bluuebunny/crossref_metadata_2025 huggingface dataset:
Mesoporous Silica-Coated Selenium Nanoparticles and Their Effects on Selenium-Enriched Properties of Pleurotus Geesteranus
Authors: Zhan Ze Wei , Peng Hongxia , Hua Ru , Tang Dejian , He Bo , Xia Zengrun , Cui Bin
Published: January 2025

Nano-selenium is ideal for selenium source materials in the fields of selenium-enriched fertilizer. However, existing nano-seleniums often suffer from low chemical stability and dispersity, limiting their widespread use. Here, a novel mesoporous Se NPs@SiO2 nanoparticle with high dispersity is synthesized by the Stober method. The application of Se NPs@mSiO2 nanoparticles for selenium-enriched fertilizer in Pleurotus geesteranus planting is reported. Compared with Na2SeO3 and Se nanoparticles, Se NPs@mSiO2 selenium source material can enhance the stability and dispersity of Se NPs in NPK ternary compound fertilizer. Mesoporous silica-coated selenium nanoparticles also increased the adsorption of Se on plant leaves, and long-term stability for plant selenium supplements. Moreover, these Se NPs@mSiO2 selenium source materials enable promote growth and selenium-enriched performance of P. geesteranus by high bioactivity. Implementation of core–shell structure selenium source material significantly reduces nano-selenium dose and hence cytotoxicity, providing a paradigm for promoting growth and selenium-enriched performance of plants.
Process optimization in friction stir welding of γ-TiAl alloys — A machine learning approach
Authors: Neelam Naga Sruthi , Varma Ankam Ravi , Kumar Challa Kiran , Das Vallepu Prabhu
Published: January 2025

[Formula: see text]-TiAl alloys with high strength-to-weight ratio, and excellent high-temperature properties are used in the low-pressure turbine sections of advanced aero-gas turbine and automotive combustion engines. Their joining processes are highly in demand as it is necessary for wider application of the alloys. Friction stir welding (FSW) has emerged as a promising solid-state welding technique, especially in the context of [Formula: see text]-TiAl alloys, owing to its ability to mitigate thermal distortion and preserve material properties. This research focuses on the process optimization of FSW in joining similar [Formula: see text]-TiAl alloys using artificial intelligence (AI)-based machine learning (ML) algorithms and enhancing the tensile strength of the welded joints. The optimization process involves the identification and refinement of welding parameters such as rotational speed, friction time, and traverse speed. By leveraging ML algorithms, a predictive model is developed to estimate tensile strength based on the selected welding parameters.
Empirical Wavelet Frames
Authors: Gilles Jérôme , Castro Richard
Published: January 2025

Due to their adaptive nature, empirical wavelets (EWs) had several successes in many fields from engineering, science, medical signal/image processing. Recently, a general theoretical framework has been developed in the one-dimensional case, showing the possibility to build EWs from any classic mother wavelets. Given extensive literature both in theory and applications of classic wavelet frames, it is legitimate to ask about the feasibility of building EW frames. We address this question in this paper. We prove several results which provide conditions on the existence of EW frames taking into account the above-mentioned adaptability.
2D Boundary Element Method for Predicting Underwater Electromagnetic Noise of Permanent Magnet Synchronous Motors
Authors: Li Xudong , Lei Guang , Zhao Shihao , Zhang Chi , Chen Leilei
Published: January 2025

This paper presents a robust and efficient boundary element method (BEM) for predicting underwater electromagnetic (EM) noise generated by permanent magnet synchronous motors (PMSMs) in rim-driven thrusters (RDTs). Compared to the Finite Element Method (FEM), the BEM has distinct advantages in handling exterior acoustic problems, such as easier implementation of Sommerfeld radiation condition, reduced mesh requirements, and lower discretization errors. However, when applied to the problem of EM noise in RDTs, the traditional BEM has two main drawbacks. First, the conventional BEM tends to produce fictitious modes at high frequencies. Second, due to the dense and frequency-dependent nature of the BEM matrices, the method suffers from low efficiency in large-scale frequency sweep calculations. To overcome the aforementioned drawbacks, the proposed method incorporates the Burton-Miller formulation to suppress fictitious modes and a Taylor expansion method for efficient frequency sweep calculations. Numerical experiments on a 96-slots, 16-poles PMSM validate the accuracy and efficiency of the proposed method. Additionally, this paper investigates fluid loading effects on the structural vibrations, providing insights for the design of vibration and noise reduction strategies in underwater motors.
Correction of volume for the offset of piston in a calculable pistonphone with small chamber
Authors: Zhong Junjie , He Wen
Published: January 2025

When the high sound pressure at high frequencies is produced in the calculable pistonphone, for instance, in order to generate a sound field with a higher frequency such as not lower than 315 Hz and a sound pressure level reaching 174 dB Ref. 20 [Formula: see text]Pa, the chamber is always designed small enough based on the sound pressure formula of the calculable pistonphone and the output capacity limitation of vibrators. Meanwhile, a balanced hole is always designed in the chamber to balance the inside and outside static pressure, which results in the offset of the piston equilibrium position and the large error of the calculated sound pressure. The mechanism of the piston offset is explained by the theory of fluid motion in circular pipes and thermal expansion. An eddy current sensor is thus introduced to measure the offset of piston of the calculable pistonphone and the primary calibration results were corrected. The experiment verified the phenomenon of the piston offset, and the effect of the correction method is confirmed in the primary calibration.
Top 2 at ALQAC 2024: Large Language Models (LLMs) for Legal Question Answering
Authors: Pham Huy Quang , Nguyen Quan Van , Tran Dan Quang , Nguyen Thang Kien-Bao , Nguyen Kiet Van
Published: January 2025

This paper details the methods proposed by the UIT-DarkCow team during their participation in the 4th Automated Legal Question Answering Competition (ALQAC 2024). Specifically, the team focused on two main tasks: legal document retrieval and legal question answering (LQA). For the legal document retrieval task, the goal was to return articles related to a given question. An article is considered “relevant” if it contains information that helps answer the question. To achieve this, the team applied a Vietnamese sentence parsing method, combined with two prominent retrieval methods: BM25, a traditional and proven method, and sentence transformer, a recently emerged and highly regarded method in natural language processing. This combination significantly improved the accuracy of finding relevant documents for the questions. In the LQA task, we faced three types of questions: true/false questions, multiple-choice questions, and free-text questions. To address these questions, the team used the most advanced technique currently available: prompt engineering with large language models. This technique allows the model to understand and accurately answer legal questions. The results of the ALQAC 2024 competition demonstrated the effectiveness of the methods applied by the team. UIT-DarkCow achieved third in the legal document retrieval task and second in the LQA task.
Geological potential of hydrogen storage in the Pannonian Basin complex
Authors: Gelencsér O. , Cseresznyés D. , Szamosfalvi Á. , Breitner D. , Kővágó Á. , Szabó Cs. , Szabó-Krausz Zs. , Falus Gy.
Published: January 2025

Hydrogen has a growing importance in the global energy market as hydrogen technologies are foreseen as the leaders of the energy transition. Its large-scale storage is the most practical manner to balance the weather dependency of renewable energy production and the daily (seasonal) energy demand. The large-scale storage of gases in geologic formations is currently implemented for natural gas and carbon-dioxide. Due to technological developments, underground hydrogen storage (UHS) has emerged as an option providing seasonal storage capability. Nevertheless, UHS can be challenging from several aspects including environmental and economics. Geochemical and biochemical reactions can occur leading to hydrogen loss in the subsurface space. Hence the geological potential of the UHS sites needs to be estimated. This study focuses on the geological resources of the Carpathian-Pannonian region, where two promising rock types are available including porous sandstones and evaporites. The geological risk of hydrogen loss is discussed, and a site selection method is introduced with respect of the regional geologic storage types.
Addressing Teamwork Delays during Life-Saving Interventions through an Activity Theory-Informed Analysis
Authors: Zellner Katherine , Sarcevic Aleksandra , Barnouw Maja , Krentsa Megan , Sullivan Travis , Kim Mary Suhyun , Burd Randall
Published: January 2025

Hemorrhage, or severe blood loss due to injury, is a leading cause of preventable deaths after injury. This study uses and extends activity theory to understand the dynamics of team-based hemorrhage control during trauma resuscitation and to explore potential computerized mechanisms to support this time- and safety-critical process. We reviewed videos of 25 resuscitation cases and analyzed hemorrhage control activities using nine activity theory prompts, including a new prompt-speech intention-a critical but underexplored dimension of teamwork in prior activity theory analyses. Through this process, we identified the most common delay-causing activities and developed routine and non-routine activity models for each. A comparison of these models showed that variations from the routine models emerged due to changes in the division of labor, instruments, community, and speech intentions. We contribute to research on designing socio-technical systems by (1) identifying needs and opportunities for computerized support that address delays in complex medical teamwork and (2) examining how an intervention changes an activity model. We also show how adding detailed speech data aids in identifying contradictions between elements in an activity model.
Generative AI Empowered Network Digital Twins: Architecture, Technologies, and Applications
Authors: Li Tong , Long Qingyue , Chai Haoye , Zhang Shiyuan , Jiang Fenyu , Liu Haoqiang , Huang Wenzhen , Jin Depeng , Li Yong
Published: January 2025

The rapid advancement of mobile networks highlights the limitations of traditional network planning and optimization methods, particularly in modeling, evaluation, and application. Network Digital Twins, which simulate networks in the digital domain for evaluation, offer a solution to these challenges. This concept is further enhanced by generative AI technology, which promises more efficient and accurate AI-driven data generation for network simulation and optimization. This survey provides insights into generative AI-empowered network digital twins. We begin by outlining the architecture of a network digital twin, which encompasses both digital and physical domains. This architecture involves four key steps: data processing and network monitoring, digital replication and network simulation, designing and training network optimizers, Sim2Real, and network control. Next, we systematically discuss the related studies in each step and make a detailed taxonomy of the problem studied, the methods used, and the key designs leveraged. Each step is examined with a focus on the role of generative AI, from estimating missing data and simulating network behaviors to designing control strategies and bridging the gap between digital and physical domains. Finally, we discuss the open issues and challenges of generative AI-based network digital twins.
Domain Counterfactual Data Augmentation for Explainable Recommendation
Authors: Yu Yi , Sugiyama Kazunari , Jatowt Adam
Published: January 2025

Providing explanations for recommendation decisions is crucial for enhancing user trust and satisfaction in recommender systems. However, existing generative methods often produce generic, repetitive explanation texts that fail to reflect the true reasons behind user interests and item attributes. Thus, it is important to address this
degeneration
issue in recommendation explanations. This work tackles a key problem in explainable recommendation: understanding how
explanation degeneration occurs
and improving explanation quality by mitigating it. We argue that examining the causal mechanism underlying the data generation process is key to addressing this problem. Along this line, we identify a neglected hidden variable, which we refer to as
textual attributes
. Textual attributes encompass various aspects, such as text style, word frequency distributions, and more. Just like user persona and item attributes in traditional recommender systems, textual attributes also shape the nature of explanations. Our analysis of the causal graph reveals the underlying cause of the model’s degeneration. To address this issue, we propose a novel learning method called
Domain for Counterfactual Reasoning
(D4C). By using the auxiliary domain to generate counterfactual data and combining it with factual data, this approach helps the model focus more on the causal contributions of users and items during training. Extensive experiments on five real-world datasets from various platforms demonstrate the effectiveness of our approach.
A Comprehensive Survey of Data-Driven Solutions for LoRaWAN: Challenges and Future Directions
Authors: Maurya Poonam , Hazra Abhishek , Kumari Preti , Sørensen Troels Bundgaard , Das Sajal K.
Published: January 2025

Long-range Wide-area Network (LoRaWAN) is an innovative and prominent communication protocol in the domain of Low-power Wide-area Networks (LPWAN), known for its ability to provide long-range communication with low energy consumption. However, the practical implementation of the LoRaWAN protocol, operating at the Medium Access Control layer and specially built to work upon the LoRa physical layer, presents numerous research challenges, including network congestion, interference, optimal resource allocation, collisions, scalability, and security. To mitigate these challenges effectively, the adoption of cutting-edge data-driven technologies such as Deep Learning (DL) and Machine Learning (ML) emerges as a promising approach. Interestingly, very few existing surveys or tutorials have addressed the importance of ML- or DL-based techniques for LoRaWAN. This article provides a comprehensive survey of current LoRaWAN challenges and recent solutions, particularly using DL and ML algorithms. The primary objective of this survey is to stimulate further research efforts to enhance the performance of LoRa networks and facilitate their practical deployments. We begin by emphasizing the characteristics of LoRaWAN compared to other LPWAN technologies and then examine the technical specifications of LoRaWAN that have been released so far, as well as the current research trends. Furthermore, we discuss an overview of the most utilized DL and ML algorithms for overcoming LoRaWAN challenges. We also present an interoperable reference architecture for LoRaWAN and validate its effectiveness using a wide range of applications. Additionally, we shed light on several evolving challenges of LoRa and LoRaWAN for the future digital network, along with possible solutions. Finally, we conclude our discussion by briefly summarizing our work.
Induction of erythropoietin by dietary medium-chain triacylglycerol in humans
Authors: Kanta Josephine M. , Lundsgaard Annemarie , Schaufuss Amanda , Kleinert Maximilian , Kiens Bente , Fritzen Andreas M.
Published: January 2025

This study is the first to assess the effects of nutritionally induced ketogenesis by acute and subchronic intake of medium-chain fatty acids on plasma erythropoietin concentrations. Medium-chain fatty acid intake increases postprandial ketone body concentrations and within only 8 days of daily intake substantially enhances basal plasma erythropoietin concentrations in young men. We therefore reveal a dietary stimulus of endogenous circulating erythropoietin concentrations in humans, with the potential to counter anemia in cardiovascular diseases.
Anxiety, Depression, and Expanded Disability Status Scale Independently Predict the Perception of Disability in Persons With Multiple Sclerosis: A Cross‐Sectional Study
Authors: Curatoli Chiara , Marcassoli Alessia , Barbadoro Filippo , Fornari Arianna , Leonardi Matilde , Raggi Alberto , Schiavolin Silvia , Terragni Rachele , Antozzi Carlo , Brambilla Laura , Torri Clerici Valentina , Confalonieri Paolo , Mantegazza Renato , Lanza Martina
Published: January 2025

Multiple sclerosis (MS) is the most common cause of disability in young adults due to several motor, sensory, and cognitive symptoms. However, little is still known about the impact of psychological, cognitive, and social‐support variables on subjective disability. This study is aimed at exploring the role of clinical, psychological, cognitive, and social‐support variables in predicting disability levels as perceived by persons with multiple sclerosis (pwMS). The World Health Organization Disability Assessment Schedule (WHODAS 2.0) and the Expanded Disability Status Scale (EDSS) were used as subjective and objective measures of disability, respectively. State‐Trait Anxiety Inventory and Beck Depression Inventory‐II assessed symptoms of anxiety and depression; 19‐item Medical Outcome Study–Social Support Survey assessed social support; and Rao’s Brief Repeatable Battery assessed cognitive functioning. A multivariable regression analysis was applied using the WHODAS 2.0 as an outcome. One hundred and fifty‐one pwMS (93 females, mean age 51.6, standard deviation (SD) 5.8) were enrolled. EDSS (β = 7.190; p < 0.001), state anxiety (β = 0.265; p = 0.009), and symptoms of depression (β = 0.835; p < 0.001) explained a large amount of the variance of subjective disability (Adj.R2 = 0.705; p < 0.001) measured through the WHODAS 2.0. Contrarily, cognitive functioning and perceived social support are not independently associated with the WHODAS 2.0 score. Psychosocial interventions in rehabilitation settings, aimed at reducing the overall perceived disability of pwMS, should be implemented in rehabilitation programs.
Exploring Ambiguity in Social Prescribing: Creating a Typology of Models Based on a Scoping Review of Core Components and Conceptual Elements in Existing Programs
Authors: Bhaskar Le-Tien , Mulvale Gillian , Underdown Vivien , Des Jardins Mike
Published: January 2025

Introduction: Despite a growing social prescribing (SP) movement, the concept itself remains ambiguous, resulting in considerable variation in practice across different contexts. As discussions of SP emerge at the policy level, this ambiguity may influence program and policy spread. This research explores current literature and practices of SP to understand the different conceptual elements (i.e., goals and motivations) and core components (i.e., structures and behaviors) of SP.

Methods: A scoping review of academic literature was conducted. Search terms included “social prescr ∗,” “social medicine,” “link worker,” “social refer ∗,” and “community refer ∗.” From this data, a typology of models based on descriptions of conceptual elements and core components was developed. Following the development of the typology, we applied our findings to existing SP programs, which were found through reference‐checking academic sources and a community consultation conducted by our partner organization.

Results: 29 articles informed the scoping review, and 24 program descriptions were compared to the typology. Four models of SP are proposed. The clinical model follows a biomedical approach where the physician refers patients to SP services primarily geared to lifestyle factors. The holistic model addresses social determinants of health, referring to food security, housing, or income programs. The empowerment model considers well‐being through relationship‐building and a deep understanding of the client context. The healthy community’s model focuses on community development, where community members gain the capacity to better support one another.

Conclusion: The proposed typology will help implementers design programs that best suit their goals and contexts. At the policy level, this research demonstrates how a “bounded ambiguity” approach may allow SP to demonstrate its fullest potential. For researchers, this work provides a foundation for future exploration of how SP is implemented despite its ambiguity.
Examination of the Association Between Bisphenol‐Related Genes and Lung Cancer
Authors: Chen Lin , Zhou Min , Lv Dingliang , Qiu Shuiwei
Published: January 2025

In recent years, the release of substantial amounts of synthetic endocrine‐disrupting chemicals (EDCs) into the environment has posed significant threats to human health. Among these EDCs, bisphenol A (BPA) and its substitutes, such as bisphenol S (BPS), bisphenol F (BPF), and bisphenol AF (BPAF), are widely used and have been implicated in disrupting various biological processes. This research aimed to evaluate the potential link between bisphenol‐related gene expression and lung cancer prognosis. Using the Comparative Toxicogenomics Database (CTD), we identified genes involved in bisphenol metabolism and their significant associations with key oncogenes and hormone‐disrupting pathways, including INS, ESR1, ESR2, AR, MAPK1, MAPK3, PPARG, and CYP19A1. Our Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicate that bisphenol‐related genes may be associated with a variety of cancers, particularly lung cancer. To develop a risk model, we employed Cox regression and LASSO regression analyses, constructing a prognostic prediction model for lung cancer based on bisphenol‐related gene expression (BBPPM). This model demonstrated prognostic significance, with lung cancer patients categorized into high‐risk and low‐risk groups, revealing significant differences in survival rates and highlighting the model’s accuracy in predicting lung cancer outcomes. In addition to bioinformatics analyses, experimental studies were conducted to evaluate the effect of BPA on lung cancer cell behavior. BPA exposure significantly promoted the proliferation of A549 lung cancer cells, as assessed by the CCK‐8 assay, and increased the clonogenic potential of the cells in a colony formation assay.
Determination of Oxidative Stress Indexes of Follow‐Up Formulas (> 12 Months) and Certain Flavored Milks
Authors: Özenir Çiler , Cemali Özge , Ağagündüz Duygu
Published: January 2025

Background: Milk is known to contain some natural antioxidants, but limited literature is available on the antioxidant/oxidant content of flavored milks, which are commonly consumed in children > 12 months of age.

Purpose: This study was performed to investigate the total antioxidant status (TAS) and total oxidant status (TOS) and oxidative stress indices of children’s follow‐up formulas (> 12 months) and flavored milks.

Materials and Methods: Milk samples (plain milk [n = 3], cocoa milk [n = 9], chocolate milk [n = 4], strawberry milk [n = 12], banana milk [n = 13], honey milk [n = 2], and children’s follow‐up formula [> 12 months] [n = 8]) between January and March 2021 were included in the study. TAS and TOS levels were measured using commercially available kits (Relassay, Turkey) and Mindray BS300 Auto Biochemistry AnalyzerTM (China). All analyses were carried out in duplicate. The OSI value (arbitrary unit) was calculated.

Results: In this study, TOS values (μmol/L) of milk samples showed a significant difference between all groups (p < 0.05) and the lowest was in plain milk (14.90 ± 3.66 μmol/L). There was a difference in TOS values between plain milk and cocoa milk (p = 0.007) and between plain milk and chocolate milk (p = 0.035). There was a significant difference in TAS values between the groups (p < 0.001), and the highest TAS values were observed in chocolate milk (2.64 ± 0.02 mmol/L) and cocoa milk (2.35 ± 0.45 mmol/L), respectively. The differences in TAS values were found between banana–cocoa milks (p < 0.001), banana–chocolate milks (p = 0.007), and strawberry–cocoa milks (p = 0.033). There was a difference between the OSI values of the groups (p < 0.001), the lowest values were found in cocoa milk (2.57 ± 0.47) and chocolate milk (2.22 ± 0.46), respectively. The difference in OSI values was found between chocolate–banana milk (p = 0.006) and cocoa–banana milk (p = 0.001). A positive correlation (r = 0.945; p < 0.001) was found between TAS and energy content of follow‐up formulas (> 12 months). Positive correlations were found between TAS and fat content (r = 0.679; p = 0.044) and saturated fat content (r = 0722; 0.028) of cocoa milk. There was no significant correlation between OSI and any macronutrient and energy in milk groups (p > 0.05).

Conclusion: Cocoa and chocolate milks have the highest antioxidant and oxidant capacity and the lowest oxidative stress index. However, plain milk had the lowest oxidant capacity. Furthermore, the linear relationship between the energy content of the follow‐up formula and oxidant capacity indicates the importance of adequate‐balanced and functional consumption of these milks.
Impact of Terahertz Frequency Irradiation on the Physicochemical, Nutritional, Microbial and Sensory Quality of Orange‐Fleshed Sweet Potato–Soy Beverage
Authors: Koranteng Lawrencia Boakyewaa , Agordo Adelaide Dorothy Esenam , Assafuah Dorothy Esi , Akanson Joshua , Abano Ernest Ekow
Published: January 2025

The manuscript explored the effect of terahertz frequency irradiation on the physicochemical, nutritional, microbial load and sensory qualities of OFSP–soy beverages. The orange‐fleshed sweet potato was processed into a beverage, and soy milk was added at varied ratios formulated: OFSP: soy milk: 90:10, 80:20 and 70:30 and pasteurised with electromagnetic irradiation at varied times (5, 10 and 15 min). The pH increase was 6.15, 6.21 and 6.24 at 5‐min irradiation and 6.07, 6.11 and 6.18 at 15‐min irradiation with 10%, 20% and 30% addition of soy milk. The Brix content was 9.30, 10.07, 12.01, 7.43, 8.06 and 9.91 at 5‐ and 15‐min irradiation and 10%, 20% and 30% of soy milk addition. However, the microbial load was not detected when samples were irradiated for 10 and 15 min but was noticed at 5‐min irradiation. Likewise, sensory qualities such as colour, taste, aroma, mouthfeel, aftertaste and overall acceptance of the beverage were improved with an increased range colour (5.90 to 6.98), aroma (6.30 to 6.98), taste (5.38 to 7.28), mouthfeel (5.29 to 7.18), aftertaste (5.26 to 7.30) and overall acceptance (5.78– to 7.54). 10‐min electromagnetic irradiation pasteurisation with 90%:10% OFSP and soymilk had optimum beta‐carotene with zero coliform counts and hence it is recommended. The outcome of this study could help to exploit the benefits of terahertz frequency irradiation machines in reducing microbial growth in the beverage industry.
Negative Binomial Regression Model Estimation Using Stein Approach: Methods, Simulation, and Applications
Authors: Ashraf Bushra , Amin Muhammad , Emam Walid , Tashkandy Yusra , Faisal Muhammad
Published: January 2025

The negative binomial regression model (NBRM) is popular for modeling count data and addressing overdispersion issues. Generally, the maximum likelihood estimator (MLE) is used to estimate the NBRM coefficients. However, when the explanatory variables in the NBRM are correlated, the MLE yields inaccurate estimates. To tackle this challenge, we propose a James–Stein estimator for the NBRM. The matrix mean squared error (MSE) and the scalar MSE properties are derived and compared with other estimators, including the ridge estimator (RE), Liu estimator (LE), and the MLE. We assess the performance of the suggested estimator using two real applications and a simulation study, with MSE serving as the assessment criterion. Results from both simulations and real applications demonstrate the superior performance of the proposed estimator over the RE, LE, and MLE.
Corneal Biomechanical Characteristics and Correlation Analysis in Children With Different Refractive States
Authors: Bai Xiao Jing , Wang Yan Hua , Liang Tian Gang , Zhao Qi , Cui Meng Fan , Cheng Jie , Nie Wei Xiang
Published: January 2025

Purpose: To investigate the correlation between corneal biomechanical characteristics and refractive status in adolescents aged 5–13 years.

Methods: A cross‐sectional study involved 339 children aged 5–13 with a spherical equivalent (SE) range from −6.00 to +2.00 diopters. Axial length (AL) was measured by IOL Master, corneal biomechanical parameters by Corvis ST, and anterior segment parameters by Pentacam. According to SE of right eye, the subjects were divided into moderate myopia, mild myopia, and emmetropia group. The correlation between AL and SE and corneal biomechanical parameters was analyzed. The corneal biomechanical parameters of the three groups were also compared.

Results: The A2V value in the moderate myopia group was significantly lower than that in both the mild group and emmetropia group (p < 0.001). PD in the moderate group was higher than that in the mild group (p < 0.05), while PD in mild myopia was higher than that in emmetropia (p < 0.05). The SSI in the emmetropia group was significantly higher than that in the other two groups (all p < 0.001), and the SSI in the mild group was higher than that in the moderate group (p < 0.01). The A2V value in the 11–13 years old group was lower than that in the 5–7 years old group (p < 0.001) and 8–10 years old group (p < 0.01). PD in the 11–13 years old group was significantly higher than that in the 8–10 years old group (p < 0.001), and PD in the 8–10 years old group was significantly higher than that in the 5–7 years old group (p < 0.01). The SSI in the 5–7 years old group was significantly higher than that in the 8–10 years old group (p < 0.001), and the SSI in the 8–10 years old group was significantly higher than that in the 11–13 years old group (p < 0.05). AL was positively correlated with PD and negatively correlated with SSI and A2V. SE was positively correlated with A2V and SSI and negatively correlated with PD.

Conclusions: Corneal stiffness seems to decrease with the increase of SE. The changes of SSI, PD, and A2V were statistically significant and can be predictors of myopia progression in adolescents aged 5–13 years.
A Fast Electromagnetic Radiation Simulation Tool for Finite Periodic Array Antenna and Universal Array Antenna
Authors: Liu Hangxin , Wang Hao , Xu Li , Liu Bingqi , Liu Junhong , Zhang Xiaobo , Yuan Xuesong , Li Bin
Published: January 2025

The domain decomposition method (DDM) enables efficient simulation of electromagnetic problems in large‐scale array antennas using full‐wave methods on moderate hardware. This paper introduces and compares two nonoverlapping DDMs serving as preconditioners with outstanding simulation efficiency. The first method targets finite periodic array antennas by transforming a single array unit rather than explicitly modeling the entire array, effectively leveraging repetitive structures to significantly reduce memory usage and computation time. The second method applies to universal array antennas with arbitrary geometries, employing both planar and nonplanar mesh‐based domain partitioning at subdomain interfaces for flexible modeling of complex arrays. To further enhance computational performance, we propose a parallel multilevel preconditioner based on the block Jacobi preconditioner, thereby accelerating the solution efficiency of subdomain matrix equations in both methods. Additionally, since the choice of domain partitioning method significantly impacts the computational efficiency of DDMs, we propose three different subdomain partitioning strategies. These strategies enable us to accelerate computations while expanding our capacity to simulate a wider variety of types of cases. We developed a fast electromagnetic radiation simulation tool utilizing these techniques. Simulations of exponentially tapered slot (Vivaldi) antenna arrays and antenna arrays with radomes demonstrate that our tool achieves accuracy comparable to commercial software, and notably, our tool outperforms commercial software in terms of the speed of iterative solutions.
Green Synthesis of Pure and Zirconium‐Doped Cerium Oxide Nanoparticles Using Aqueous Extract of Sanvitalia procumbens, Its Characterization, Antiplatelet and Cytotoxic Activities
Authors: Parveen Tasmeena , Ahmad Ijaz , Aslam Madeeha , Fozia Fozia , Khushal Ahmad , Mohany Mohamed , Al-Rejaie Salim S. , Ziaullah Ziaullah , Milošević Marija
Published: January 2025

The current study was used to achieved the green synthesis of pure with different percentages of zirconium‐doped cerium oxide nanoparticles (Zr‐doped CeO2 NPs) using an aqueous plant extract of Sanvitalia procumbens. The synthesis of pure NPs was achieved by mixing 30 mL of Ce (NO3)3·6H2O into 10 mL of plant extract and then adding ZrO (NO3)2. xH2O into a reaction mixture to synthesize Zr‐doped CeO2 NPs with the variation of x (x = 5%, 10%, and 15%). The phytochemicals present in Sanvitalia procumbens plant extract function as stabilizing and reducing agent which may have ability to synthesize pure and Zr‐doped CeO2 NPs. The synthesized NPs were characterized by different analytical techniques, such as UV‐visible (UV‐Vis), scanning electron microscopy (SEM), energy dispersive X‐ray (EDX), Fourier transform infrared spectroscopy (FT‐IR), and powder X‐ray diffraction (PXRD). The UV‐Vis spectroscopy revealed that zirconium (Zr) was well doped in CeO2 NPs with a band gap energy of 4.07–4.56 eV. The SEM images demonstrate the irregular morphology with an average particle size range of 26.72, 24.37, 21.24, and 19.12 nm for pure, 5%, 10%, and 15% Zr‐doped CeO2 NPs, respectively. The fundamental elemental composition of Zr‐doped CeO2 NPs was ascertained by EDX analysis, whereas the PXRD patterns support the crystalline nature of NPs. Furthermore, the synthesized pure and Zr‐doped CeO2 NPs were used to analyze the antiplatelet activity that showed dose‐dependent antiplatelet potentials. The results revealed that 15% Zr‐doped CeO2 NPs showed maximum antiplatelet activity that was 84.24 s at concentrations of 100 μg/mL. Moreover, the IMR32 cell line was also studied to demonstrate the cytotoxicity of pure and Zr‐doped CeO2 NPs. Accordingly, Zr‐doped CeO2 NPs exhibits higher cytotoxic effects against brain cancer in contrast to undoped CeO2 NPs. Thus, the obtained results suggest the potential use of Zr‐doped CeO2 NPs as an industrial application such as in the development of antiplatelet and cytotoxic activity.
Deciphering Metabolic Responses in Traumatic Brain Injury Patients With Different Severity Using 1H NMR‐Based Serum Metabolomics
Authors: Zhou Huan , Sun Dongdong , Wang Dongmei , Zhu Zirui , Hong Xuelian , Fang Rui , Wang Hua , Li Minghui
Published: January 2025

The analysis of metabolites presents a promising opportunity to gain insight into the neuropathophysiology of individuals affected by traumatic brain injury (TBI). In order to elucidate the underlying pathophysiologic mechanisms and identify serum biomarkers associated with TBI, we conducted a comprehensive investigation utilizing a 1H nuclear magnetic resonance (NMR)–based metabolomics approach and ELISA analysis of serum samples obtained within 24 h postinjury from a cohort of participants with varying degrees of TBI severity. Our findings revealed that the decrease of isoleucine, valine, tryptophan, and histidine, as well as the increase of lactate, were proportional to the severity of TBI. In addition, creatine phosphate showed promise in specifically distinguishing moderate TBI from controls, while glutamine and the lactate‐to‐pyruvate ratio demonstrated excellent performance in diagnosing severe TBI from controls. Pathway analysis revealed disruptions in the ketone body metabolism, carnitine synthesis, butyrate metabolism, and citric acid cycle across mild to severe TBI patients. Moreover, our findings suggest an upregulation of the cytokines IL‐1β, IL‐6, and TNF‐α following TBI, displaying correlations with lactate, 5‐aminopentanoate, glucose, and creatinine metabolites. This study offers a novel concept and theoretical framework by leveraging serum metabolites to enhance the objective, rapid and reliable assessment of TBI severity. The clinical implications of this research are significant, as it facilitates the diagnosis and prognosis of TBI patients across a spectrum of severity levels.
Supplementary Data Figure S4 from Neuroendocrine Differentiation in Prostate Cancer Requires ASCL1
Authors: Rodarte Kathia E. , Nir Heyman Shaked , Guo Lei , Flores Lydia , Savage Trisha K. , Villarreal Juan , Deng Su , Xu Lin , Shah Rajal B. , Oliver Trudy G. , Johnson Jane E.
Published: January 2025

Sorting parameters for TdTom + tumor cells used for seeding secondary allograft tumors.
The Endocrine Chameleon: Expanding the phenotype of Pseudohypoparathyroidism 1A in infancy
Authors: Munteanu Martin , Resch Elisabeth , Bildheim Victor , Hoffjan Sabine , Erdlenbruch Bernhard , Linglart Agnès , Grasemann Corinna
Published: January 2025

Introduction: Pseudohypoparathyroidism 1A (PHP1A) is the best-known representative of inactivating PTH/PTHrP signaling disorders (iPPSD). The associated phenotype develops over time and often includes hormonal resistances, short stature and osteoma cutis. More complex and very early manifestations have also been reported. Neonatal complications may indicate a more severe course of the disease. Here we report 3 patients with heterozygous GNAS-variants and infancy-onset of iPPSD2 / PHP1A.

Case Presentations: Patient 1 is a 15-month-old boy, who presented with severe chronic noninfectious diarrhea and elevated TSH beginning at 1 month of age, leading to life-threatening failure to thrive.
Patient 2 is a 4-year-old boy with a history of bronchopulmonary dysplasia as well as neonatal-onset severe pulmonary complications, including critical pulmonary bleeding and recurring pulmonary infections and TSH elevation.
Patient 3 is a 4-year-old girl, who exhibited signs of PTH resistance and progressive osteoma cutis at the age of 1-2 weeks and obesity at the age of 3 months.

Conclusion: The phenotypic spectrum of iPPSD2/ PHP1A in neonates and infants may include severe gastrointestinal, pulmonary and endocrine manifestations, which may delay diagnosis if not recognized as a spectrum-disorder of Gsα deficiency. The cases support the hypothesis that early-life manifestations may indicate a more complicated course of the disease. Elevated PTH or TSH in infants with unclear symptoms or conditions should prompt evaluation for disorders of the iPPSD spectrum. In the absence of reliable predictors for the individual courses of PHP1A, in depth clinical screening for possible manifestations beyond the classical spectrum is warranted even in infancy.
Risk of Atherosclerotic Cardiovascular Disease After Chronic Obstructive Pulmonary Disease Hospitalization among Primary and Secondary Prevention Older Adults
Authors: Mosher Christopher L. , Osazuwa‐Peters Oyomoare L. , Nanna Michael G. , MacIntyre Neil R. , Que Loretta G. , Palmer Scott M. , Jones W. Schuyler , O'Brien Emily C.
Published: January 2025

Background

Meta‐analyses have suggested that the risk of cardiovascular disease events is significantly higher after a chronic obstructive pulmonary disease (COPD) exacerbation, but the populations at highest risk have not been well characterized to date.

Methods and Results

The authors analyzed the risk of atherosclerotic cardiovascular disease (ASCVD) hospitalizations after COPD hospitalization compared with before COPD hospitalization and patient factors associated with ASCVD hospitalizations after COPD hospitalization among 2 high‐risk patient cohorts. The primary outcome was risk of an ASCVD hospitalization composite outcome (myocardial infarction, coronary artery bypass graft, percutaneous coronary intervention, stroke, transient ischemic accident) after COPD hospitalization relative to before COPD hospitalization. Additional analyses evaluated for risk factors associated with the composite ASCVD hospitalization outcome. In the high‐risk primary prevention cohort, the hazard ratio (HR) estimate following adjustment for the composite ASCVD hospitalization outcome after COPD hospitalization versus before COPD hospitalization for 30 days was 0.74 (95% CI, 0.66–0.82;
P
≤0.0001); for 90 days, 0.69 (95% CI, 0.64–0.75;
P
≤0.0001); and for 1 year, 0.78 (95% CI, 0.73–0.82;
P
≤0.0001). In the secondary prevention cohort, the HR for 30‐day hospitalization was 1.15 (95% CI, 1.05–1.26;
P
=0.0036); 90‐day hospitalization, 1.08 (95% CI, 1.01–1.15;
P
=0.0178); and 1‐year hospitalization, 1.07 (95% CI, 1.02–1.11;
P
=0.0026). Among the 19 characteristics evaluated, hyperlipidemia and history of acute ASCVD event were associated with the highest risk of ASCVD events 1 year after COPD hospitalization in the high‐risk primary and secondary prevention cohorts.

Conclusions

The risk of ASCVD hospitalization was higher in patients with established ASCVD and lower among high‐risk patients without established ASCVD after‐COPD hospitalization relative to before hospitalization. We identified multiple risk factors for ASCVD hospitalization after COPD hospitalization.
Health Care Resource Use and Costs of Rivaroxaban Versus Warfarin Among Nonvalvular Atrial Fibrillation Polypharmacy Patients With Obesity
Authors: Alberts Mark , He Jinghua , Kharat Akshay , Pericone Christopher D. , Ashton Veronica
Published: January 2025

Background

The economic burden of nonvalvular atrial fibrillation (NVAF) is substantial. Many patients with NVAF are obese and manage other health conditions requiring multiple medications. This real‐world study compared health care resource use (HRU) and costs for rivaroxaban and warfarin in patients with NVAF who had polypharmacy and obesity.

Methods and Results

We used health care claims databases (Merative MarketScan commercial and Medicare supplemental claims) to identify patients initiating the direct oral anticoagulant rivaroxaban or warfarin with ≥1 diagnostic claim for atrial fibrillation, presence of polypharmacy (based on 3 categories for the number of concurrent medications: 1–4, 5–9, ≥10), and obesity. Cohorts were balanced for demographic and baseline characteristics using propensity score matching. All‐cause and NVAF‐related HRU rates and costs were compared between treatments using rate ratios and adjusted mean differences per patient per year. Eligible patients totaled 95 875, with 19 990 patients in each treatment cohort following propensity score matching. All‐cause HRU rates were significantly lower with rivaroxaban versus warfarin, and hospital stays were reduced by 3.1 days with rivaroxaban. Mean (95% CI) all‐cause total medical and total health care costs per patient per year were significantly reduced with rivaroxaban versus warfarin (−$4499 [−$5660 to −$3305] and –$1627 [−$2790 to −$438], respectively). NVAF‐related HRU was reduced with rivaroxaban versus warfarin, but total NVAF‐related medical costs were not significantly different between treatment groups ($144 [−$756 to $1079] per patient per year). Subgroup and sensitivity analysis results were generally consistent with the main analysis.

Conclusions

Among patients with NVAF, polypharmacy, and obesity, rivaroxaban was associated with a reduction in HRU and all‐cause costs compared with warfarin.
MUCking In, or Fifty Years in Information Extraction
Authors: Grishman Ralph
Published: January 2025

I want to thank the ACL for this Lifetime Achievement Award. I am deeply honored to be receiving it. I would also like to thank the students, faculty, and researchers who were members of the Proteus Project during most of my professional lifetime. It was an honor to serve that group.
A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions
Authors: Wu Junchao , Yang Shu , Zhan Runzhe , Yuan Yulin , Chao Lidia Sam , Wong Derek Fai
Published: January 2025

The remarkable ability of large language models (LLMs) to comprehend, interpret, and generate complex language has rapidly integrated LLM-generated text into various aspects of daily life, where users increasingly accept it. However, the growing reliance on LLMs underscores the urgent need for effective detection mechanisms to identify LLM-generated text. Such mechanisms are critical to mitigating misuse and safeguarding domains like artistic expression and social networks from potential negative consequences. LLM-generated text detection, conceptualized as a binary classification task, seeks to determine whether an LLM produced a given text. Recent advances in this field stem from innovations in watermarking techniques, statistics-based detectors, and neural-based detectors. Human-assisted methods also play a crucial role. In this survey, we consolidate recent research breakthroughs in this field, emphasizing the urgent need to strengthen detector research. Additionally, we review existing datasets, highlighting their limitations and developmental requirements. Furthermore, we examine various LLM-generated text detection paradigms, shedding light on challenges like out-of-distribution problems, potential attacks, real-world data issues, and ineffective evaluation frameworks. Finally, we outline intriguing directions for future research in LLM-generated text detection to advance responsible artificial intelligence. This survey aims to provide a clear and comprehensive introduction for newcomers while offering seasoned researchers valuable updates in the field.1
Forgetting the Covenant of Her God
Authors: O’Kelly Matthew A.
Published: January 2025

Three main proposals have been put forward for how to understand the covenant of the foreign woman’s God in Prov. 2:17: (1) the marriage covenant; (2) a covenant with her foreign god; or (3) the covenant with Yhwh, usually specified as the Sinai covenant. In this essay it is argued that the Sinai covenant is indeed in view, but that to properly square this with the fact that the woman is in fact depicted as “foreign” requires further explanation. It is argued that, with due attention to the socio-political and religious dynamics of the late Persian period (when Proverbs 1–9 is widely agreed to have been written), along with a robust understanding of the constructed nature of ethnic foreignness, emerging tensions between Judah and Samaria in the late Persian period provide a probable scenario for seeing how this was so.
Track Two Dialogue in Times of War – Unsuitable or Advancing Peace for Ukraine?
Authors: Fink Oliver , Graf Wilfried
Published: January 2025

Massive intergroup violence such as the Russian invasion of Ukraine continues to inflict devastating harm to individuals and societies. Civil societies generally do not need to remain inactive and can support peace processes even in severely escalated, apparently unsolvable intergroup conflicts. However, such engagement is delicate, and the exact conditions that make such commitment possible and effective in ‘classic’ interstate war settings remain unclear. Herbert C. Kelman (1927–2022), a social psychologist at Harvard University, developed seminal approaches of unofficial ‘Track Two’ diplomacy and problem-solving, mainly in the Israeli-Palestinian intergroup conflict. Using metatheory and critical hermeneutics, we suggest its current updated form is the conceptual enhancement from inter-group to complex intra/inter-national settings. Therefore, Track Two approaches can be valuable in the Russia/Ukraine setting. The paper outlines initial efforts of ongoing facilitated dialogue, unilateral on both sides and inter-coordinational between, offering inroads in an interstate context where conflict transformation is desperately needed.