bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring Agreement Using Guessing Models and Knowledge Coefficients
Authors: Moss Jonas 
Published: June 2023

Several measures of agreement, such as the Perreault–Leigh coefficient, the AC1\documentclass[12pt]{minimal}
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\begin{document}$$\textsc {AC}_{1}$$\end{document}, and the recent coefficient of van Oest, are based on explicit models of how judges make their ratings. To handle such measures of agreement under a common umbrella, we propose a class of models called guessing models, which contains most models of how judges make their ratings. Every guessing model have an associated measure of agreement we call the knowledge coefficient. Under certain assumptions on the guessing models, the knowledge coefficient will be equal to the multi-rater Cohen’s kappa, Fleiss’ kappa, the Brennan–Prediger coefficient, or other less-established measures of agreement. We provide several sample estimators of the knowledge coefficient, valid under varying assumptions, and their asymptotic distributions. After a sensitivity analysis and a simulation study of confidence intervals, we find that the Brennan–Prediger coefficient typically outperforms the others, with much better coverage under unfavorable circumstances.
A YOLOv5-based network for the detection of a diffuse reflectance spectroscopy probe to aid surgical guidance in gastrointestinal cancer surgery
Authors: Gkouzionis Ioannis , Zhong Yican , Nazarian Scarlet , Darzi Ara , Patel Nisha , Peters Christopher J. , Elson Daniel S. 
Published: June 2023

Abstract
Purpose
A positive circumferential resection margin (CRM) for oesophageal and gastric carcinoma is associated with local recurrence and poorer long-term survival. Diffuse reflectance spectroscopy (DRS) is a non-invasive technology able to distinguish tissue type based on spectral data. The aim of this study was to develop a deep learning-based method for DRS probe detection and tracking to aid classification of tumour and non-tumour gastrointestinal (GI) tissue in real time.

Methods
Data collected from both ex vivo human tissue specimen and sold tissue phantoms were used for the training and retrospective validation of the developed neural network framework. Specifically, a neural network based on the You Only Look Once (YOLO) v5 network was developed to accurately detect and track the tip of the DRS probe on video data acquired during an ex vivo clinical study.

Results
Different metrics were used to analyse the performance of the proposed probe detection and tracking framework, such as precision, recall, mAP 0.5, and Euclidean distance. Overall, the developed framework achieved a 93% precision at 23 FPS for probe detection, while the average Euclidean distance error was 4.90 pixels.

Conclusion
The use of a deep learning approach for markerless DRS probe detection and tracking system could pave the way for real-time classification of GI tissue to aid margin assessment in cancer resection surgery and has potential to be applied in routine surgical practice.
VIS+AI: integrating visualization with artificial intelligence for efficient data analysis
Authors: Wang Xumeng , Wu Ziliang , Huang Wenqi , Wei Yating , Huang Zhaosong , Xu Mingliang , Chen Wei 
Published: June 2023

Abstract
Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On one hand, visualization can facilitate humans in data understanding through intuitive visual representation and interactive exploration. On the other hand, AI is able to learn from data and implement bulky tasks for humans. In complex data analysis scenarios, like epidemic traceability and city planning, humans need to understand large-scale data and make decisions, which requires complementing the strengths of both visualization and AI. Existing studies have introduced AI-assisted visualization as AI4VIS and visualization-assisted AI as VIS4AI. However, how can AI and visualization complement each other and be integrated into data analysis processes are still missing. In this paper, we define three integration levels of visualization and AI. The highest integration level is described as the framework of VIS+AI, which allows AI to learn human intelligence from interactions and communicate with humans through visual interfaces. We also summarize future directions of VIS+AI to inspire related studies.
Perceived altruism in cause-related marketing
Authors: Lopes Julia Maringoni , Bairrada Cristela Maia , Coelho Arnaldo Fernandes de Matos 
Published: June 2023

AbstractThe purpose of this paper is to analyze how corporate image may mediate the effects of cause-related marketing on consumer behavior, aiming to expand existing literature in the field of corporate social responsibility. Altruism was used as a moderator of the proposed relationships. The conceptual model presents 7 hypotheses, and the testing is based on a sample of 463 valid respondents from Brazil and Portugal. Data was collected through an online survey and statistically analyzed using the structural equations modeling. The Ekos line of the Brazilian brand Natura is used as an object of study in this research. Brand-cause fit, consumer-cause identification and trust in cause-related marketing (CRM) campaign showed evidence of a positive relationship with corporate image. Corporate image showed a positive relationship with purchase intention, life satisfaction and brand attitude. However, results show how different levels of altruism may affect consumer perceptions. The study has several limitations, in particular due to the use of a convenience sample. This research finds evidence of relevant impacts of brand-cause fit, consumer-cause identification and trust in CRM campaign in the construction of a credible corporate image, which in turn influences greatly purchase intention, consumer satisfaction and overall attitude towards brand, giving precious clues to how to redirect marketing campaigns. The research offers a model that depicts the chain of effects between a CRM campaign and customer decision, introducing the possible impacts on life satisfaction and the moderation of consumer altruistic values.
Adipocyte-derived extracellular vesicles: bridging the communications between obesity and tumor microenvironment
Authors: Zhou Chuan , Huang Yu-Qian , Da Ming-Xu , Jin Wei-Lin , Zhou Feng-Hai 
Published: June 2023

AbstractBy the year 2035 more than 4 billion people might be affected by obesity and being overweight. Adipocyte-derived Extracellular Vesicles (ADEVs/ADEV-singular) are essential for communication between the tumor microenvironment (TME) and obesity, emerging as a prominent mechanism of tumor progression. Adipose tissue (AT) becomes hypertrophic and hyperplastic in an obese state resulting in insulin resistance in the body. This modifies the energy supply to tumor cells and simultaneously stimulates the production of pro-inflammatory adipokines. In addition, obese AT has a dysregulated cargo content of discharged ADEVs, leading to elevated amounts of pro-inflammatory proteins, fatty acids, and carcinogenic microRNAs. ADEVs are strongly associated with hallmarks of cancer (proliferation and resistance to cell death, angiogenesis, invasion, metastasis, immunological response) and may be useful as biomarkers and antitumor therapy strategy. Given the present developments in obesity and cancer-related research, we conclude by outlining significant challenges and significant advances that must be addressed expeditiously to promote ADEVs research and clinical applications.
Seroprevalence of arthropod-borne bacterial infections in homeless individuals in Hamburg in 2020
Authors: Heinrich Fabian , Rauch Jessica , Bertram Franziska , Kempf Volkhard A. J. , Besier Silke , Kuta Piotr , Renné Thomas , Ondruschka Benjamin , Püschel Klaus , Tappe Dennis 
Published: June 2023

Abstract
Purpose
The number of homeless people in Germany is steadily increasing. Due to their often precarious living conditions, this specific population may be increasingly exposed to ectoparasites that can transmit various pathogens. To assess the prevalence and thus the risk of such infections, we analyzed the seropositivity of rickettsiosis, Q fever, tularemia and bartonellosis in homeless individuals.

Methods
A total of 147 homeless adults from nine shelters in Hamburg, Germany, were included. The individuals underwent questionnaire-based interviewing, physical examination, and venous blood was drawn between May and June 2020. Blood samples were analyzed for antibodies against rickettsiae (Rickettsia typhi and R. conorii), Coxiella burnetii, Francisella tularensis and bartonellae.

Results and conclusion
A very low seroprevalence of R. typhi and F. tularensis infection was found (0–1%), while antibodies against R. conorii and C. burnetii were more common (7% each), followed by a relatively high seroprevalence of 14% for bartonellosis. Q fever seroprevalence was associated with the country of origin, whereas bartonellosis seroprevalence was associated with the duration of homelessness. Preventive measures targeting ectoparasites, especially body lice, should be put in place continuously.
Artificial Intelligence Algorithms for Collaborative Book Recommender Systems
Authors: Tegetmeier Clemens , Johannssen Arne , Chukhrova Nataliya 
Published: June 2023

AbstractBook recommender systems provide personalized recommendations of books to users based on their previous searches or purchases. As online trading of books has become increasingly important in recent years, artificial intelligence (AI) algorithms are needed to recommend suitable books to users and encourage them to make purchasing decisions in the short and the long run. In this paper, we consider AI algorithms for so called collaborative book recommender systems, especially the matrix factorization algorithm using the stochastic gradient descent method and the book-based k-nearest-neighbor algorithm. We perform a comprehensive case study based on the Book-Crossing benchmark data set, and implement various variants of both AI algorithms to predict unknown book ratings and to recommend books to individual users based on the highest predicted ratings. This study aims to evaluate the quality of the implemented methods in recommending books by using selected evaluation metrics for AI algorithms.
WRANet: wavelet integrated residual attention U-Net network for medical image segmentation
Authors: Zhao Yawu , Wang Shudong , Zhang Yulin , Qiao Sibo , Zhang Mufei 
Published: June 2023

AbstractMedical image segmentation is crucial for the diagnosis and analysis of disease. Deep convolutional neural network methods have achieved great success in medical image segmentation. However, they are highly susceptible to noise interference during the propagation of the network, where weak noise can dramatically alter the network output. As the network deepens, it can face problems such as gradient explosion and vanishing. To improve the robustness and segmentation performance of the network, we propose a wavelet residual attention network (WRANet) for medical image segmentation. We replace the standard downsampling modules (e.g., maximum pooling and average pooling) in CNNs with discrete wavelet transform, decompose the features into low- and high-frequency components, and remove the high-frequency components to eliminate noise. At the same time, the problem of feature loss can be effectively addressed by introducing an attention mechanism. The combined experimental results show that our method can effectively perform aneurysm segmentation, achieving a Dice score of 78.99%, an IoU score of 68.96%, a precision of 85.21%, and a sensitivity score of 80.98%. In polyp segmentation, a Dice score of 88.89%, an IoU score of 81.74%, a precision rate of 91.32%, and a sensitivity score of 91.07% were achieved. Furthermore, our comparison with state-of-the-art techniques demonstrates the competitiveness of the WRANet network.
A framework for drivers fostering social-ecological restoration within forest landscape based on people’s participation. A systematic literature review
Authors: Maniraho Leonidas , Frietsch Marina , Sieber Stefan , Löhr Katharina 
Published: June 2023

AbstractDegradation exacerbates food and water insecurity, economic hardship, biodiversity loss, and the devastating effects of climate change. Given that ecosystem restoration is a global challenge, the United Nations declared 2021 to 2030 as the Decade of Ecosystem Restoration.Many ecological restoration projects overlook social perspectives, resulting in unsuccessful restoration outcomes within Forest Landscape Restoration (FLR). Against this background, we review social-ecological restoration frameworks and summarize seven key balanced drivers that could help enhance the adoption of ecosystem restoration in a dynamic social context. The drivers relate to including the most affected communities, privileging local knowledge and practices, empowering local representatives and opinion leaders, ensuring social and environmental justice and equity, targeting deep leverage points, aligning restoration practices with local needs and aspirations, and connecting neighboring communities.We argue that ecosystem restoration will be most effective if approached from a social-ecological perspective. In developing countries, establishing social groups that share savings and credit structures within neighboring households can be a sustainable approach. With increasing global initiatives, taking a social-ecological perspective on ecosystem restoration as a social-ecological restoration approach offers new opportunities for both research and practice. Social-ecological restoration is a key strategy that can support the achievement of sustainable development goals (SDGs) and deliver net positive gains environmentally, socially, and economically. Further studies should focus on two new cross-cutting aspects: the ecological and social effects of restoration at small to large scales and social ecological restoration and peace building within a restorative landscape.
Sensor system for development of perception systems for ATO
Authors: Tagiew Rustam , Leinhos Dirk , von der Haar Henrik , Klotz Christian , Sprute Dennis , Ziehn Jens , Schmelter Andreas , Witte Stefan , Klasek Pavel 
Published: June 2023

AbstractDeveloping AI systems for automatic train operation (ATO) requires developers to have a deep understanding of the human tasks they are trying to replace. This paper fills this gap and translates the regulatory requirements from the context of German railways for the AI developer community. As a result, tasks such as train’s path monitoring for collision prediction, signal detection, door operation, etc. are identified. Based on this analysis, a functionally justified sensor setup with detailed configuration requirements is presented. This setup was also evaluated by a survey within the railway industry. The evaluated sensors include RGB/IR cameras, LIDARs, radars and ultrasonic sensors. Calculations and estimates for the evaluated sensors are presented graphically and included in this paper. However, the ultimate sensor setup is still a subject of research. The results of this paper also address the lack of training and test datasets for railway AI systems. It is proposed to acquire research datasets that will allow the training of domain adaptation algorithms to transform other datasets, thus increasing the number of available datasets. The sensor setup is also recommended for such research datasets.
Cyber insurance-linked securities
Authors: Braun Alexander , Eling Martin , Jaenicke Christoph 
Published: June 2023

AbstractWe investigate the feasibility of cyber risk transfer through insurance-linked securities (ILS). On the investor side, we elicit the preferred characteristics of cyber ILS and the corresponding return expectations. We then estimate the cost of equity of insurers and compare it to the Rate on Line expected by investors to match demand and supply in the cyber ILS market. Our results show that cyber ILS will work for both cedents and investors if the cyber risk is sufficiently well understood. Thus, challenges related to cyber risk modeling need to be overcome before a meaningful cyber ILS market may emerge.
The effect of pharyngeal packing on gastric volume in patients undergoing nasal surgery: a randomised, controlled trial
Authors: Altun Demet , Özkan-Seyhan Tülay , Canbaz Mert , Aydemir Levent , Altun Dilek , Gökduman Hürü Ceren , Çamcı Emre 
Published: June 2023

AbstractObjectiveTo explore the effects of pharyngeal packing on antral cross-sectional area, gastric volume and post-operative complications.MethodsIn this prospective, randomised, controlled study, 180 patients were randomly assigned to a control group or a pharyngeal packing group. Gastric antral dimensions were measured with pre- and post-operative ultrasound scanning. Presence and severity of post-operative nausea and vomiting and sore throat were recorded.ResultsPost-operative antral cross-sectional area and gastric volume were significantly larger in the pharyngeal packing group compared to the control group. The incidence and severity of post-operative nausea and vomiting were significantly less in the pharyngeal packing group. More frequent and severe sore throat was observed in the control group within the ward. An increased Apfel simplified risk score and post-operative antral cross-sectional area were associated with post-operative nausea and vomiting during the first 2 hours, whereas septorhinoplasty and functional endoscopic sinus surgery, absent pharyngeal packing, and lower American Society of Anesthesiologists’ physical status were associated with post-operative nausea and vomiting within the ward.ConclusionRegardless of operation type, pharyngeal packing use resulted in smaller gastric volume, which was associated with reduced post-operative nausea and vomiting frequency and severity, and lower sore throat incidence.
When Is Something an Alternative? A General Account Applied to Animal-Free Alternatives to Animal Research
Authors: Kramer Koen 
Published: June 2023

AbstractThe first “R” from animal research ethics prescribes the replacement of animal experiments with animal-free alternatives. However, the question of when an animal-free method qualifies as an alternative to animal experiments remains unresolved.Drawing lessons from another debate in which the word “alternative” is central, the ethical debate on alternatives to germline genome editing, this paper develops a general account of when something qualifies as an alternative to something. It proposes three ethically significant conditions that technique, method, or approach X must meet to qualify as an alternative to Y: (1) X must address the same problem as Y, under an appropriate description of that problem; (2) X must have a reasonable chance of success, compared to Y, in solving the problem; and (3) X must not be ethically unacceptable as a solution. If X meets all these conditions, its relative advantages and disadvantages determine whether it is preferable, indifferent, or dispreferable as an alternative to Y.This account is then applied to the question of whether animal-free research methods qualify as alternatives to animal research. Doing so breaks down the debate around this question into more focused (ethical and other) issues and illustrates the potential of the account.
The Pediatric Serious Illness Conversation Program: Understanding challenges and experiences for clinicians after advance care planning training
Authors: Doherty Megan , Gujral Preet , Frenette Maryse , Lusney Nadine , van Breemen Camara 
Published: June 2023

AbstractObjectivesTo explore experiences of pediatric clinicians participating in a serious illness communication program (SICP) for advance care planning (ACP), examining how the SICP supports clinicians to improve their communication and the challenges of implementing new communication tools into clinical practice.MethodsA qualitative description study using individual interviews with a diverse group of pediatric clinicians who participated in 2.5-hour SICP training workshops at pediatric tertiary hospitals. Discussions were transcribed, coded, and arranged into overarching themes. Thematic analysis was conducted using interpretive description methodology.ResultsFourteen clinicians from 2 Canadian pediatric tertiary hospital settings were interviewed, including nurses (36%), physicians (36%), and social workers (29%), from the fields of neonatology (36%), palliative care (29%), oncology (21%), and other pediatric specialties (14%). Key themes included specific benefits of SICP, with subthemes of connecting with families, increased confidence in ACP discussions, providing tools to improve communication, and enhanced self-awareness and self-reflection. A second theme of perceived challenges emerged, which included subthemes of not having the conversation guide readily accessible, divergent team communication practices, and particular features of the clinical environment which limited the possibility of engaging in ACP discussions with parents.Significance of resultsA structured program to enhance serious illness communication supports clinicians to develop skills and tools to increase their confidence and comfort in conducting conversations about end-of-life issues. Addressing challenges of adopting the newly learned communication practices, by providing access to digital SICP tools and conducting SICP training for clinical teams may further support clinicians to engage in ACP.
Burial and Denudation Alter Microbial Life at the Bottom of the Hypo‐Critical Zone
Authors: McIntosh Jennifer , Kim Ji‐Hyun , Bailey Lydia , Osburn Magdalena , Drake Henrik , Martini Anna , Reiners Peter , Stevenson Bradley , Ferguson Grant 
Published: June 2023

AbstractHow subsurface microbial life changed at the bottom of the kilometers‐deep (hypo) Critical Zone in response to evolving surface conditions over geologic time is an open question. This study investigates the burial and exhumation, biodegradation, and fluid circulation history of hydrocarbon reservoirs across the Colorado Plateau as a window into the hypo‐Critical Zone. Hydrocarbon reservoirs, in the Paradox and Uinta basins, were deeply buried starting ca. 100 to 60 Ma, reaching temperatures >80–140°C, likely sterilizing microbial communities present since the deposition of sediments. High salinities associated with evaporites may have further limited microbial activity. Upward migration of hydrocarbons from shale source rocks into shallower reservoirs during maximum burial set the stage for microbial re‐introduction by creating organic‐rich “hot spots.” Denudation related to the incision of the Colorado River over the past few million years brought reservoirs closer to the surface under cooler temperatures, enhanced deep meteoric water circulation and flushing of saline fluids, and likely re‐inoculated more permeable sediments up to several km depth. Modern‐ to paleo‐hydrocarbon reservoirs show molecular and isotopic evidence of anaerobic oxidation of hydrocarbons coupled to bacterial sulfate reduction in areas with relatively high SO4‐fluxes. Anaerobic oil biodegradation rates are high enough to explain the removal of at least some portion of postulated “supergiant oil fields” across the Colorado Plateau by microbial activity over the past several million years. Results from this study help constrain the lower limits of the hypo‐Critical Zone and how it evolved over geologic time, in response to changing geologic, hydrologic, and biologic forcings.