bluuebunny/crossref_metadata_2025_split huggingface dataset:
A physics-aware neural network for effective refractive index prediction of photonic waveguides
Authors: Ünal Hasan Said , Durgun Ahmet Cemal 
Published: January 2025

Abstract
Neural network (NN)—based surrogates have been effectively used for modeling dynamic systems, including photonic devices. However, black-box data-driven modeling approaches significantly suffer from performance reduction in high-dimensional spaces.As a remedy, we propose a novel physics-aware NN architecture for the effective index prediction of photonic strip waveguides. The model learns a translation between the strip waveguide and an equivalent infinite slab waveguide by employing physical loss terms in the loss function. The proposed method exhibits significantly lower error, with more than

$$50\%$$

50
%

reduction, compared to a black-box NN and a variational method. Because of its physical basis, the proposed NN can predict field distributions in rectangular waveguides and the effective indices of higher-order modes.
Free Algebras in Finitely Generated Varieties of Commutative BCK-algebras
Authors: Cenker Václav 
Published: January 2025

AbstractThe article aims at describing finitely generated free algebras in certain finitely generated varieties of commutative BCK-algebras. To achieve this, we first investigate homomorphisms from free commutative BCK-algebras to free ŁBCK-algebras that extend the insertion of generators. The approach allows us to utilize existing results on free ŁBCK-algebras. The second step involves valuations and their equivalence. An essential part is to count the number of non-equivalent valuations with specific properties. With the number in hand, we can provide a comprehensive description of the free algebras.
Disentangling patent quality: using a large language model for a systematic literature review
Authors: Schmitt Valentin J. 
Published: January 2025

Abstract
Assessing patent quality has long been the subject of research interest due to interchangeable terminology, overlapping indicators, and diverse perspectives. To address these challenges, this study presents a comprehensive framework for assessing patent quality, that draws on stakeholder theory and adopts a multidimensional perspective encompassing economic, legal, and technological dimensions, each of which is clearly defined within the study. Using the capabilities of the large language model GPT-4, a systematic literature review was conducted, analyzing an initial sample of 5141 scientific articles and selecting 762 as relevant. From these selected articles, 985 distinct indicators for assessing patent quality were identified and classifed in accordance with the dimensions of patent quality. The findings reveal that forward citations, family size, and the number of claims are among the most frequently used indicators, highlighting a predominant focus on technological quality in nearly two-thirds of the literature. In addition, the study highlights several challenges in patent quality assessment, such as poor research reproducibility due to inconsistent definitions and applications of indicators such as family size. In response, eight research propositions are proposed, emphasizing the critical evaluation of indicators, the application of sophisticated methods, and the quantification of complex metrics. As a contribution to management and scholarship, this research underscores the complexity of patent quality assessment and provides a structured framework for future studies, emphasizing the importance of a multidimensional perspective. It also illustrates the transformative potential of large language models in enhancing systematic literature reviews, setting a new standard for future research.
Biodegradation of Benzophenone-3 in Non-Sterile Culture Process Using Klebsiella huaxiensis W2
Authors: Omeroglu Mehmet Akif , Bakan Buket , Baltaci Mustafa Ozkan , Arslan Nazli Pinar , Ucar Sefa , Elmas Seydanur , Adiguzel Ahmet , Taskin Mesut 
Published: January 2025

Abstract
Benzophenone-3 (BP3) is an organic pollutant widely detected in soil and aquatic environments. The aims of this study were to isolate a bacterium which is capable of degrading BP3 and converting it into non-toxic products, and to design a non-sterile culture process which may be applied to the real biological treatment systems for the bioremediation of BP3. Klebsiella huaxiensis W2 (GenBank accession number: PQ143284) isolated from a wastewater treatment system was found to have high potency to degrade BP3. This bacterium degraded BP3 into two byproducts: phenol, 2,4-bis-(1,1-dimethylethyl) and benzyl benzoate. Oxygenases (P450 monooxygenases, dioxygenases etc.) were predicted to be effective in BP3 degradation. BP3-degradation products did not cause a toxicity on fibroblast cell line. Optimizing inoculum size, that is, inoculating the high size (1–2%) of the bacterial preculture into the wastewater-based medium, make the bacterium more dominant in this medium, thus enabling the bacterial cells to degrade BP3 under non-sterile culture conditions. In this process, biodegradation efficiency was not affected notably from temperature variations, and the bacterium was able to hydrolyze about 99.33% of 1 g/L BP3 within 120 h. Overall, K. huaxiensis W2 was deduced to possess the potency for being used as a bioremediation agent in non-sterile biological treatment systems, in which sterilization process, temperature control, and nutrient supplementation were not needed. The designed process may find applications in the bioremediation of wastewater and sewage effluents. This is the first study using K. huaxiensis in a non-sterile environment for BP3 degradation.
Automatic 4D mitral valve segmentation from transesophageal echocardiography: a semi-supervised learning approach
Authors: Munafò Riccardo , Saitta Simone , Tondi Davide , Ingallina Giacomo , Denti Paolo , Maisano Francesco , Agricola Eustachio , Votta Emiliano 
Published: January 2025

Abstract
Performing automatic and standardized 4D TEE segmentation and mitral valve analysis is challenging due to the limitations of echocardiography and the scarcity of manually annotated 4D images. This work proposes a semi-supervised training strategy using pseudo labelling for MV segmentation in 4D TEE; it employs a Teacher-Student framework to ensure reliable pseudo-label generation. 120 4D TEE recordings from 60 candidates for MV repair are used. The Teacher model, an ensemble of three convolutional neural networks, is trained on end-systole and end-diastole frames and is used to generate MV pseudo-segmentations on intermediate frames of the cardiac cycle. The pseudo-annotated frames augment the Student model’s training set, improving segmentation accuracy and temporal consistency. The Student outperforms individual Teachers, achieving a Dice score of 0.82, an average surface distance of 0.37 mm, and a 95% Hausdorff distance of 1.72 mm for MV leaflets. The Student model demonstrates reliable frame-by-frame MV segmentation, accurately capturing leaflet morphology and dynamics throughout the cardiac cycle, with a significant reduction in inference time compared to the ensemble. This approach greatly reduces manual annotation workload and ensures reliable, repeatable, and time-efficient MV analysis. Our method holds strong potential to enhance the precision and efficiency of MV diagnostics and treatment planning in clinical settings.

Graphical abstract
Post-mortem diagnosis of septic arthritis by Pasteurella multocida: a case report and literature review of fatal septic arthritis
Authors: Giorgetti Arianna , Santelli Simone , Filipuzzi Ilenia , Bonasoni Maria Paola , Basile Giuseppe , Pirani Filippo , Pelotti Susi 
Published: January 2025

Abstract The diagnosis of septic arthritis remains challenging in the clinical setting, often leading to a suspicion for medical liability. Our purpose is to describe an unusual case of a post-mortem diagnosis of P. multocida fatal septic arthritis, in a healthy 67-year-old woman presenting with pain in the right shoulder. Moreover, a literature review of cases of fatal septic arthritis is provided. The multidisciplinary approach consisted of a forensic autopsy and additional post-mortem analyses (microbiology, biochemical analyses, histopathology, and revision of radiological images) carried out during the prosecutor’s investigation for medical liability. A systematic review of the literature was performed to collect cases of fatal septic arthritis and to understand its frequency and characteristics. No clear cause of death was determined after the autopsy, that only highlighted swelling and purulent exudation in the right glenohumeral joint. The microbiological swab performed on the shoulder tested positive for P. multocida, while histopathological and biochemical data were consistent with a sepsis. These results guided the interview with the woman’s relatives, until a history of a previous contact with a stray cat emerged. The cause of death was deemed as fatal septic arthritis caused by P. multocida, occurred after cat scratches and bites and only diagnosed post-mortem. The review of the literature provided 15 articles about fatal septic arthritis, only 1 caused by P. multocida, and all with ante-mortem diagnosis. Given the nonspecific symptoms, usually including a localized pain, and the absence of a clear history, e.g. of animal contact, septic arthritis might represent an under-reported clinical and pathological diagnosis, leading to a judicial autopsy for the suspicion for medical liability. The post-mortem examination, following a multidisciplinary approach including integration of the clinical history, microbiological and histopathological analysis, could represent the only opportunity for the diagnosis of the cause of death.
Digital Transformation of Corporate Technical Education and Training – A Case Study on Instructional Designers´ Perceptions
Authors: Wintersberg Lisa , Pittich Daniel 
Published: January 2025

AbstractThis article explores the perspective of instructional designers on the digital transformation of corporate technical education and training. It draws on “episodic narrative interviews” conducted with the learning and development department of a for-profit company in the manufacturing sector to investigate their perceptions of digital transformation. We examine the working structures of the studied company, elaborate on their perceived challenges and needs, and highlight our position on future implications for corporate technical education and training. The case study improves the quality of practice within professional education by pointing out necessary considerations about communication, the instructional design process, job descriptions, digital learning products, and the target group’s attitude towards digital teaching and learning. Our results support companies, learning and development departments, and everyone related to corporate technical education and training in developing concepts for professional education programs or contributing with further best practices.
The intermediate jacobian fibration of a cubic fourfold containing a plane and fibrations in Prym varieties
Authors: Mattei Dominique 
Published: January 2025

AbstractWe give a description of the intermediate Jacobian fibration attached to a general complex cubic fourfold X containing a plane as a Lagrangian subfibration of a moduli space of torsion sheaves on the K3 surface associated to X up to a cover. To do so, we propose a general construction of Lagrangian fibrations in Prym varieties as subfibrations of Beauville–Mukai systems over some loci of nodal curves in linear systems on K3 surfaces.
Initial Stage Oxidation of 304HCu Stainless Steel in Oxygen Environment
Authors: Archana M. , Rao Ch. Jagadeeswara , Ningshen S. 
Published: January 2025

Abstract
The early stages of oxidation and the development of transient initial oxides on 304HCu stainless steel (SS) were investigated by isothermal oxidation at 650 and 750 °C in a pure oxygen environment using thermogravimetry. At 750 °C, the formation of the continuous oxide layer occurs more rapidly, exhibiting protective parabolic kinetics, where the slow diffusion of iron through the oxide layer governs the oxidation rate. The oxide scales primarily consist of binary oxides of iron and chromium, with noticeable segregation of manganese and niobium in the early stages. Distinct morphological differences were observed in the transient initial oxide scales formed at the two temperatures, each providing additional nucleation sites for oxide formation. The GDOES depth profiles indicated the migration of Cu from the oxide/scale interface to the oxide scale. The role of the oxide composition and its morphology on the oxidation behavior of 304HCu SS are discussed in detail.
Effectively eliminating lead and cadmium from industrial wastewater using a biowaste-based sorbent
Authors: Reda Aly , El-Demerdash Abdel-Ghafar , Sadik Wagih , El-Rafey Essam , Shoeib Tamer 
Published: January 2025

Abstract
Toxic heavy metals, such as Pb(II) and Cd(II), pose serious environmental and health risks, stressing the urgent demand for innovative and sustainable techniques to reduce their adverse effects. This study investigates the use of sugar beet biowaste as an eco-friendly biosorbent for the removal of Pb(II) and Cd(II) from aqueous solutions, in both laboratory and industrial effluents. Characterization through scanning electron microscopy, X-ray diffraction, thermogravimetric analysis, Fourier-transform infrared spectroscopy, and energy-dispersive X-ray spectroscopy revealed the formation of stable hydrocerussite and otavite, confirming chemisorption. Approximately 95% of the employed biowaste is composed of calcium (Ca), carbon (C), and oxygen (O). The zeta potential was measured at − 17.5 mV with a point of zero charge at pH 8.0, and the total surface area of the biosorbent was approximately 7.72 m2 g−1, with a Langmuir surface area of 11.563 m2 g−1 and a pore volume of 0.028 cm3 g−1. Various parameters, such as the metal concentration, biosorbent dosage, pH, temperature, and contact time, were optimized, achieving maximum removal of Pb(II) and Cd(II) within 60 min at pH 12 and 328 K. Sorption followed a pseudo-second-order kinetic model (R2 = 0.99) and the Freundlich isotherm (R2 = 0.98), with high sorption capacities of 466.5 mg g−1 for Pb(II) and 505.6 mg g−1 for Cd(II). Thermodynamic analysis indicated that the sorption process is spontaneous, thermodynamically favorable, and endothermic. The biowaste effectively removed heavy metals and demonstrated removal efficiencies exceeding 85% for most heavy metals in industrial effluent samples from Alexandria and Ain Sokhna. Sorption capacity ratio values close to 1 indicate effective Pb(II) and Cd(II) uptake with minimal interference, even in the presence of methylene blue dye. Comparative analysis revealed that the untreated biosorbent was more efficient than typical biosorbents, and an economic cost evaluation revealed that processing the biosorbent costs 1.05 USD/kg, highlighting its potential as a sustainable and economically viable option for industrial effluent treatment and supporting broader environmental goals.
Neural Network-Based Finite-Time Control for Stochastic Nonlinear Systems with Input Dead-Zone and Saturation
Authors: Kharrat Mohamed , Krichen Moez , Alhazmi Hadil , Mercorelli Paolo 
Published: January 2025

AbstractThe problem of adaptive control for stochastic systems impacted by saturation and dead zone is discussed in this study. Neural networks are incorporated into the design to effectively control the unknown nonlinear functions present in these systems. The non-smooth input saturation and dead-zone nonlinearities are approximated using the non-affine smooth function. Next, the mean-value theorem is applied to derive the affine form. The study develops an adaptive finite-time controller using the backstepping approach, ensuring semi-globally practical finite-time stability for all closed-loop system signals while driving the tracking error to converge within a finite time to a small region around the origin. To illustrate the efficacy of the suggested control strategy, two simulation examples are given.
Brainsourcing for temporal visual attention estimation
Authors: Moreno-Alcayde Yoelvis , Ruotsalo Tuukka , Leiva Luis A. , Traver V. Javier 
Published: January 2025

Abstract
The concept of temporal visual attention in dynamic contents, such as videos, has been much less studied than its spatial counterpart, i.e., visual salience. Yet, temporal visual attention is useful for many downstream tasks, such as video compression and summarisation, or monitoring users’ engagement with visual information. Previous work has considered quantifying a temporal salience score from spatio-temporal user agreements from gaze data. Instead of gaze-based or content-based approaches, we explore to what extent only brain signals can reveal temporal visual attention. We propose methods for (1) computing a temporal visual salience score from salience maps of video frames; (2) quantifying the temporal brain salience score as a cognitive consistency score from the brain signals from multiple observers; and (3) assessing the correlation between both temporal salience scores, and computing its relevance. Two public EEG datasets (DEAP and MAHNOB) are used for experimental validation. Relevant correlations between temporal visual attention and EEG-based inter-subject consistency were found, as compared with a random baseline. In particular, effect sizes, measured with Cohen’s d, ranged from very small to large in one dataset, and from medium to very large in another dataset. Brain consistency among subjects watching videos unveils temporal visual attention cues. This has relevant practical implications for analysing attention for visual design in human-computer interaction, in the medical domain, and in brain-computer interfaces at large.
Inhibitory effects of the combination of rapamycin with gemcitabine plus paclitaxel on the growth of pancreatic cancer tumors
Authors: Jobu Yuri , Nishigawa Miki , Furihata Kaoru , Furihata Mutsuo , Uchida Kazushige , Taniuchi Keisuke 
Published: January 2025

AbstractWe previously examined the antitumor effects of short interfering RNA nanoparticles targeting mammalian target of rapamycin (mTOR) in an orthotopic pancreatic cancer mouse model. We herein report the inhibitory effects of the mTOR inhibitor rapamycin on tumor growth in a novel established mouse model of pancreatic cancer using human pancreatic cancer cell line-derived organoids. Gemcitabine, 5-fluorouracil, and gemcitabine plus nab-paclitaxel are clinically used to treat advanced pancreatic cancer. In vitro assays showed that rapamycin strongly inhibited cell invasion, while gemcitabine, 5-fluorouracil, and gemcitabine plus paclitaxel primarily inhibited cell proliferation with minimal effects on invasion. In vivo mouse experiments demonstrated that rapamycin exhibited superior antitumor activity to S-1 (a metabolically activated prodrug of 5-fluorouracil) and another mTOR inhibitor, everolimus, while its efficacy was similar to that of gemcitabine plus paclitaxel (which was used instead of nab-paclitaxel due to concerns about allergic reactions in mice to human albumin) in a mouse model of pancreatic cancer using human pancreatic cancer cell line-derived organoids. Furthermore, the combination of rapamycin with gemcitabine plus paclitaxel exerted synergistic inhibitory effects on the growth of pancreatic cancer tumors. Although the inhibition of tumor growth was significantly stronger in everolimus-treated mice than in control mice, there were no additive anti-growth effects when combined with gemcitabine plus paclitaxel. The present results suggest that the combination of rapamycin with gemcitabine plus paclitaxel achieved the greatest reduction in tumor volumes in the mouse xenograft model and, thus, has significant clinical promise.
A review of advanced controller methodologies for robotic manipulators
Authors: Tinoco Vítor , Silva Manuel F. , Santos Filipe N. , Morais Raul , Magalhães Sandro A. , Oliveira Paulo Moura 
Published: January 2025

Abstract
With the global population on the rise and a declining agricultural labor force, the realm of robotics research in agriculture, such as robotic manipulators, has assumed heightened significance. This article undertakes a comprehensive exploration of the latest advancements in controllers tailored for robotic manipulators. The investigation encompasses an examination of six distinct controller paradigms, complemented by the presentation of three exemplars for each category. These paradigms encompass: (i) adaptive control, (ii) sliding mode control, (iii) model predictive control, (iv) robust control, (v) fuzzy logic control and (vi) neural network control. The article further introduces and presents comparative tables for each controller category. These controllers excel in tracking trajectories and efficiently reaching reference points with rapid convergence. The key point of divergence among these controllers resides in their inherent complexity.
Teachers’ Beliefs and Practices About the Potential of ChatGPT in Teaching Mathematics in Secondary Schools
Authors: Busuttil Leonard , Calleja James 
Published: January 2025

AbstractThis study investigates the beliefs and practices of secondary school mathematics teachers in Malta regarding the potential of generative artificial intelligence (GenAI), particularly through tools like ChatGPT, in teaching, using the TPACK framework. Through a case study methodology involving pre- and post-professional development (PD) session surveys and analysis of field notes, the research examines the alignment between teachers’ self-reported beliefs and pedagogical practices and their perceptions of ChatGPT’s utility. Findings show teachers, particularly those with discovery and connectionist educational philosophies, view ChatGPT positively, believing it fosters active learning, encourages exploration, and supports individualised engagement. Despite challenges like interpreting visual mathematical representations and inaccuracies, teachers see ChatGPT as a tool for creating practice problems, assessments, and personalised feedback, aligning with trends in existing literature. The study underscores the necessity of ongoing PD to equip teachers with the skills to integrate ChatGPT effectively into their pedagogy, suggesting a deeper understanding of both the opportunities and challenges presented by GenAI in education. The alignment of teachers’ beliefs and practices with their perceptions of ChatGPT’s potential suggests a readiness among educators to adopt innovative technologies that align with contemporary pedagogical values, enhancing the teaching and learning experience in mathematics. This research contributes to the body of knowledge on GenAI integration in education, highlighting the importance of aligning educational technology with teachers’ pedagogical beliefs and practices to maximise its benefits and recognising the potential of ChatGPT to change mathematics education by facilitating active engagement and personalised learning, while also acknowledging its limitations and ethical implications.
Refined Chabauty–Kim computations for the thrice-punctured line over $$\mathbb {Z}[1/6]$$
Authors: Lüdtke Martin 
Published: January 2025

AbstractThe Chabauty–Kim method and its refined variant by Betts and Dogra aim to cut out the S-integral points $$X(\mathbb {Z}_S)$$

X
(

Z
S

)

on a curve inside the p-adic points $$X(\mathbb {Z}_p)$$

X
(

Z
p

)

by producing enough Coleman functions vanishing on them. We derive new functions in the case of the thrice-punctured line when S contains two primes. We describe an algorithm for computing refined Chabauty–Kim loci and verify Kim’s Conjecture over $$\mathbb {Z}[1/6]$$

Z
[
1
/
6
]

for all choices of auxiliary prime $$p < 10{,}000$$

p
<
10
,
000

.