bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of deep learning on diagnostic performance in the differentiation of benign and malignant thyroid nodules
Authors: Kaba Esat , Solak Merve , Varlık Ayşenur Topçu , Çubukçu Yusuf , Sağır Lütfullah , Sünnetci Kubilay Muhammed , Alkan Ahmet , Gündoğdu Hasan , Çeliker Fatma Beyazal , Beyazal Mehmet 
Published: September 2024

Aims: This study aims to use deep learning (DL) to classify thyroid nodules as benign and malignant with ultrasonography (US). In addition, this study investigates the impact of DL on the diagnostic success of radiologists with different experiences. Material and methods: This study included 576 US images of thyroid nodules. The dataset was divided into 80% training and 20% test sets. Four radiologists with different levels of experience classified the images in the test set as benign-malignant. A DL model was then trained with the train set and predicted benign-malignant for the test set. Then, the output of the DL model for each nodule in the test set was presented to 4 radiologists, who were asked to make a benign-malignant classification again considering these DL results.Results: The accuracy of the DL model was 0.9391. The accuracy for junior resident (JR) 1, JR 2, senior resident (SR), and senior radiologist (Srad) before DL-assisting were 0.7043, 0.7826, 0.8435, and 0.8522 respectively. The accuracy in DL-assisted classifications was 0.9130, 0.8696, 0.9304, and 0.9043 for JR 1, JR2, SR, and Srad, respectively. DL assistance changed the decisions of less experienced radiologists more than more experienced radiologists. Conclusion: The DL model has superior accuracy in classifying thyroid nodules as benign-malignant with US images than radiologists with different levels of experience. Additionally, all radiologists, and most notably less experienced radiology residents, increased their accuracy in DL-assisted predictions.
Korean Dual-Career Judokas’ Junior-to-Senior Transition: A Longitudinal Study
Authors: Hong Hee Jung , Hong Seung Han 
Published: September 2024

This study adopts the athletic career transition model to explore the experiences of Korean dual-career (DC) judokas during their junior-to-senior transition using a longitudinal approach. We recruited 12 Korean elite judokas, all of whom were in their first year of university during their initial interview. Participants were organized into three focus groups, with three rounds of interviews conducted over approximately 2 years, totaling nine focus-group sessions. Thematic analysis was applied, which led to the identification of three key themes: (a) multifaceted challenges, (b) coping strategies, and (c) perceived needs of DC athletes prioritizing sport over study. The results indicate that Korean DC judokas share some common challenges (e.g., increased training demands, balancing their studies with training demands) with their European counterparts, but they also face unique challenges (e.g., managing weight control, laundry duties, and relationships with senior judokas) specific to the Korean judokas. Their coping strategies include both internal resources (e.g., focusing on performance target, utilizing resilience) and external ones (e.g., seeking social support), emphasizing the critical role of psychological support during their junior-to-senior transition. Proactive psychological support is recommended through a specialized system tailored to this group. Given that Korean DC judokas significantly prioritize sport over education, this system should also address balancing both sport and education.
Birds as reservoirs: unraveling the global spread of Gamma- and Deltacoronaviruses
Authors: Guo Jinyue , He Jieheng , Liang Zhaoping , Huang Shujian , Wen Feng 
Published: September 2024

ABSTRACT

Avian migration is a global phenomenon that transcends geographical boundaries. These migratory birds serve as unwitting carriers of diverse Gammacoronaviruses (γ-CoVs) and Deltacoronaviruses (δ-CoVs). While recombination events have been documented among γ-CoVs in avian species and β-CoVs in mammals, evidence for recombination between CoVs of distinct genera remains limited. This minireview examines the prevalence of CoVs in both domestic waterfowl (ducks and geese) and wild bird populations inhabiting various regions. We investigate the dissemination patterns of γ-CoVs and δ-CoVs among these populations, highlighting their shared characteristics. Furthermore, the review explores the intricate web of cross-species transmission of δ-CoVs from wild birds to mammals, with a particular focus on pigs. Understanding the distinct features of CoVs harbored by waterfowl and wild birds and their potential for cross-species transmission is crucial for preparedness and response to future CoV epidemics.
The Rise of Sustainability Provisions in International Investment Agreements
Authors: Dotzauer Marius , Biber-Freudenberger Lisa , Dietz Thomas 
Published: September 2024

Abstract
There is a lively debate about whether international investment agreements (IIAs)—the central instruments governing foreign direct investment—are compatible with sustainable development objectives. One critical argument is that investment treaty provisions limit governments’ policy space to achieve transitions toward sustainability and may lead to costly legal disputes. Against this background, governments, international organizations, and other stakeholders have begun to consider options for modernizing international investment law by including provisions related to sustainable development in the treaties. In this article, we examine to what extent and why states include sustainability references in IIAs. Our automated text analysis of 2,083 bilateral investment treaties and 374 other treaties with investment provisions shows that the number of sustainability references has risen sharply recently. Drawing on the literature on issue linkage in economic agreements, we test different explanations for the changes in the treaty language. We find that the level of democracy among treaty parties and the experience of being sued in the past are strong drivers of the described trend.
Neural Correlates of Visual Feature Binding
Authors: Ro Tony , Pierce Allison M. , Porubanova Michaela , Lucas Miriam San 
Published: September 2024

Abstract
We perceive visual objects as unified although different brain areas process different features. An attentional mechanism has been proposed to be involved with feature binding, as evidenced by observations of binding errors (i.e., illusory conjunctions) when attention is diverted. However, the neural underpinnings of this feature binding are not well understood. We examined the neural mechanisms of feature binding by recording EEG during an attentionally demanding discrimination task. Unlike prestimulus alpha oscillatory activity and early ERPs (i.e., the N1 and P1 components), the N1pc, reflecting stimulus-evoked spatial attention, was reduced for errors relative to correct responses and illusory conjunctions. However, the later sustained posterior contralateral negativity, reflecting visual short-term memory, was reduced for illusory conjunctions and errors compared with correct responses. Furthermore, binding errors were associated with distinct posterior lateralized activity during a 200- to 300-msec window. These results implicate a temporal binding window that integrates visual features after stimulus-evoked attention but before encoding into visual short-term memory.
Event Segmentation Promotes the Reorganization of Emotional Memory
Authors: Laing Patrick A. F. , Dunsmoor Joseph E. 
Published: September 2024

Abstract
Event boundaries help structure the content of episodic memories by segmenting continuous experiences into discrete events. Event boundaries may also serve to preserve meaningful information within an event, thereby actively separating important memories from interfering representations imposed by past and future events. Here, we tested the hypothesis that event boundaries organize emotional memory based on changing dynamics as events unfold. We developed a novel threat-reversal learning task whereby participants encoded trial-unique exemplars from two semantic categories across three phases: preconditioning, fear acquisition, and reversal. Shock contingencies were established for one category during acquisition (CS+) and then switched to the other during reversal (CS−). Importantly, reversal was either separated by a perceptible event boundary (Experiment 1) or occurred immediately after acquisition, with no perceptible context shift (Experiment 2). In a surprise recognition memory test the next day, memory performance tracked the learning contingencies from encoding in Experiment 1, such that participants selectively recognized more threat-associated CS+ exemplars from before (retroactive) and during acquisition, but this pattern reversed toward CS− exemplars encoded during reversal. By contrast, participants with continuous encoding—without a boundary between conditioning and reversal—exhibited undifferentiated memory for exemplars from both categories encoded before acquisition and after reversal. Further analyses highlight nuanced effects of event boundaries on reversing conditioned fear, updating mnemonic generalization, and emotional biasing of temporal source memory. These findings suggest that event boundaries provide anchor points to organize memory for distinctly meaningful information, thereby adaptively structuring memory based on the content of our experiences.
Multi-level Shared Knowledge Guided Learning for Knowledge Graph Completion
Authors: Shan Yongxue , Zhou Jie , Peng Jie , Zhou Xin , Yin Jiaqian , Wang Xiaodong 
Published: September 2024

Abstract
In the task of Knowledge Graph Completion (KGC), the existing datasets and their inherent subtasks carry a wealth of shared knowledge that can be utilized to enhance the representation of knowledge triplets and overall performance. However, no current studies specifically address the shared knowledge within KGC. To bridge this gap, we introduce a multi-level Shared Knowledge Guided learning method (SKG) that operates at both the dataset and task levels. On the dataset level, SKG-KGC broadens the original dataset by identifying shared features within entity sets via text summarization. On the task level, for the three typical KGC subtasks—head entity prediction, relation prediction, and tail entity prediction—we present an innovative multi-task learning architecture with dynamically adjusted loss weights. This approach allows the model to focus on more challenging and underperforming tasks, effectively mitigating the imbalance of knowledge sharing among subtasks. Experimental results demonstrate that SKG-KGC outperforms existing text-based methods significantly on three well-known datasets, with the most notable improvement on WN18RR (MRR: 66.6%→ 72.2%, Hit@1: 58.7%→67.0%).
Innovating through Nature-Positive Engineering: How Can We Move Forward?
Authors: Bridges Todd , Jones Shana , Shudtz Matthew 
Published: September 2024

Abstract
Nature-based solutions – approaches that take advantage of existing aspects of the natural landscape and/or imitate natural processes through engineering and design to produce environmental and societal value – will be key to actively restoring the ocean’s ability to sustain human societies. Nature-based solutions upend the dominant paradigm informing engineering decision-making, which is ultimately founded upon the idea that humans can use hard, structural approaches to control nature and that degradation of natural functions can be offset. In the United States, the current legal tools and policy regimes to protect the environment and manage land use decisions were designed for the traditional engineering era. Pointing to the US Clean Water Act as an example, the article draws lessons learned from its successes and limitations, emphasising that future policy frameworks should clearly identify that encompassing nature as a way to enhance functioning and design is a high priority.
Precising E-waste Generation for Economic Recycling
Authors: Sharma Himanshu , Kumar Harish 
Published: September 2024

With enhanced technological advancements, digital transformation and globalisation, there has been a significant rise in the amount of electronic waste (e-waste), posing a threat to the global economy and environment. The study deploys a grey prediction model to forecast the amount of e-waste generation by 2026 in India. The precise data generated can be further used to calculate operation costs, workforce requirements, collection time, warehouse and landfills needed for economical recycling of e-waste. JEL Codes: A1, C8, Q5
Children and Adolescents With Sickle Cell Disease and Skull Infarction: A Systematic Review
Authors: Perez Alexia M. , Garcia-Guaqueta Danna P. , Setty Bindu N. , Neri Caitlin , Torres Alcy R. 
Published: September 2024

Introduction Skull infarction is an uncommonly reported complication of sickle cell disease. We aimed to characterize the clinical and imaging features of skull infarction in pediatric patients with sickle cell disease. Methods We searched the PubMed database for case reports on skull bone infarction in pediatric patients with sickle cell disease. Out of 67 records retrieved, 15 met inclusion criteria, and a 16th case reported by the senior author was included. We extracted and analyzed clinical and imaging data. Results The most common symptom at onset was headache (88%). Bilateral skull infarction (50%) and parietal bone involvement (82%) were frequent imaging findings. Epidural hematoma developed in 65% of the cases, 30% of patients required drainage, and exchange infusion was reported in 18%. No fatal outcomes were reported. Conclusions Skull infarction is a potentially severe complication of sickle cell disease presenting unique clinical challenges. Acute headaches should raise suspicion for this condition and may require additional investigation.
Assessing novel partner antimicrobials to protect ceftriaxone against gonococcal resistance: An in vitro evaluation
Authors: Abdellati Saïd , Gestels Zina , Baranchyk Yuliia , de Block Tessa , Van Den Bossche Dorien , De Baetselier Irith , Manoharan-Basil Sheeba Santhini , Kenyon Chris 
Published: September 2024

Background The emergence of ceftriaxone-resistant Neisseria gonorrhoeae poses a significant threat to existing treatment regimens. Our study aimed to assess the efficacy of antimicrobials that could be combined with ceftriaxone to reduce the probability of ceftriaxone resistance emerging and spreading in N. gonorrhoeae. Methods and Results Broth microdilution was used to determine the minimal inhibitory concentrations (MICs) for a panel of ceftriaxone-resistant (WHO X, Y, Z) and ceftriaxone-susceptible (WHO L, N, P) N. gonorrhoeae WHO reference strains for the following antimicrobials: ceftriaxone, doxycycline, azithromycin, zoliflodacin, fosfomycin, pristinamycin, ramoplanin, gentamicin and NAI-107. The MICs for zoliflodacin and pristinamycin for all strains were lower than or equal to the available breakpoints. A checkerboard assay was used to determine the drug-drug combination effect, which showed either an indifferent or an additive effect for all the combinations tested with ceftriaxone. Conclusions The low MICs of zoliflodacin and pristinamycin for the three ceftriaxone-resistant strains suggest that these antimicrobials could be used as partner drugs with ceftriaxone to reduce the probability of ceftriaxone resistance spreading in areas with a high prevalence of ceftriaxone resistance.
Development of Prediction Model for 5-year Survival of Colorectal Cancer
Authors: Nopour Raoof 
Published: September 2024

Objectives: This study aims to introduce a prediction model based on a machine learning approach as an efficient solution for prediction purposes to better prognosis and increase CRC survival. Methods: In the current retrospective study, we used the data of 1062 CRC cases to analyse and establish a prediction model for the 5-year CRC survival. The machine learning algorithms were used to develop prediction models, including random Forest, XG-Boost, bagging, logistic regression, support vector machine, artificial neural network, decision tree, and K-nearest neighbours. Results: The current study revealed that the XG-Boost with AU-ROC of 0.906 and 0.813 for internal and external conditions gave us better insight into predictability and generalizability than other algorithms. Conclusion: XG-Boost can be utilised as a knowledge source for implementing intelligent systems as an assistive tool for clinical decision-making in healthcare settings to improve prognosis and increase CRC survival through various clinical solutions that doctors can achieve.
What do Climate Change, Nutrition, and the Environment Have to do With Mental Health?
Authors: Sugden Steven G. , Merlo Gia 
Published: September 2024

Climate change is becoming the most significant global challenge and must be addressed on a global scale. At the time that this article is being written, the planetary heat in 2023 was the hottest on record. Similarly, the World Health Organization reports that 99% of the world’s population lives in regions of unhealthy air pollution. Similarly, depression has become one of the leading causes of global mental and physical disabilities, and the impact of depression is predicted to only worsen over the next 25 years. It is interesting to note that climate experts often overlook the adoption of nutrition via a whole plant-based diet as a solution to both mental illness and climate change. In this review, we will touch upon the role of nutrition in gut microbiota and mental health, the impact diet has on greenhouse gases, the role of ultra-processed food, and environmental factors such as air pollution and increasing planetary heat and their growing impacts on mental health. In the end, the promotion of plant-based foods has the potential to improve personal mental and physical health while improving planetary health.
Reliable Anatomic Femoral Tunnel Positioning for Anterior Cruciate Ligament Reconstruction Using a Novel Femoral Aiming Guide
Authors: Khan Shehzaad A. , Spalding Tim 
Published: September 2024

Background: Anterior cruciate ligament (ACL) tunnel placement has been long debated for many years. Femoral tunnel mal-position is the commonest technical error resulting in early ACL laxity and failure. There are many different methods to achieve accurate femoral tunnel position. In this video, we describe use of a novel femoral jig aiming device to drill a reliably and easily reproducible femoral tunnel for primary ACL reconstruction (ACLR). Indications: This femoral jig aiming device is indicated for all patients undergoing primary ACLR with any graft chosen by the surgeon. This jig is particularly useful for the inexperienced and low volume ACLR surgeon. Technique Description: An appropriate graft is harvested and prepared according to preferred techniques and the diameter of the graft to be inserted in the femoral tunnel is measured. The femoral notch is prepared, ensuring appropriate tissue is cleared to view the apex of the deep cartilage (ADC). The Infinity anteromedial (AM) femoral guide (Conmed), is inserted through the AM portal and hooked onto the notch just proximal to the ADC. In deep flexion, the guide wire is advanced and the tunnel reamed, aiming to preserve 2.0 to 2.5 mm of bone. Results: 19 consecutive patients were operated on. There were no complications during the intra- and postoperative period. There have been no reported failures or graft ruptures. All tunnels (100%) were centered in the footprint. The mean tunnel position was 25:20 on the superimposed Bernard-Hertel grid with tight grouping. Discussion/Conclusion: We have shown that this new femoral guide accurately locates the femoral tunnel close to the AM bundle position and gives a reliable and reproducible femoral tunnel position, thereby reducing the risk of intra-operative error. This may assist accuracy of tunnel position for surgeons starting out performing ACLR or for low-volume surgeons. Patient Consent Disclosure Statement: The author(s) attests that consent has been obtained from any patient(s) appearing in this publication. If the individual may be identifiable, the author(s) has included a statement of release or other written form of approval from the patient(s) with this submission for publication.
Adherence-enhancing interventions for pharmacological and oxygen therapy in patients with COPD: a systematic review and component network meta-analyses
Authors: Ammous Omar , Kampo Regina , Wollsching-Strobel Maximilian , Zimmermann Maximilian , Andreas Stefan , Friede Tim , Kroppen Doreen , Stanzel Sarah , Salem Susanna , Windisch Wolfram , Mathes Tim 
Published: September 2024

IntroductionAdherence to COPD management strategies is complex, and it is unclear which intervention may enhance it.ObjectivesWe aim to evaluate the effectiveness of adherence-enhancing interventions, alone or compared to interventions, for patients with COPD.MethodsThis review comprises a component network meta-analysis with a structured narrative synthesis. We searched MEDLINE, Embase, CENTRAL, CINAHL and trial registries on 9 September 2023. We included controlled studies that explored adherence in patients with COPD. Two review authors independently performed the study selection, data extraction and the risk of bias assessment. We involved patients with COPD in developing this systematic review through focus group interviews and displayed the findings in pre-designed logic models.ResultsWe included 33 studies with 5775 participants. We included 13 studies in the component network meta-analysis that explored adherence. It was mainly assessed through questionnaires. As a continuous outcome, there was a tendency mainly for education (standardised mean difference 1.26, 95% CI 1.13–1.38, very low certainty of evidence) and motivation (mean difference 1.85, 95% CI 1.19–2.50, very low certainty of evidence) to improve adherence. As a dichotomous outcome (e.g.adherent/non-adherent), we found a possible benefit with education (odds ratio 4.77, 95% CI 2.25–10.14, low certainty of evidence) but not with the other components. We included six studies that reported quality of life in the component network meta-analysis. Again, we found a benefit of education (mean difference −9.70, 95% CI −10.82– −8.57, low certainty of evidence) but not with the other components.ConclusionsEducation may improve adherence and quality of life in COPD patients. Patient focus group interviews indicated that interventions that strengthen patients’ self-efficacy and help them to achieve individual goals are the most helpful.