship between influencing factors and the capital structure of PPP projects. This study uses machine learning models to explore the nonlinear relationship between influencing factors and the capital structure of PPP projects and explains the working principles.
#ChooseToBeTVET: exploring the political aim to enhance the perceived value of TVET in Chile through a communication campaign
Authors: Bravo Paulina , Escárate Pablo 
Published: October 2024

PurposeThis paper aims to understand the ideas and material circumstances behind the policy objective to enhance the perceived value of Technical and Vocational Education and Training (TVET) in Chile through a communication campaign and how this campaign addresses this objective.Design/methodology/approachThis research adopted a qualitative approach, drawing on data collected through 26 semi-structured interviews, the revision of 4 policy documents and 15 promotional videos. The data were analysed thematically, adopting the cultural political economy framework as a lens to guide the analysis.FindingsFindings show that the problematisation of TVET’s perceived value is rooted in the system’s development history and cultural ideas. A communication campaign was one of the means to address this problem. Initial campaign messages appealed to the benefits prospective students could enjoy because of choosing TVET programs. However, later, the message gradually shifted to highlighting the collective benefits for the country, depicting TVET as a fulfilling and valuable education path.Originality/valueThis article is the first to critically analyse the reasons for and use of a communication campaign to enhance the TVET’s perceived value in a global south context.
Impact of ChatGPT and generative AI on lifelong learning and upskilling learners in higher education: unveiling the challenges and opportunities globally
Authors: Asad Muhammad Mujtaba , Ajaz Aqsa 
Published: October 2024

PurposeA gripping keyword emerged in the dynamic world of 2022: GPT or the advent of Generative Artificial Intelligence (GAI), at its forefront, embodied by the mysterious ChatGPT. This technological marvel had been silently lurking in the background for just over five years. However, all of a sudden, it emerged onto the scene, capturing the public’s attention and quickly becoming one of the most widely adopted inventions in history. Therefore, this narrative review is conducted in order to explore the impact of generative AI and ChatGPT on lifelong learning and upskilling of students in higher education and address opportunities and challenges proposed by Artificial Intelligence from a global perspective.Design/methodology/approachThis review has been conducted using a narrative literature review approach. For in-depth identification of research gaps, 105 relevant articles were included from scholarly databases such as Scopus, Web of Science, ERIC and Google Scholar. Seven major themes emerged from the literature to answer the targeted research questions that describe the use of AI, the impact of generative AI and ChatGPT on students, the challenges and opportunities of using AI in education and mitigating strategies to cope with the challenges associated with the integration of ChatGPT and generative AI in education.FindingsThe review of the literature presents that generative AI and ChatGPT have gained a lot of recognition among students and have revolutionized educational settings. The findings suggest that there are some contexts in which adult education research and teaching can benefit from the use of chatbots and generative AI technologies like ChatGPT. The literature does, however, also highlight the necessity of carefully considering the benefits and drawbacks of these technologies in order to prevent restricting or distorting the educational process or endangering academic integrity. In addition, the literature raises ethical questions about data security, privacy and cheating by students or researchers. To these, we add our own ethical concerns about intellectual property, such as the fact that, once we enter ideas or research results into a generative chatbot, we no longer have control over how it is used.Practical implicationsThis review is helpful for educators and policymakers to design the curriculum and policies that encourage students to use generative AI ethically while taking academic integrity into account. Also, this review article identifies the major gaps that are associated with the impact of AI and ChatGPT on the lifelong learning skills of students.Originality/valueThis review of the literature is unique because it explains the challenges and opportunities of using generative AI and ChatGPT, also defining its impact on lifelong learning and upskilling of students.