bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of pericardium patch graft thickness in patients with Ahmed glaucoma valve implantation: an anterior segment OCT study
Authors: Akbas Yusuf Berk , Alagoz Nese , Sari Cem , Altan Cigdem , Yasar Tekin 
Published: March 2024

Abstract
Purpose
To evaluate the changes in thickness of tissues, specifically the pericardium patch graft (PPG) covering the silicone tube in Ahmed Glaucoma Valve (AGV) surgery.

Study design
Prospective observational study.

Methods
This study included cases with refractory glaucoma that underwent AGV implantation with PPG coverage. Conjunctival epithelium, stroma and PPG thickness covering the tube were measured using anterior segment optical coherence tomography (AS-OCT) at 1, 6 and 12 months. Additionally, the same measurements were taken 1500 µm away from the tube as a control for the central measurements.

Results
Twenty-seven eyes of 27 patients were evaluated in the study. Although PPG thickness decreased significantly in both regions, the amount of reduction was more pronounced centrally. Centrally, the reduction rate was 21.2% and 34.8% during the 1-6 months period and 6-12 months period, while peripherally it was 3.5% and 5.1%, respectively. No change was observed in the thickness of the epithelium during the follow-up period. There was a significant thinning of the stroma in the central and peripheral regions during the 1-6 months period (30.5% and 17%, respectively). No cases of exposure were observed during the follow-up period.

Conclusion
Although the most evident thinning of the layers covering the tube was observed in the early postoperative period, PPG showed a stable decrease even in the late period. The progressive reduction in the PPG thickness observed also in the peripheral region indicates that factors beyond mechanical forces contribute to this degenerative process. AS-OCT could be a valuable non-invasive tool in clarifying this process.
Re-evaluating GPT-4’s bar exam performance
Authors: Martínez Eric 
Published: March 2024

AbstractPerhaps the most widely touted of GPT-4’s at-launch, zero-shot capabilities has been its reported 90th-percentile performance on the Uniform Bar Exam. This paper begins by investigating the methodological challenges in documenting and verifying the 90th-percentile claim, presenting four sets of findings that indicate that OpenAI’s estimates of GPT-4’s UBE percentile are overinflated. First, although GPT-4’s UBE score nears the 90th percentile when examining approximate conversions from February administrations of the Illinois Bar Exam, these estimates are heavily skewed towards repeat test-takers who failed the July administration and score significantly lower than the general test-taking population. Second, data from a recent July administration of the same exam suggests GPT-4’s overall UBE percentile was below the 69th percentile, and$$\sim$$∼48th percentile on essays. Third, examining official NCBE data and using several conservative statistical assumptions, GPT-4’s performance against first-time test takers is estimated to be$$\sim$$∼62nd percentile, including$$\sim$$∼42nd percentile on essays. Fourth, when examining only those who passed the exam (i.e. licensed or license-pending attorneys), GPT-4’s performance is estimated to drop to$$\sim$$∼48th percentile overall, and$$\sim$$∼15th percentile on essays. In addition to investigating the validity of the percentile claim, the paper also investigates the validity of GPT-4’s reported scaled UBE score of 298. The paper successfully replicates the MBE score, but highlights several methodological issues in the grading of the MPT + MEE components of the exam, which call into question the validity of the reported essay score. Finally, the paper investigates the effect of different hyperparameter combinations on GPT-4’s MBE performance, finding no significant effect of adjusting temperature settings, and a significant effect of few-shot chain-of-thought prompting over basic zero-shot prompting. Taken together, these findings carry timely insights for the desirability and feasibility of outsourcing legally relevant tasks to AI models, as well as for the importance for AI developers to implement rigorous and transparent capabilities evaluations to help secure safe and trustworthy AI.
A whole food, plant-based randomized controlled trial in metastatic breast cancer: feasibility, nutrient, and patient-reported outcomes
Authors: Campbell Erin K. , Campbell Thomas M. , Culakova Eva , Blanchard Lisa , Wixom Nellie , Guido Joseph J. , Fetten James , Huston Alissa , Shayne Michelle , Janelsins Michelle C. , Mustian Karen M. , Moore Richard G. , Peppone Luke J. 
Published: March 2024

Abstract
Purpose
Quality of life (QOL) is among the most important outcomes for women with metastatic breast cancer (MBC), and it predicts survival. QOL is negatively impacted by cognitive impairment, fatigue, and weight gain. We assessed whether a whole food, plant-based (WFPB) diet-promoting weight loss is feasible and might improve QOL.

Methods
Women with MBC on stable systemic treatments were randomized 2:1 to 1) WFPB dietary intervention (n = 21) or 2) usual care (n = 11) for 8 weeks. Participants attended weekly education visits and consumed an ad libitum WFPB diet (3 prepared meals/day provided). Patient-reported outcomes and 3-day food records were assessed at baseline and 8 weeks. The effects of WFPB diet on changes in outcomes were assessed by analysis of covariance model controlling for baseline.

Results
20 intervention and 10 control participants completed the trial. Intervention participants were highly adherent to the WFPB diet (94.3 % total calories on-plan). Intervention group nutrient intakes changed significantly including dietary fat (35.8 % to 20.4 % percent calories from fat, p < 0.001) and fiber content (12.7 to 30.8 g fiber/1000 kcal, p < 0.001). Perceived cognitive function (FACT-Cog total + 16.1; 95 % confidence interval [CI] = 0.8–31.7; p = 0.040) and emotional well-being (FACT-B emotional well-being subscale + 2.3; CI = 0.5–4.1; p = 0.016) improved in the WFPB versus the control group. Fatigue, measured by the BFI, improved within the WFPB group for fatigue severity (M = 4.7 ± 2.5[SD] to 3.7 ± 2.3, p = 0.047) and fatigue at its worst (5.8 ± 2.8 to 4.4 ± 2.4, p = 0.011).

Conclusions
Significant dietary changes in this population are feasible and may improve QOL by improving treatment-related symptoms. Additional study is warranted.
Trial Registration: ClinicalTrials.gov identifier: NCT03045289. Registered 7 February 2017.
A longitudinal multi-modal dataset for dementia monitoring and diagnosis
Authors: Gkoumas Dimitris , Wang Bo , Tsakalidis Adam , Wolters Maria , Purver Matthew , Zubiaga Arkaitz , Liakata Maria 
Published: March 2024

AbstractDementia affects cognitive functions of adults, including memory, language, and behaviour. Standard diagnostic biomarkers such as MRI are costly, whilst neuropsychological tests suffer from sensitivity issues in detecting dementia onset. The analysis of speech and language has emerged as a promising and non-intrusive technology to diagnose and monitor dementia. Currently, most work in this direction ignores the multi-modal nature of human communication and interactive aspects of everyday conversational interaction. Moreover, most studies ignore changes in cognitive status over time due to the lack of consistent longitudinal data. Here we introduce a novel fine-grained longitudinal multi-modal corpus collected in a natural setting from healthy controls and people with dementia over two phases, each spanning 28 sessions. The corpus consists of spoken conversations, a subset of which are transcribed, as well as typed and written thoughts and associated extra-linguistic information such as pen strokes and keystrokes. We present the data collection process and describe the corpus in detail. Furthermore, we establish baselines for capturing longitudinal changes in language across different modalities for two cohorts, healthy controls and people with dementia, outlining future research directions enabled by the corpus.
TCMeta: a multilingual dataset of COVID tweets for relation-level metaphor analysis
Authors: Brglez Mojca , Zayed Omnia , Buitelaar Paul 
Published: March 2024

AbstractThe COVID pandemic spurred the use of various metaphors, some very common and universal, others depending on the language, country and culture. The use of metaphors by the general public, especially in languages other than English, has not yet been sufficiently investigated, one of the reasons being the lack of resources and automatic tools for metaphor analysis. To fill this gap, we introduce TCMeta, a dataset of tweets annotated for metaphors around COVID-19, in two languages from ten different countries. The dataset contains metaphoric phrases covering four source domains. Furthermore, we introduce a semi-automatic methodology to annotate more than 2000 tweets in English and Slovene. To the best of our knowledge, this is the first multilingual semi-automatically compiled dataset of user-generated texts aimed at investigating metaphorical language about the pandemic. It is also the first Slovene dataset of tweets annotated for metaphors.
Democratic Climate Policies with Overlapping Generations
Authors: Goussebaïle Arnaud 
Published: March 2024

AbstractAn extensive climate policy literature provides various recommendations for mitigating climate change, but these recommendations are not supported democratically, since the models employed consider either infinitely-lived individuals or normative social objectives (or both). In contrast, the present paper provides policy recommendations capable of incorporating democratic processes. I develop an overlapping generation model with political process micro-foundations and show how democratic climate policies are interconnected with other democratic policies. Time inconsistent social objectives combined with commitment issues lead to an inefficient tax on capital accumulation and a climate policy below the efficient level; while suppressing the tax on capital accumulation generates a climate policy even further below the efficient level. I derive a novel politico-economic Keynes–Ramsey rule for the market interest rate, which is useful for calculating the climate policy level. I show that individual pure time preference, individual altruism toward descendants, and young generation political power are key determinants of democratic climate policy ambition.
Do Commercial Place Managers Explain Crime Across Places? Yes and NO(PE)
Authors: Tucker Riley , O’Brien Daniel T. 
Published: March 2024

AbstractObjectivesSome criminologists of place have argued that property owners and place managers are the key actors exerting guardianship over crime and driving differences in crime across places, giving rise to the “Neighborhoods Out of Places Explanation” (NOPE) theory of crime. However, research to date has yet to fully evaluate if crime statistically varies across properties, their owners, or surrounding geographies.MethodsData scraped from Yelp.com is used to identify 1070 land parcels that had at least one business receiving reviews from 2014 to 2020. 911 dispatches for disturbances are linked to parcels and measured as the rate of events per Yelp reviewer in the average year. Hierarchical negative binomial modeling-based variance decomposition techniques are used to evaluate how variation in disturbance rates is distributed across parcels, owners, census blocks, and census tracts. Hierarchical negative binomial models are used to assess the correlates of disturbance rates. Sensitivity analyses assess the correlates of disturbance rates using a single-level negative binomial model with bootstrapped standard errors as well as an alternative outcome measure based on count of 911 events.ResultsCommercial disturbance rates vary across parcels, parcel owners, and blocks. At the parcel level, higher Yelp ratings are associated with lower disturbance rates while parcel square footage and land value are associated with increased disturbance rates. Additionally, parcel-level crime disturbance rates are explained by block features such as poverty, violent crime, and the number of Yelp restaurants on the block.ConclusionsParcel, owner, and block features can all help explain why some restaurants have more crime than others. Future research should build on the place management perspective by investigating the wider breadth of potential actors who may exert guardianship over properties while acknowledging that offenders and targets systematically vary across geographies, making effective guardianship more difficult in some locations than others.
Structure-based inhibition of acetylcholinesterase and butyrylcholinesterase with 2-Aryl-6-carboxamide benzoxazole derivatives: synthesis, enzymatic assay, and in silico studies
Authors: Kuzu Burak , Alagoz M. Abdullah , Demir Yeliz , Gulcin Ilhami , Burmaoglu Serdar , Algul Oztekin 
Published: March 2024

Abstract
An important research topic is the discovery of multifunctional compounds targeting different disease-causing components. This research aimed to design and synthesize a series of 2-aryl-6-carboxamide benzoxazole derivatives that inhibit cholinesterases on both the peripheral anionic and catalytic anionic sides. Compounds (7–48) were prepared from 4-amino-3-hydroxybenzoic acid in three steps. The Ellman test, molecular docking with Maestro, and molecular dynamics simulation studies with Desmond were done (Schrodinger, 12.8.117). Compound 36, the most potent compound among the 42 new compounds synthesized, had an inhibitory concentration of IC50 12.62 nM for AChE and IC50 25.45 nM for BChE (whereas donepezil was 69.3 nM and 63.0 nM, respectively). Additionally, compound 36 had docking values ​​of − 7.29 kcal/mol for AChE and − 6.71 kcal/mol for BChE (whereas donepezil was − 6.49 kcal/mol and − 5.057 kcal/mol, respectively). Furthermore, molecular dynamics simulations revealed that compound 36 is stable in the active gorges of both AChE (average RMSD: 1.98 Å) and BChE (average RMSD: 2.2 Å) (donepezil had average RMSD: 1.65 Å and 2.7 Å, respectively). The results show that compound 36 is a potent, selective, mixed-type dual inhibitor of both acetylcholinesterase and butyrylcholinesterase. It does this by binding to both the catalytically active and peripheral anionic sites of cholinesterases at the same time. These findings show that target compounds may be useful for establishing the structural basis for new anti-Alzheimer agents.

Graphical abstract
Central Attention with Multi-Graphs for Image Annotation
Authors: Liu Baodi , Liu Yan , Shao Qianqian , Liu Weifeng 
Published: March 2024

AbstractIn recent decades, the development of multimedia and computer vision has sparked significant interest among researchers in the field of automatic image annotation. However, much of the research has primarily focused on using a single graph for annotating images in semi-supervised learning. Conversely, numerous approaches have explored the integration of multi-view or image segmentation techniques to create multiple graph structures. Yet, relying solely on a single graph proves to be challenging, as it struggles to capture the complete manifold of structural information. Furthermore, the computational complexity of building multiple graph structures based on multi-view or image segmentation is substantial and time-consuming. To address these issues, we propose a novel method called "Central Attention with Multi-graphs for Image Annotation." Our approach emphasizes the critical role of the central image region in the annotation process. Remarkably, we demonstrate that impressive performance can be achieved by leveraging just two graph structures, composed of central and overall features, in semi-supervised learning. To validate the effectiveness of our proposed method, we conducted a series of experiments on benchmark datasets, including Corel5K, ESPGame, and IAPRTC12. These experiments provide empirical evidence of our method’s capabilities.
XRD and UV–Vis studies of cellulose acetate film blended with different concentrations of nano-metal oxide
Authors: Ezzat Dina , Youssif Mortda , Elhaes Hanan , El-Nahass Mahmoud 
Published: March 2024

AbstractMolybdenum Trioxide nanoparticle (MoO3-NPs) was introduced to Cellulose acetate (CA) biopolymer with different concentration using casting process by dispersed MoO3-NPs [0.0, 0.25, 0.5 and 1.0 wt%]. Molecular structure of samples has been studied using XRD and UV–Vis. the data shown by X-ray results indicated the amorphous nature of the pure polymer. Some peaks are appeared as a result of the addition of MoO3-NPs which indicate that samples were partially crystallized. The crystallite size of nano-metal oxide was calculated for blended samples by Size–Strain Plot method which was found to increase with increasing the concentration of MoO3. UV–Vis results indicate that there exist two indirect energy band gaps; Onset band gap which observed to decreases from 1.3 eV for pure polymer to 0.78 eV for polymer blended with 1.0 wt% MoO3-NPs and HOMO–LOMO band gap which observed to decrease from 3.23 eV for pure polymer to 2.89 eV for polymer blended with 1.0 wt% MoO3-NPs. This indicate that the addition of nano-metal oxide improve the optical conduction of CA. Urbach energy was observed to increase with increasing MoO3-NPs from 0.27 eV for pure CA to 0.32 eV for 1.0 wt% MoO3-NPs concentration which may be occurred due to the creation localized states at the band gap as a result of the addition of MoO3-Nps.
Reciprocal relationships among reading and vocabulary over time: a longitudinal study from grade 1 to 5
Authors: Killingly Callula , Graham Linda J. , Tancredi Haley , Snow Pamela 
Published: March 2024

AbstractReading comprehension is contingent on both oral language comprehension and word-level reading ability, skills that are thought to be intrinsically related in the early school years. However, while previous studies examining bidirectional relationships among oral vocabulary and reading development have generally found an association between word recognition and subsequent vocabulary skills, they have yielded inconsistent results regarding whether vocabulary is linked to later word recognition. In this longitudinal study (n = 176), we assessed reciprocal relationships between expressive and receptive vocabulary and word recognition measured yearly from Grade 1 to 5. We compared results from a cross-lagged panel model (CLPM) to a random-intercept cross-lagged panel model (RI-CLPM), an analytic approach which permits disaggregation of variance between children in the constructs of interest from year-to-year fluctuations within children. Expressive and receptive vocabulary were examined in separate models. Results showed that the RI-CLPMs provided a better fit to the data in contrast to the CLPMs, and provided evidence of reciprocal relationships between word recognition and both receptive and expressive vocabulary. Significant between-child variance was shown for vocabulary but not word recognition. These findings confirm that reading and vocabulary skills build upon one another across the primary years, and each is an important area of classroom instruction focus. Early and regular screening measures may serve to inform the development of timely and appropriate support and intervention.
Infrared and visible image fusion in a rolling guided filtering framework based on deep feature extraction
Authors: Cheng Wei , Lin Bing , Cheng Liming , Cui Yong 
Published: March 2024

AbstractTo preserve rich detail information and high contrast, a novel image fusion algorithm is proposed based on rolling-guided filtering combined with deep feature extraction. Firstly, input images are filtered to acquire various scales decomposed images using rolling guided filtering. Subsequently, PCANet is introduced to extract weight maps to guide base layer fusion. For the others layer, saliency maps of input images are extracted by a saliency measure. Then, the saliency maps are optimized by guided filtering to guide the detail layer fusion. Finally, the final fusion result are reconstructed by all fusion layers. The experimental fusion results demonstrate that fusion algorithm in this study obtains following advantages of rich detail information, high contrast, and complete edge information preservation in the subjective evaluation and better results in the objective evaluation index. In particular, the proposed method is 16.9% ahead of the best comparison result in the SD objective evaluation index.
Short- and long-term stability of synthetic cathinones and dihydro-metabolites in human urine samples
Authors: Aldubayyan Abdulaziz A. , Castrignanò Erika , Elliott Simon , Abbate Vincenzo 
Published: March 2024

Abstract
Purpose
Synthetic cathinones constitute the second largest group of new psychoactive substances, which are often used for recreational purposes and reported in toxicological analysis. Various factors may influence the stability of synthetic cathinones between sampling and analysis, and therefore, stability studies are required to determine the best storage conditions as well as extend the period of detection.

Methods
This study involved sixteen synthetic cathinones and ten dihydro-metabolites spiked in human urine to evaluate the stability under common storage conditions to imitate real forensic toxicology samples. The samples were stored at either room temperature (22–23 °C) for up to 3 days, refrigerated (4 °C) for up to 14 days or frozen (–40 °C) for up to 12 months, and analyzed in triplicate using a validated liquid chromatography–tandem mass spectrometry method.

Results
Analytes’ concentrations decreased over time, although slower when stored frozen. All analytes remained stable (> 80%) for 1 month when stored frozen before losses in content were more apparent for some compounds, depending on their chemical structure. Under all storage conditions, the highest instability was observed for analytes containing halogens (i.e., chlorine or fluorine). Thus, halogenated analytes were further investigated by using liquid chromatography coupled to quadruple time-of-flight mass spectrometry to attempt identifying degradation products.

Conclusions
Irrespective of parent analytes, dihydro-metabolites had improved stability at each tested temperature, which highlights their importance as appropriate urine biomarkers when retesting is required after a long period of storage.