bluuebunny/crossref_metadata_2025_split huggingface dataset:
Heart Shaped Anterior Neck Lipoma Mimicking Thyroid Mass: A Case Report
Authors: Ansari Abdus Samad , Chaurasia Dhiraj , Yadav Bikash , Shrestha Season , Basnet Inku Shrestha 
Published: January 2025

ABSTRACTLipomas, one of the most common benign tumors, rarely occur in the anterior neck, often misdiagnosed as thyroid masses. This case highlights the diagnostic challenge posed by such lesions. A 58‐year‐old male presented with a painless slowly progressive anterior neck swelling initially mistaken for a thyroid mass. Though clinical examination findings suggested lipoma, the location of swelling influenced the decision toward thyroid mass. The elevated thyroid stimulating hormone (TSH) level further inclined the diagnosis toward thyroid mass. But imaging and fine needle aspiration cytology shifted the diagnosis toward a lipoma. Surgical excision was performed successfully. The gross and histopathological examination confirmed the diagnosis of lipoma. Anterior neck lipomas pose diagnostic challenges due to their uncommon location. Thorough clinical examination and evaluation is crucial to differentiate them from other neck pathologies, primarily thyroid mass. Surgical excision remains the preferred treatment. Postoperative follow‐up is important to monitor for recurrence and complications. Awareness of anterior neck lipoma is vital among clinicians for early diagnosis and optimal management. Early suspicion of this prevalent condition in the given unusual location can guide them towards appropriate diagnostic approach and treatment decisions, ultimately improving patient outcomes and reducing diagnostic complexity for healthcare professionals.
Robust Multivariate Dispersion Charts for Quality Control: Application to Sulfur Dioxide Monitoring
Authors: Ajadi Jimoh Olawale , Abbas Nasir , Riaz Muhammad , Ajadi Nurudeen Ayobami , Salami Taofeek Adeola , Adegoke Nurudeen A. 
Published: January 2025

ABSTRACTThis study introduces two robust multivariate Shewhart‐type control charts based on grouped observations to detect changes in the covariance matrix, with a focus on monitoring sulfur dioxide levels during quality control processes. We compute the covariance matrix of observations, and apply the least absolute shrinkage and selection operator to penalize it in the in‐control process. Logarithms are then applied to eigenvalues derived through singular value decomposition (SVD) of the shrunken covariance matrix, ensuring robustness to non‐normality in the multivariate data. The proposed methods offer significant advantages, particularly in their ability to maintain robustness to non‐normality without relying on strict distributional assumptions. Performance comparisons using the average run length demonstrate that the proposed charts exhibit superior robustness to normality assumptions compared with existing methods. However, potential limitations include the computational complexity of the shrinkage and SVD processes, which may affect the scalability of large datasets. An application to the white wine production process illustrates the effectiveness of the proposed methods for analyzing complex multivariate chemical data. These findings indicate that the introduced charts enhance the detection of shifts in the covariance matrix of physicochemical properties, thereby improving the reliability of quality control processes in non‐normal environments. This study provides valuable tools for quality engineers and practitioners in industries dealing with multivariate analytical data, contributing to improved process monitoring and control, ensuring higher quality standards, and ensuring consistent product outcomes in fields such as food science and industrial chemistry.
Aqueous Binder with Self‐Emulsifying Characteristics for Practical Si/C Anode in Lithium‐Ion Batteries
Authors: Wang Wenqiang , Li Xvfeng , Chen Xiaofeng , Sun Minqiang , Wang Gengchao 
Published: January 2025

AbstractSilicon/carbon (Si/C) materials have achieved commercial applications as a solution to the problems of large volume expansion and short lifespan of silicon‐based anodes in lithium‐ion batteries. However, the potential risk of structural fracture and localized differences in surface adsorption properties lead to difficulties in maintaining the structural integrity of Si/C anodes using conventional binders during repeated lithiation/delithiation. Herein, an aqueous binder (PVA‐g‐M) based on polyvinyl alcohol (PVA) grafted methacrylic acid (MAA) obtained by self‐emulsifying emulsion polymerization is reported. The introduction of carboxyl groups of MAA enables PVA‐g‐M to form more hydrogen bonds, thereby enhancing both the cohesion of the binder film and its adhesion to silicon‐based surface. Simultaneously, the methyl‐containing segments of MAA can wet the carbon‐based surface, thereby enhancing the adhesion of PVA‐g‐M to carbonaceous materials. In addition, the hydroxyl groups on both the PVA segments and the silicon surface can be esterified with the carboxyl groups during the heat treatment, thus further improving the bonding strength. As‐prepared Si/C anodes with PVA‐g‐M binder can significantly inhibit the electrode volume expansion and maintain high structural integrity during cycling as well as form SEIs with high lithium fluoride content, showing excellent cycling stability (81.1 % capacity retention after 300 cycles).
Prednisolone versus antihistamine for allergic rhinitis: No significant difference found in randomized trial
Authors: Skröder Carl , Hellkvist Laila , Westin Ulla , Sahlstrand‐Johnsson Pernilla , Hansson Kerstin , Karlsson Agneta , Dahl Åslög , Bjermer Leif , Cardell Lars Olaf 
Published: January 2025

AbstractBackgroundSeasonal allergic rhinitis (AR) impacts public health by affecting work productivity and quality of life. The Swedish tree pollen season starts in February with alder and hazel pollination, followed by birch and ends with oak in May. Systemic corticosteroids are often prescribed when topical treatments fail, despite limited evidence supporting their efficacy.ObjectiveTo compare the effectiveness of prednisolone tablets versus antihistamine tablets in reducing symptoms and medication usage in patients with moderate to severe tree pollen‐induced AR.MethodsThis interventional single‐center, double‐blinded randomized trial included 34 patients. Treatment was initiated, and symptoms were registered during the tree pollen season. The two groups received either prednisolone tablets (20 mg) or ebastine tablets (20 mg) for 7 days. Treatment effects were evaluated by comparing daily symptom scores, use of topical medication, and a combined symptom‐medical score between the groups. Quality of life was recorded at the start and after 3 weeks.ResultsBoth interventions demonstrated efficacy in enhancing quality of life metrics. The area under the curve (AUC) for the combined symptom severity and medication usage score averaged 34.0 (SD = 19.1, 95% CI = 24.5–43.4) in the group treated with prednisolone. This was marginally lower than the control group, with an AUC of 32.6 (SD = 13.2, 95% CI = 25.6–39.7). The difference was not statistically significant (p = 0.80). Both groups exhibited only mild adverse events, which were statistically comparable in frequency and severity.ConclusionsPrednisolone tablets did not show superior efficacy over antihistamine tablets in reducing symptoms or medication usage in tree pollen‐induced AR. These results suggest that systemic corticosteroids may not provide additional benefits over antihistamines, and clinicians should prioritize individualized treatment based on patient preferences and tolerability.
Examining the Relation Between Prenatal Emotion Dysregulation and Toddler Vocabulary Development: A Biobehavioral Approach
Authors: Wright Kira R. , Bruce Madeleine , Zhou Anna M. , Maylott Sarah E. , Raby K. Lee , Conradt Elisabeth , Crowell Sheila E. 
Published: January 2025

ABSTRACTEarly language is shaped by parent–child interactions and has been examined in relation to maternal psychopathology and parenting stress. Minimal work has examined the relation between maternal emotion dysregulation and toddler vocabulary development. This longitudinal study examined associations between maternal emotion dysregulation prenatally, maternal everyday stress at 7 months postpartum, and toddler vocabulary at 18 months. Data were collected from 289 typically developing, monolingual children (54% female) and their mothers (63% White and non‐Hispanic; 56% held a college degree). During pregnancy, maternal emotion dysregulation was measured via self‐report and resting respiratory sinus arrhythmia (RSA). Mothers completed questionnaires about their perceived everyday stress and their child's vocabulary at 7 and 18 months postpartum, respectively. Path analysis revealed that expectant mothers’ self‐reported emotion dysregulation was indirectly associated with toddlers’ expressive vocabulary via their level of postpartum perceived everyday stress. In addition, prenatal maternal resting RSA directly predicted toddlers’ expressive vocabulary size. These findings yield insights into the mechanisms by which perinatal mental health may shape early language development and highlight the potential utility of interventions targeting emotion dysregulation during pregnancy.
Dietary Shifts Among the Developmental Stages of the Ectoparasite, Argulus japonicus (Crustacea; Branchiura), Mirror Ontogeny as Shown Through Differences in Stable Isotope Ratios of Carbon (δ13C) and Nitrogen (δ15N)
Authors: Gilbert Beric M. , Nachev Milen , Sures Bernd , Avenant‐Oldewage Annemariè 
Published: January 2025

ABSTRACTFood web architecture and trophic interactions between organisms can be studied using ratios of naturally occurring stable isotopes of carbon (13C/12C) and nitrogen (15N/14N). Most studies, however, focused on free‐living organisms, but recently, there has been growing interest in understanding trophic interactions of parasites. The crustacean ectoparasite Argulus japonicus is a well‐studied parasite of freshwater teleost fish, which has low host specificity and a cosmopolitan distribution. Little is known about the trophic interactions between various developmental stages of this parasite and its host. This study compares stable isotope ratios of carbon (δ13C) and nitrogen (δ15N) among developmental stages of A. japonicus. It was hypothesised firstly that stable isotopes would vary among the developmental stages of the parasite with differences matching ontogenetic development of the parasite. Secondly, fractionation patterns among developmental stages would relate to different fish tissues and particles, such as algae, ingested by the parasite. Goldfish, Carassius auratus, were infected with A. japonicus, and different developmental stages of the parasite were isolated and prepared for stable isotope analysis. Differences in stable isotope enrichment correlated with the ontogenetic development of the parasite. In adult parasites, δ15N was higher than in the host's tissues, whereas stage two larvae showed the lowest δ15N values. Infection by A. japonicus alters δ13C ratios between infected and uninfected hosts, where the latter group showed lower δ13C compared to uninfected hosts. Source contribution comparison showed that algae was not incorporated into the diet of A. japonicus and tissues of the host served as the only dietary source of nourishment. These results further suggest that the diet of the parasite is mixed and correlates to the ontogenetic development of A. japonicus.
Extensive Admixture Among Karst‐Obligate Salamanders Reveals Evidence of Recent Divergence and Gene Exchange Through Aquifers
Authors: Nice Chris C. , Bell Katherine L. , Gompert Zachariah , Lucas Lauren K. , Ott James R. , Tovar Ruben U. , Crump Paul , Diaz Peter H. 
Published: January 2025

ABSTRACTKarst ecosystems often contain extraordinary biodiversity, but the complex underground aquifers of karst regions present challenges for assessing and conserving stygobiont diversity and investigating their evolutionary history. We examined the karst‐obligate salamanders of the Eurycea neotenes species complex in the Edwards Plateau region of central Texas using population genomics data to address questions about population connectivity and the potential for gene exchange within the underlying aquifer system. The E. neotenes species complex has historically been divided into three nominal species, but their status, and spatial extent of species ranges, have remained uncertain. We discovered evidence of extensive admixture among species within the complex and with adjacent lineages. We observed relatively low levels of differentiation among all sampling localities which supports the hypothesis of recent divergence. Nominal taxonomy, aquifer region and geography each accounted for a modest amount of the overall population genomic variation; however, these predictors were largely confounded and difficult to disentangle. Importantly, current taxonomy of the three nominal species does not reflect the admixture apparent in clustering analyses. Inference of migration events revealed a complex pattern of gene exchange, suggesting that Eurycea salamanders have a dynamic history of dispersal through the aquifer system. These results highlight the need for greater understanding of how stygobiont populations are connected via dispersal and gene exchange through karst aquifers. These results also highlight the applicability of population genomics data as a powerful lever for investigating connectivity among populations in systems where direct detection of dispersal paths is difficult, as in underground, aquatic systems.
Combining Individual‐Based Radio‐Tracking With Whole‐Genome Sequencing Data Reveals Candidate for Genetic Basis of Partial Migration in a Songbird
Authors: Weissensteiner Matthias H. , Delmore Kira , Peona Valentina , Lugo Ramos Juan Sebastian , Arnaud Gregoire , Blas Julio , Faivre Bruno , Pokrovsky Ivan , Wikelski Martin , Partecke Jesko , Liedvogel Miriam 
Published: January 2025

ABSTRACTPartial migration is a phenomenon where migratory and resident individuals of the same species co‐exist within a population, and has been linked to both intrinsic (e.g., genetic) as well as environmental factors. Here we investigated the genomic architecture of partial migration in the common blackbird, a songbird that comprises resident populations in the southern distribution range, partial migratory populations in central Europe, and exclusively migratory populations in northern and eastern Europe. We generated whole‐genome sequencing data for 60 individuals, each of which was phenotyped for migratory behavior using radio‐telemetry tracking. These individuals were sampled across the species' distribution range, including resident populations (Spain and France), obligate migrants (Russia), and a partial migratory population with equal numbers of migratory and resident individuals in Germany. We estimated genetic differentiation (FST) of single‐nucleotide variants (SNVs) in 2.5 kb windows between all possible population and migratory phenotype combinations, and focused our characterization on birds from the partial migratory population in Germany. Despite overall low differentiation within the partial migratory German population, we identified several outlier regions with elevated differentiation on four distinct chromosomes. The region with the highest relative and absolute differentiation was located on chromosome 9, overlapping PER2, which has previously been shown to be involved in the control of the circadian rhythm across vertebrates. While this region showed high levels of differentiation, no fixed variant could be identified, supporting the notion that a complex phenotype such as migratory behavior is likely controlled by a large number of genetic loci.
O−Doped Carbon Nitride: A Recyclable, Metal‐free Photocatalyst for Oxidative Amidation of Aromatic Aldehydes and Amines under Visible Light Irradiation
Authors: Huang Zezhao , Xu Hang , Zhang Wenjie , Liang Zeyao , Lin Ping , Zhu Li , Yao Xiaoquan 
Published: January 2025

AbstractOxidative amidation of aldehydes with amines is a promising strategy for the synthesis of valuable amides. However, conventional methods often use toxic oxidants and additives, resulting in the generation of chemical waste. In this study, we report the catalytic oxidative amidation of aldehydes with amines using molecular oxygen under additive & metal‐free conditions in visible light, facilitated by an oxygen‐doped carbon nitride (OCN) catalyst. The OCN catalyst shows excellent activity in the production of various amides, demonstrating high functional group tolerance. Furthermore, the OCN catalyst can be reused several times without loss of activity.
Enhancing Agricultural Disease Detection: A Multi‐Model Deep Learning Novel Approach
Authors: Hamid Muhammad Khalid , Shah Said Khalid , Husnain Ghassan , Ghadi Yazeed Yasin , Al Maaytah Shahab Ahmad , Qahmash Ayman 
Published: January 2025

ABSTRACTArtificial intelligence, especially deep learning, has attracted significant interest in bioinformatics, with prominent applications in precision agriculture. A significant threat to the agricultural sector is the rapid propagation of diseases from affected to healthy plants, which, if undetected, may culminate in significant crop losses. This research focusses on employing multi‐model deep‐learning techniques to identify diseases in the leaves of economically significant crops that are potatoes, tomatoes, grapes, apples, and peaches. These crops are widely grown and crucial for food security, with disease outbreaks threatening yield and quality. This study evaluates the performance of deep learning models, including VGG16, MobileNetV2, Xception, and ResNet, using four metrics, that is, Accuracy, Precision, Recall, and F1‐Score. Furthermore, consumer research was undertaken to evaluate user trust in AI‐driven multi‐model systems, collecting feedback from farmers to inform future research directions. The results demonstrate that the VGG16 model outperformed all others in every evaluation criterion. Experimental simulations were performed in Jupyter Notebook utilizing Anaconda and Python. The findings indicate that the proposed multi‐model approach allows a scalable, non‐invasive, and contactless machine vision solution for the early detection of diseases in plant leaves, achieving an efficiency of 99% via multimodal classification techniques that incorporate statistical variables including mean, median, mode, skewness, and kurtosis.
Autonomous Power Sources for Electric Vehicles and Their Charging Infrastructure
Authors: Arhun Shchasiana , Hnatov Andrii , Sokhin Pavlo , Kunicina Nadezda 
Published: January 2025

ABSTRACTThe development and integration of autonomous power sources (APSs) for electric vehicle (EV) charging infrastructure are essential for reducing dependency on centralized power grids and advancing sustainable transportation. This study presents a novel APS model that integrates hybrid inverters, photovoltaic (PV) panels, and battery storage to create a reliable, cost‐effective, and environmentally friendly EV charging solution. The proposed system achieves a 30% increase in charging efficiency compared to traditional grid‐dependent models. Furthermore, the APS model reduces operational costs by 40%–60% for EV fleet operators and demonstrates a potential CO₂ emissions reduction of 70%–90% by relying on renewable solar energy. The results highlight the APS's adaptability across various environmental conditions, making it suitable for deployment in both urban and remote areas. This work contributes to the field by providing a scalable and sustainable approach to EV charging that supports green urban infrastructure and promotes resilience in energy supply.
Laboratory‐Scale Assessment of Carbon‐Epoxy Structural U‐Channels Exposed to Flange Heating
Authors: Aspinall Tim J. , Erskine Emmajane L. , Denham Kevin A. , Taylor Derek C. , Hadden Rory M. 
Published: January 2025

ABSTRACTThis study investigates the combined thermal and mechanical response of pre‐loaded woven carbon‐epoxy U‐channels subjected to radiant heating conditions similar to those experienced by aircraft structures in the event of a fire. A custom‐built laboratory scale test rig was used to combine the mechanical loads and thermal boundary conditions. The main experimental aim was to measure failure times, failure modes, displacement and temperature distribution of the U‐channels. The results show that the U‐channels undergo multiple phases of decomposition when exposed to heat. These phases include physico‐chemical changes such as bubble formation, visible charring, and epoxy resin pyrolysis. Additionally, the U‐channels experience mechanical degradation through thermal‐induced delamination and torsional deformation, causing the flange furthest from the heat source to buckle. The rate of decomposition and loss of load‐bearing capacity are directly proportional to heat flux, with higher heat fluxes accelerating these processes. Analysis of displacement data reveals that higher heat fluxes correlate with lower displacement variability over time for U‐channels under identical thermal conditions. Temperature measurements indicate that higher heat fluxes result in higher temperatures but lower temperature gradients, directly influencing failure times and modes. Consequently, higher temperatures lead to shorter failure times, while lower temperatures extend failure times. The findings from this study will provide valuable knowledge to inform optimised approaches, especially in the domain of aircraft structural fire safety.
MasqueradeGAN‐GP: A Generative Adversarial Network Framework for Evading Black‐Box Intrusion Detection Systems
Authors: Dong Baishun , Wang Hongsen , Luo Rubin 
Published: January 2025

ABSTRACTThe proliferation of sophisticated malware poses an escalating threat to economic and national security, demanding a reevaluation of cybersecurity in next‐generation wireless networks like 6G. Integrating artificial intelligence (AI) offers a crucial opportunity to enhance network defenses against increasingly complex cyber threats. However, the growing complexity of 6G technologies exposes current Intrusion Detection Systems (IDS) to covert malware exploitation, underscoring the need for more adaptive and resilient detection mechanisms. In response to these challenges, this study presents MasqueradeGAN‐GP, an innovative framework based on Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN‐GP). The MasqueradeGAN‐GP framework consists of a generator, responsible for transforming raw malicious traffic into a semblance of benign activity, and a discriminator, which dynamically assimilates the feature set of the IDS to discern between genuine and adversarial traffic. Additionally, it includes a restrictive modification mechanism to ensure the fidelity of attack vectors. Experiments conducted on the CICIDS 2017 and NSL‐KDD datasets indicate that MasqueradeGAN‐GP effectively evades detection, suggesting its potential for advancing IDS capabilities and reinforcing AI‐driven security solutions within the 6G landscape. This contributes to building a more robust detection system capable of facing adversarial malware attacks in future wireless communications.