bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of edible oil types used in packaged foods in Türkiye with principal component analysis
Authors: Icyer Necattin Cihat , Kuran Nesrin 
Published: January 2024

AbstractIn our rapidly changing world, where consumers’ expectations for healthy food are on the rise, the edible oil content in packaged foods has become a central focus. Among various types of oils, palm oil is often regarded as one of the most contentious. This research study aimed to identify the types of fats present in packaged food products in Türkiye and examined the reasons for their utilization. A total of 1380 packaged food items, classified into 11 categories, were scrutinized, and the types of oils within their ingredients were classified using principal component analysis and hierarchical cluster analysis. The study's results have determined that among packaged food products available in Türkiye, 50.1% contain palm oil, 30.4% contain sunflower oil, 16.4% contain canola oil, 14.9% contain cottonseed oil, 17.9% contain cocoa oil, and 12.6% contain coconut oil. In particular, it was determined that palm oil was used in 91% of bakery products, 81% of margarine and shortening products, and 71.3% of ice creams. Consequently, the data obtained in the context of ongoing debates regarding the fat content in packaged foods, especially concerning palm oil usage, will make a valuable contribution to the literature.
The emergence of natural products as potential therapeutics for male infertility
Authors: Li Xiuyun , Zhang Bin , Yang Huijun , Zhang Liuping , Lou Hongxiang , Zheng Shicun 
Published: January 2024

AbstractInfertility is a major reproductive health problem. Approximately 50% of all documented cases of infertility are attributable to male factors, such as poor testicular function and semen quality. The recent significant global decline in sperm counts has serious implications for male fertility, but the armamentarium for improving testicular function and semen quality is limited. Natural products have a wide range of activities and are a major source of drugs for disease prevention and treatment. To provide ideas and a theoretical basis for the research and development of therapeutic drugs for male infertility, this review summarizes natural products (mostly monomers) that have been shown to improve testicular function and semen quality and their possible mechanisms of action. These natural products primarily improve testicular function and semen quality via antioxidant, antiapoptotic, and anti‐inflammatory effects, in addition to increasing serum testosterone and reducing DNA damage in spermatozoa and testicular cells. Prospects for the application of natural products in the treatment of male infertility are discussed.
The social epistemology of eating disorders: How our gaps in understanding challenge patient care
Authors: Lee Ji‐Young 
Published: January 2024

AbstractIn this article, I argue that various epistemic challenges associated with eating disorders (EDs) can negatively affect the care of already marginalized patient groups with various EDs. I will first outline deficiencies in our understanding of EDs—in research, healthcare settings, and beyond. I will then illustrate with examples cases where discriminatory misconceptions about what EDs are, the presentation and treatment of EDs, and who gets EDs, instantiate obstacles for the treatment of various ED patient groups.
Design and implementation of an AI‐enabled visual report tool as formative assessment to promote learning achievement and self‐regulated learning: An experimental study
Authors: Liao Xiaofang , Zhang Xuedi , Wang Zhifeng , Luo Heng 
Published: January 2024

AbstractFormative assessment is essential for improving teaching and learning, and AI and visualization techniques provide great potential for its design and delivery. Using NLP, cognitive diagnostic and visualization techniques designed to analyse and present students' monthly exam data, we developed an AI‐enabled visual report tool comprising six modules and conducted an empirical study of its effectiveness in a high school biology classroom. A total of 125 students in a ninth‐grade biology course were assigned to a treatment group (n = 63) receiving AI‐enabled visual reports as the intervention and a control group (n = 62) receiving overall oral feedback from the teacher. We present the main statistical results of the within‐subjects design and the between‐subjects design respectively, to better capture the main findings. Repeated measures ANOVA revealed a significant interaction effect of intervention and time on learning achievement, and the paired‐sample Wilcoxon test indicated that the treatment group had experienced increasing learning anxiety (Cohen's d = 0.203, p = 0.046) and self‐efficacy (Cohen's d = 1.793, p = 0.000) over time. Moreover, we conducted a series of non‐parametric tests to compare the effects of AI‐enabled visual reports and teacher feedback, but found no significant differences except for an increased self‐efficacy (Cohen's d = 0.312, p = 0.046). Additionally, we had the students in the treatment group rate their favourable modules in the AI‐enabled visual report and provide evaluative feedback. The study results provide important insights into the design and implementation of effective formative assessment supported by artificial AI and visualization techniques.
Practitioner notesWhat is already known about this topic

Formative assessment is essential for improving teaching and learning.
Traditional formative assessment tools lack accurate data‐oriented assessment and usability.
AI and visualization techniques have great potential for formative assessment.
What this paper adds

This study designs and implements an AI‐enabled visual report tool that generates data‐driven, user‐friendly reports.
The AI‐enabled visual report can not only enhance students' learning achievement and self‐regulated learning over time but also increase their test anxiety.
The AI‐enabled visual report has a comparable effect with teacher feedback but leads to increased self‐efficacy.
Implications for practice and/or policy

We recommend using the AI‐enabled visual report in large‐size classes for its overall positive effects on both learning achievement and self‐regulated learning.
We recommend using the AI‐enabled visual report over teacher feedback for its capacity to enhance students' self‐efficacy.
We recommend prioritizing the modules of Performance Ranking, Personal Mastery and Knowledge Alert when designing the AI‐enabled visual report.
Ecological niche modelling and population genomics provide insights into the geographic and demographic ‘explosion’ of a non‐indigenous salmonid
Authors: Maduna Simo Njabulo , Aspholm Paul Eric , Hansen Ane‐Sofie Bednarczyk , Klütsch Cornelya F. C. , Hagen Snorre B. 
Published: January 2024

AbstractAimEffective management of non‐indigenous species requires knowledge of their dispersal factors and founder events. We aim to identify the main environmental drivers favouring dispersal events along the invasion gradient and to characterize the spatial patterns of genetic diversity in feral populations of the non‐native pink salmon within its epicentre of invasion in Norway.LocationMainland Norway and North Atlantic Basin.MethodsWe first conducted SDM using four modelling techniques with varying levels of complexity, which encompassed both regression‐based and tree‐based machine‐learning algorithms, using climatic data from the present to 2050. Then, we used the triple‐enzyme restriction‐site associated DNA sequencing (3RADseq) approach to genotype over 30,000 high‐quality single‐nucleotide polymorphisms to elucidate the patterns of genetic diversity and gene flow within the pink salmon putative invasion hotspot.ResultsWe discovered temperature‐ and precipitation‐related variables drove pink salmon distributional shifts across its non‐native ranges and that climate‐induced favourable areas will remain stable for the next 30 years. In addition, all SDMs identified north‐eastern Norway as the epicentre of the pink salmon invasion, and genomic data revealed that there was minimal variation in genetic diversity across the sampled populations at a genome‐wide level in this region. While utilizing a specific group of ‘diagnostic’ SNPs, we observed a significant degree of genetic differentiation, ranging from moderate to substantial, and detected four hierarchical genetic clusters concordant with geography.Main ConclusionsOur findings suggest that fluctuations in climate extreme events associated with ongoing climate change will likely maintain environmental favourability for the pink salmon outside its ‘native’/introduced ranges. Locally invaded rivers are themselves potential source populations of invaders in the ongoing secondary spread of pink salmon in Northern Norway. Our study shows that SDMs and genomic data can reveal species distribution determinants and provide indicators to aid in post‐control measures and potentially inferences about their success.
The rise and fall of paper money in Yuan China, 1260–1368
Authors: Guan Hanhui , Palma Nuno , Wu Meng 
Published: January 2024

AbstractFollowing the Mongol invasion of China, the Yuan (1260–1368) dynasty was the first political regime to introduce a precious metal standard and deploy paper money as the sole legal tender. Drawing on a new dataset on money issues, prices, warfare, imperial grants, taxation, natural disasters, and population, we find that a silver standard initially consolidated the Chinese currency market. However, persistent fiscal pressures eventually compelled rulers to ease the monetary standard, and a fiat standard was adopted. We show that inflation was high in the early and late periods of the dynasty but remained moderate for nearly half a century. We find that military pressure, particularly civil war, generated fiscal demands that led to the over‐issuance of money. By contrast, natural disasters and imperial grants did not trigger the over‐issue of money. Warfare was much more likely to increase paper money issues under the fiat standard than during the silver standard period.
A post hoc analysis of PROTECT VIII kids assessing long‐term efficacy and safety of damoctocog alfa pegol in adolescents with severe haemophilia A
Authors: Ahuja Sanjay , Biss Tina , Maas Enriquez Monika , Mancuso Maria Elisa , Steele MacGregor , Kenet Gili 
Published: January 2024

AbstractIntroductionThe safety and efficacy of the extended half‐life factor VIII (FVIII) product damoctocog alfa pegol (BAY 94‐9027, Jivi®) has been demonstrated in the PROTECT VIII Kids study (NCT01775618), where male previously‐treated patients (PTPs) aged <12 years old with severe haemophilia A and ≥ 50 exposure days (EDs) were treated prophylactically. The PROTECT VIII Kids extension study assessed the long‐term safety and efficacy of damoctocog alfa pegol in the same population.AimTo evaluate the long‐term impact of damoctocog alfa pegol in a post hoc subgroup analysis of adolescent patients in the PROTECT VIII Kids study and its extension from 12th birthday onwards.MethodsThe current analysis included PTPs aged ≥12 years old, who remained in the extension for ≥6 months following their 12th birthday. The observation period was defined as the time from 12th birthday to the end of the extension period; all data from this birthday were included whether in the main study or extension phase. The main efficacy variable was annualised bleeding rate (ABR) and the main safety variable was the frequency of inhibitor development.ResultsThis subgroup analysis comprised 25 patients. Median observation time after 12th birthday was 3.2 years. Median total/joint/spontaneous ABRs in the observation period were 1.7/0.7/0.3, respectively. Safety findings were consistent with those reported for the overall study population; no confirmed FVIII inhibitors or anti‐drug antibodies were reported.ConclusionsDamoctocog alfa pegol is efficacious with a favourable safety profile in adolescents with haemophilia A, supporting its long‐term use in children and adolescents.
Implications for cumulative and prolonged clinical improvement induced by cross‐linked hyaluronic acid: An in vivo biochemical/microscopic study in humans
Authors: Wang Frank , Do Thy Thy , Smith Noah , Orringer Jeffrey S. , Kang Sewon , Voorhees John J. , Fisher Gary J. 
Published: January 2024

AbstractIn photoaged human skin, type I collagen fragmentation impairs dermal extracellular matrix (ECM) integrity, resulting in collapsed/contracted fibroblasts with reduced type I procollagen synthesis. Injections of cross‐linked hyaluronic acid (CL‐HA) reverse these deleterious changes. To investigate the time course and effects of biochemical changes induced by injected CL‐HA, particularly whether fibroblast activation leads to accumulation/deposition of dermal collagen, we injected CL‐HA into photoaged skin of human participants over 60 years‐old and performed biochemical/microscopic analyses of skin samples. Beginning 1 week post‐injection and lasting 6–9 months, fibroblasts exhibited activation, including increased immunostaining and gene expression of markers of type I collagen synthesis, such as heat shock protein 47 and components of the transforming growth factor‐β pathway. At 1 week post‐injection, multiphoton microscopy revealed elongation/stretching of fibroblasts, indicating enhanced dermal mechanical support. At 4 weeks, second‐harmonic generation microscopy revealed thick collagen bundles densely packed around pools of injected CL‐HA. At 12 months, accumulation of thick collagen bundles was observed and injected CL‐HA remained present in substantial amounts. Thus, by occupying space in the dermal ECM, injected CL‐HA rapidly and durably enhances mechanical support, stimulating fibroblast elongation and activation, which results in thick, densely packed type I collagen bundles accumulating as early as 4 weeks post‐injection and continuing for at least a year. These observations indicate that early and prolonged clinical improvement following CL‐HA injection results from space‐filling and collagen deposition. As type I collagen has an estimated half‐life of 15 years, our data provide the foundations for optimizing the timing/frequency of repeat CL‐HA injections.
An AI knowledge‐based system for police assistance in crime investigation
Authors: Fernandez‐Basso Carlos , Gutiérrez‐Batista Karel , Gómez‐Romero Juan , Ruiz M. Dolores , Martin‐Bautista Maria J. 
Published: January 2024

AbstractThe fight against crime is often an arduous task overall when huge amounts of data have to be inspected, as is currently the case when it comes for example in the detection of criminal activity on the dark web. This work presents and describes an artificial intelligence (AI) based system that combines various tools to assist police or law enforcement agencies during their investigations, or at least mitigate the hard process of data collection, processing and analysis. The system is an early warning/early action system for crime investigation that supports law enforcement with different processes to collect and process data as well as having knowledge extraction tools. It helps to extract information during the investigation of a criminal case or even to detect possible criminal hotspots that may lead to further investigation or analysis of a criminal case Abu Al‐Haija et al. (2022, Electronics, 11, 556). The functionality of the proposed system is illustrated through several examples using data collected from the dark web, which includes advertisements offering firearms‐related products.
Deep convolutional neural networks information fusion and improved whale optimization algorithm based smart oral squamous cell carcinoma classification framework using histopathological images
Authors: Meer Momina , Khan Muhammad Attique , Jabeen Kiran , Alzahrani Ahmed Ibrahim , Alalwan Nasser , Shabaz Mohammad , Khan Faheem 
Published: January 2024

AbstractThe most prevalent type of cancer worldwide is mouth cancer. Around 2.5% of deaths are reported annually due to oral cancer in 2023. Early diagnosis of oral squamous cell carcinoma (OSCC), a prevalent oral cavity cancer, is essential for treating and recovering patients. A few computerized techniques exist but are focused on traditional machine learning methods, such as handcrafted features. In this work, we proposed a fully automated architecture based on Self‐Attention convolutional neural network and Residual Network information fusion and optimization. In the proposed framework, the augmentation process is performed on the training and testing samples, and then two developed deep models are trained. A self‐attention MobileNet‐V2 model is developed and trained using an augmented dataset. In parallel, a Self‐Attention DarkNet‐19 model is trained on the same dataset, whereas the hyperparameters have been initialized using the whale optimization algorithm (WOA). Features are extracted from the deeper layers of both models and fused using a canonical correlation analysis (CCA) approach. The CCA approach is further optimized using an improved WOA version named Quantum WOA that removes the irrelevant features and selects only important ones. The final selected features are classified using neural networks such as wide neural networks. The experimental process is performed on the augmented dataset that includes two sets: 100× and 400×. Using both sets, the proposed method obtained an accuracy of 98.7% and 96.3%. Comparison is conducted with a few state‐of‐the‐art (SOTA) techniques and shows a significant improvement in accuracy and precision rate.
Responses by benthic invertebrate community composition to dissolved organic matter in lakes decline substantially above a threshold concentration
Authors: Jane Stephen F. , Johnson Richard K. , Rose Kevin C. , Eklöv Peter , Weyhenmeyer Gesa A. 
Published: January 2024

Abstract

Dissolved organic matter (DOM), often measured as dissolved organic carbon (DOC), plays a fundamental role in influencing the structure and function of lake ecosystems. Due to the myriad ecosystem effects of DOM, widespread observations of long‐term increasing DOM concentrations have received much attention from ecologists. DOM positively influences primary production and consumer production at low concentrations due to the fertilising influence of bound nutrients. However, beyond a unimodal peak in production, a reduced light environment may result in a negative effect on production. This unimodal model has been largely developed and tested in lakes with low to moderate DOM concentrations (i.e., typically ≤10 mg/L DOC).

To understand ecological responses in lakes across a larger range in DOM concentrations, we examined the response of benthic invertebrate communities in 148 Swedish lakes with DOM concentrations ranging between 0.67 and 32.77 mg/L DOC.

We found that increasing DOM concentrations had a strong effect on invertebrate community composition below c. 10 mg/L. Across this range, abundances of individual taxa both increased and decreased, probably in response to environmental change induced by DOM. However, in lakes above this concentration, increasing DOM had minimal influence on community composition.

As DOM concentrations continue to increase, faunal communities in lakes below this 10 mg/L DOC threshold are likely to undergo substantial change whereas those above this threshold are likely to be minimally impacted.
Germany's public EV charging points: Analysing the 2023 state of expansion
Authors: Neumeier Stefan , Osigus Torsten 
Published: January 2024

AbstractThe European Climate Law sets a legally binding target of net zero greenhouse gas emissions by 2050. In this regard, in 2023 the EU Environmental Council decided that from 2035 onwards only CO2‐neutral new cars will be licensed in the European Union. Simultaneously, since the energy crisis caused by the Russian invasion of Ukraine, fuel prices increased in Germany. This has made more and more households think about purchasing an e‐car. However, not every household has the opportunity to install their own wallbox, and when travelling long distances, e‐car users are dependent on the availability of ample public charging stations. Against this background, with a special focus on rural areas, this paper considers the questions whether and where spatial inequalities in the accessibility of public charging stations might currently exist. To approach these questions, based on an empirical analysis of the 2023 official location data of public charging points in Germany, we examine the nationwide distribution, accessibility and available capacity of public charging stations in Germany at small‐scale from the point of view of the ‘household’ as well as those who travel by e‐car within Germany. In order to evaluate the location data of public charging stations we mainly use raster‐based accessibility analysis methods as well as isotropic kernel intensity estimates. We found that, in contrast to the common belief, the network of public charging stations is quite dense. However, taking a closer look reveals that the charging infrastructure in Germany has so far been tailored to the needs of intra‐regional travelers (commuting, shopping, leisure) rather than to those of the residential population with no access to their own wallbox (daily recharging in close proximity to one‘s home) or the mid‐ to long‐distance travelers.
How and why do doctors communicate diagnostic uncertainty: An experimental vignette study
Authors: Cox Caitríona , Hatfield Thea , Fritz Zoë 
Published: January 2024

AbstractBackgroundDiagnostic uncertainty is common, but its communication to patients is under‐explored. This study aimed to (1) characterise variation in doctors' communication of diagnostic uncertainty and (2) explore why variation occurred.MethodsFour written vignettes of clinical scenarios involving diagnostic uncertainty were developed. Doctors were recruited from five hospitals until theoretical saturation was reached (n = 36). Participants read vignettes in a randomised order, and were asked to discuss the diagnosis/plan with an online interviewer, as they would with a ‘typical patient’. Semi‐structured interviews explored reasons for communication choices. Interview transcripts were coded; quantitative and qualitative (thematic) analyses were undertaken.ResultsThere was marked variation in doctors' communication: in their discussion about differential diagnoses, their reference to the level of uncertainty in diagnoses/investigations and their acknowledgement of diagnostic uncertainty when safety‐netting. Implicit expressions of uncertainty were more common than explicit. Participants expressed both different communication goals (including reducing patient anxiety, building trust, empowering patients and protecting against diagnostic errors) and different perspectives on how to achieve these goals. Training in diagnostic uncertainty communication is rare, but many felt it would be useful.ConclusionsSignificant variation in diagnostic uncertainty communication exists, even in a controlled setting. Differing communication goals—often grounded in conflicting ethical principles, for example, respect for autonomy versus nonmaleficence—and differing ideas on how to prioritise and achieve them may underlie this. The variation in communication behaviours observed has important implications for patient safety and health inequalities. Patient‐focused research is required to guide practice.Patient or Public ContributionIn the design stage of the study, two patient and public involvement groups (consisting of members of the public of a range of ages and backgrounds) were consulted to gain an understanding of patient perspectives on the concept of communicating diagnostic uncertainty. Their feedback informed the formulations of the research questions and the choice of vignettes used.