bluuebunny/crossref_metadata_2025_split huggingface dataset:
An object detection algorithm based on deep learning and salient feature fusion for roadside surveillance camera
Authors: He Yang , Jin Lisheng , Wang Huanhuan , Sun Xinyu , Huo Zhen , Wang Guangqi 
Published: January 2025

AbstractIn intelligent transportation systems, object detection for a surveillance video is one of the important functions. The performance of existing surveillance video object detection algorithms is affected by the conflict between the features of the objects, which leads to a decline in precision. Therefore, an object detection algorithm based on deep learning and salient feature fusion is proposed. The proposed method introduces a non‐weight‐sharing network to process the salient features of the image and fuse them with the features extracted from the red blue green branch. Different from the previous solutions, the salient feature extraction branch uses the boundary features and statistical features of the image and fuses the features of the two branches in the efficient layer aggregation networks structure. At the same time, the attention module is used in efficient layer aggregation networks with convolutional block attention module to improve the efficiency of feature utilisation. The training and evaluation are carried out in the constructed surveillance video feature conflict dataset, and eight scenes are constructed in the way of orthogonal experiments. The experimental results show that the performance of object detection can be significantly improved by using the proposed method in the object detection task of the intelligent transportation system surveillance video feature conflict scene.
A bipolar high‐voltage pulse driver for air‐coupled ultrasonic defect detection in soft‐pack lithium battery
Authors: Luo Kan , Zhang Qirong , Chen Yu , Chen Siluo , Huang Jing , Liang Chaobing 
Published: January 2025

AbstractDeveloping a high‐performance transducer driver is essential yet challenging for air‐coupled ultrasound applications. This study introduces a MOSFET‐based bipolar high‐voltage pulse driver designed for defect detection in soft‐pack lithium batteries. High‐voltage DC generation is achieved through a push–pull inverter and full‐wave voltage multiplier circuit, producing a stable DC output. High‐speed MOSFET switching then controls the charging and discharging of a capacitor in an RC network, generating a symmetric bipolar high‐voltage pulse signal with a peak‐to‐peak voltage of 1104 V at 100 kHz. Performance evaluation experiments demonstrated that a 7‐cycle pulse train provides an optimal balance of signal penetration and time resolution, effectively preventing waveform overlap. The system reliably penetrates soft‐pack lithium batteries up to 6 mm thick, and detects internal lithium battery defects, such as 1 mm air bubbles. Overall, this bipolar high‐voltage pulse driver surpasses traditional designs in both time and frequency domains, offering enhanced detection accuracy and practicality for air‐coupled ultrasonic inspection of lithium battery defects.
The optimised model of predicting protein‐metal ion ligand binding residues
Authors: Yang Caiyun , Hu Xiuzhen , Feng Zhenxing , Hao Sixi , Zhang Gaimei , Chen Shaohua , Guo Guodong 
Published: January 2025

AbstractMetal ions are significant ligands that bind to proteins and play crucial roles in cell metabolism, material transport, and signal transduction. Predicting the protein‐metal ion ligand binding residues (PMILBRs) accurately is a challenging task in theoretical calculations. In this study, the authors employed fused amino acids and their derived information as feature parameters to predict PMILBRs using three classical machine learning algorithms, yielding favourable prediction results. Subsequently, deep learning algorithm was incorporated in the prediction, resulting in improved results for the sets of Ca2+ and Mg2+ compared to previous studies. The validation matrix provided the optimal prediction model for each ionic ligand binding residue, exhibiting the capability of effectively predicting the binding sites of metal ion ligands for real protein chains.
Exploring optimizer efficiency for facial expression recognition with convolutional neural networks
Authors: Madni Syed Hamid Hussain , A/L Pathmanatan Lokessh , Faheem Muhammad , Shahzad Hafiz Muhammad Faisal , Shah Sajid 
Published: January 2025

AbstractIt's widely accepted that human expressions, considering for roughly sixty percent of all daily interactions, are among the most authentic forms of communication. Numerous studies are being conducted to explore the importance of facial expressions and the development of machine‐assisted recognition techniques. Significant progress is being made in facial and expression recognition, largely due to the rapid growth of machine learning and computer vision. A variety of algorithmic approaches and methods exist for detecting and recognizing facial expressions and features. This study investigates various optimization algorithms used with convolutional neural networks for facial expression recognition. The primary focus is on Adam, RMSProp, stochastic gradient descent and AdaMax optimizers. A comprehensive comparison is being made, examining the key aspects of each optimizer, including its advantages and disadvantages. Furthermore, the study also incorporates findings from recent studies that used these optimizers in various applications, highlighting their performance in terms of training time and precision. The aim is to illuminate the process of selecting a suitable optimizer for specific applications, analysing the trade‐offs between training speed and higher accuracy levels. Moreover, this study provides a deeper analysis of the role optimizers play in machine learning‐based facial expression recognition models. The discussion of the technical challenges posed by these optimizers and future improvements for achieving much more optimal results concludes the study.
Pulsatile Dexamethasone in Patients with Infantile Spasms: A Retrospective Analysis of a Unique Therapy Regime
Authors: Reimer Dennis , Brandl Ulrich , Vries Heike De 
Published: January 2025

Abstract
Objective Infantile spasms (IS) are an age-specific epilepsy syndrome associated with poor outcomes. Sustained and early spasm control remains the main goal of therapy. We aimed to evaluate a unique pulsatile dexamethasone therapy regime in children with IS.
Methods Children with IS were treated with oral pulsatile-applied dexamethasone in the Children's Hospital Jena between 2002 and 2021, regardless of duration since IS onset or previous therapy (except ACTH). A prolonged initial pulse was given in case of insufficient response (standard: 5–7 days, prolonged: 10–14 days). We analyzed spasm reduction, electroencephalographic response, adverse reactions, neurodevelopmental status, and epileptic disorders at the last follow-up.
Results Included were 26 patients with a median age of 5.5 months (interquartile range 4–8) at IS onset and a mean follow-up of 6.2 years (standard deviation [SD] 3.99). Fifty percent had an unknown etiology. Patients received on average 10.8 pulses (SD 6.0); 69.2% achieved initial seizure freedom, however, 38.9% relapsed. Seventeen patients had an initial prolonged pulse, of those, 14 got initially seizure-free (82.4%). Sixty-four percent of the cases had a sustained spasm cessation after the third pulse. At the last follow-up, half of the patients had no persisting epileptic disorder; 22.2% had a favorable neurocognitive development. Patients with unknown etiology were more likely to achieve seizure freedom during therapy (p = 0.025), had a more favorable neurocognitive outcome (p = 0.049), and were less likely to suffer from epileptic disorders (p = 0.037). No serious adverse effects were observed.
Conclusion Our results show that our treatment is safe and leads to outcomes comparable to usually applied hormonal therapy regimes. Etiology remains the most influential factor.
The Efficacy of Platelet-Rich Plasma in the Repair of Tympanic Membrane Perforation
Authors: Prashanth Kudure Basavaraj , Manjunatha Haraganahalli Anandappa , Nayak Prathvi P. 
Published: January 2025

Abstract
Introduction Platelet-rich plasma (PRP) contains high platelet concentration and growth factors that help in rapid wound healing, hemostasis, and decreased scarring. It has been used in various conditions to aid in healing, but its use in ear, nose, and throat (ENT) is not yet common.
Objective To compare the outcome of using PRP with myringoplasty with that of myringoplasty alone in the repair of tympanic membrane perforations.
Methods Sixty-eight patients in the 16-to-50 years age group with tympanic membrane perforation of 3 months duration, with dry ear for 6 weeks, and mild to-moderate conductive hearing loss were selected and divided by simple randomization into 2 equal groups. A thorough preoperative evaluation was done. In group A, patients underwent myringoplasty, and in group B, patients underwent myringoplasty with PRP. Patients were followed up for 3 months postsurgery.
Results At 6 weeks, 67.6 and 94.1% had graft uptake in groups A and B, respectively (p-value 0.011). At 3 months, 85.3 and 97.1% had graft uptake in groups A and B, respectively (p-value 0.197). The mean pure tone audiometry difference in group A was 8.35 ± 2.05, and 11.00 ± 2.28 in group B (p < 0.001). The mean air-bone gap difference for group A was 8.29 ± 2.14, and 10.76 ± 2.36 for group B (p < 0.001). Graft uptake rate at 6 weeks, pure tone audiometry, and air-bone gap difference were statistically significant.
Conclusion The present study results showed that the use of PRP during myringoplasty aids healing of the tympanic membrane with better hearing improvement in the postoperative period when compared to myringoplasty alone.
The listening renaissance: a theoretical exploration of audio-based digital narratives in literature
Authors: Palanisamy Bhuvaneshwari , V Rajasekaran 
Published: January 2025

Abstract
This paper examines the burgeoning phenomenon of audio-based digital narratives and their transformative impact on literature consumption, focusing on the evolving role of listening in the digital age. As audiobooks, podcasts, and other audio formats gain prominence, they challenge traditional notions of reading and storytelling, reshaping individual’s engagement with literary works. Through a theoretical exploration drawing from cognitive theory, media studies, and literary criticism, this study argues that the rise of audio literature represents not merely a shift in medium, but a fundamental change to process and interact with narrative content. The paper investigates the historical evolution of audio narratives, the cognitive processes involved in auditory literary experiences and the emergence of “literary listening” as a distinct skill. It also considers broader implications, including accessibility issues, the democratization of literature, and potential future directions of storytelling in an increasingly audio-centric digital environment. By synthesizing existing research and theoretical frameworks, this study aims to provide a comprehensive understanding of the listening renaissance in literature. The paper concludes by reflecting on the changing nature of literature consumption and the enduring importance of listening in an individual’s engagement with narrative art, suggesting that audio-based digital narratives represent a significant cultural shift associated with literature, rather than just a technological trend.
The pragmatics of critical thinking
Authors: Bardzokas Valandis , Desilla Louisa 
Published: January 2025

Abstract
The notion of critical thinking (CT) has attracted intensive research interest over the years in a number of
scientific fields, i.e., education, psychology, logic, rhetoric, to mention but a few. However, due to its multidirectional
orientation, it has proven hard to pin down. More recently, it has realistically been viewed as a notion that can be organized
into types or sub-skills, each of which can be duly considered relative to the distinctive details of a specific subject (McPeck 1981). The current work observes the type of CT exercised in playing adventure
games, particularly in solving puzzles. Importantly, the obvious link of CT to inferential reasoning notwithstanding, the prospect
of a pragmatic description of the notion at hand is overlooked in the relevant literature, as is the prospect of a pragmatic
description of videogaming. In order to compensate for this double oversight, the current work draws on the insights of relevance
theory, securing a unifying framework of pragmatic analysis. More specifically, as will be shown, playing an adventure game
engages the player in exercising a type of critical thinking that is oriented towards the task of solving a problem or puzzle. In
this light, a puzzle is composed of a series of mental challenges, addressing which contributes to the construction of a
relevance-driven syllogistic process; a type of process that is geared towards the derivation of contextual effects that are
relevant to the aim of solving the puzzle.
The copula sendá in the revitalization of Palenquero Creole
Authors: Marsella Mara 
Published: January 2025

Abstract
This study provides a first description of the distribution of the copular items of the Spanish-lexified Creole
Palenquero (San Basilio de Palenque, Colombia). Notably, besides the descriptions of the occurrence of the oppositional couple
ta/é (and its variants era and jue), the distribution of
the third and most innovative copula sendá (< Sp. sentar(se) ‘to sit’) has not yet been
clarified. This study reveals that the distribution of the copulas é/jue/era ~ sendá is stratified by age.
Although sendá has been recorded in previous traditional corpora with low frequency of occurrence, this paper
demonstrates that young Palenquero speakers nowadays regularly select the copula sendá in both attributive and
identificational equative copular constructions. Elderly traditional speakers prefer using the copulas é, jue,
and era in this context. The change in usage is particularly prevalent among second language users of Palenquero
who acquired it as part of language revitalization activities.
The use of traditional herbal medicine in Pakistani dentistry and mechanistic overview of some phytochemicals against oral and dental disease categories
Authors: Asad Syed Aizad , Asad Syed Rohid , Khan Malaika , Asad Syed Aswad , Hussain Adil 
Published: January 2025

Abstract

Due to the chronic nature and rapid development, oral and dental diseases remained major health concerns. In this regard, herbal medicines could be very vital in controlling such complications. Here, we provide a comprehensive data on plants used as alternate medicine against oral and dental diseases in Pakistan with an overview of reported mechanisms of action of some phytochemicals against these diseases. Data were searched across scientific databases including Scopus, PubMed, Web of Science, SciELO and Science Direct with particular keywords. Overall, 234 plants from 177 genera of 77 plant families have been reported in Pakistan against oral and dental diseases.
Acacia
and
Solanum
with 6 species each,
Rumex
and
Ficus
with 4 species each,
Artemisia
,
Ferula, Plantago
and
Tephrosia
with 3 species each were maximally used against dental diseases. Herb remained the highly prevalent growth habit for 125 species (54%), following shrubs (56 species, 24%) and tree (50 species, 21%). A total of 16 different plant parts were used as medicine where leaves (97 species, 41.45%), roots (66 species, 28.20%) and stem (34 species, 14.52%) were highly used parts with 15 modes of remedies where decoction (77 species), raw form (69 species) and powder (60 species) were highly preferred modes. The plants were used against 15 oral and dental diseases maximally against toothache (189 species) and gum infections (39 species). Further, the review presented possible mechanisms of action of some phytochemicals against major oral and dental diseases. The data provides crucial information in curing oral and dental complications and further studies are recommended to clarify their safety and effectiveness.
Sputtering yields and induced contamination of Kapton, PEEK and PTFE under xenon ion bombardment
Authors: Nicolas L , Villemant M , Paulmier T 
Published: January 2025

Abstract
In this article, we present the results of sputtering yield measurements of Kapton, polyether ether ketone (PEEK) and polytetrafluoroethylene (PTFE) due to xenon ion bombardment. We measured these yields using the weight loss technique, for energies ranging from 350 to 800 eV and incidence angles from 0 to 75∘. Polymers sputtering yield dependence versus incidence angle appears to be much lower than what we usually observe in other materials (such as metals). Furthermore, PTFE exhibits a very high erosion rate, which is 2 orders of magnitude larger than Kapton and PEEK ones. We also performed collection measurements using a quartz crystal microbalance apparatus. Such a method provides differential sputtering that yields data which are key pieces of information regarding satellite contamination issues. We also computed the total sputtering yields obtained by this second method, and it appears that they are much smaller than the ones measured previously by weight loss, especially for PTFE. This suggests that erosion products may be of different types (atoms, molecules) which are not all able to stick on a facing surface.
Ultrafast expansion kinetics of femtosecond laser-induced optical breakdown in bulk fused silica
Authors: Ur Rehman Zia , Nguyen V H , Janulewicz Karol Adam 
Published: January 2025

Abstract
In this study, we employ femtosecond pump–probe transmission microscopy and complex Nomarski interferometry to investigate the ultrafast dynamics of laser-induced plasma and shock waves in bulk fused silica subjected to high laser intensities. It was found that the plasma channel, in its development, takes on a columnar shape with minimal variations during the early expansion stage between 130 and 200 ps. However, after 200 ps, the cylindrical shock wave commenced its departure from the plasma channel and gradually expanded outward along the radial direction. An electron density in the evolving plasma channel approached a level of

∼

1.9
∗

10

20

cm

−
3

, at a delay time of 50 ps. The resulting change in refractive index caused by electronic plasma was 0.05, while the reflectivity of the probe beam was ≈0.03

%

. The blast wave model described the plasma and cylindrical shock wave expansion. A pressure of 65 GPa and a plasma temperature of a few eV were registered at a delay time of 150 ps. The resulting extreme conditions mapped to the cross-section analysis of the void and shock wave-affected area reveal polycrystalline structures near the periphery of the cavity at the geometrical focus. The areas more distant from the focus tend to show an amorphous character. These findings enrich the interpretation of femtosecond laser–dielectric interactions, with significant implications for micromachining, optical data storage, and the advancement of photonic device technologies.
High spin–orbit torque efficiency in Pt/Co/Tb/W repetition structures with broken spatial inversion symmetry
Authors: Tokunaga Kazuhiko , Kurokawa Yuichiro , Zhang Lin , Yuasa Hiromi 
Published: January 2025

Abstract
Spin–orbit torque (SOT) is an attractive phenomenon as a method of current-induced control of magnetization obtained at the interface between the heavy metal and magnetic layers. We investigate the SOT dependence of the stacking structure, namely [Pt/Co]
n
, [Pt/Co/Tb]
n
, or [Pt/Co/Tb/W]
n
where n is the repetition number because the repetition structure guarantees the thermal stability of magnetization. Whereas the SOT is negligibly small in the repetition structure [Pt/Co]10 because the SOT between the top and bottom Pt is cancelled out, we observe a finite SOT in [Pt/Co/Tb]10 induced by breaking the spatial inversion symmetry. Furthermore, the SOT of [Pt/Co/Tb/W]10 was more than three times higher than that of [Pt/Co/Tb]10 because the net spin Hall torque was enhanced by sandwiching Co with Pt and W with opposite polarity of spin Hall angles. In addition, we clarified that the magnetization is reduced due to the intermixing at the Co/Tb interface by x-ray diffraction and composition depth profiles, which is another reason for the SOT improvement. These results are expected to provide a new foothold for the control of magnetization in various spintronic devices.
2D surface optical reflectance for use in harsh reactive environments
Authors: Zetterberg J , Larsson A , Grespi A , Pfaff S , Rämisch L , Merte L R , Lundgren E 
Published: January 2025

Abstract
In recent years, studies of surfaces at more realistic conditions has advanced significantly, leading to an increased understanding of surface dynamics under reaction conditions. The development has mainly been due to the development of new experimental techniques or new experimental approaches. Techniques such as High Pressure Scanning Tunneling/Force Microscopy, Ambient Pressure x-ray Photo emission Spectroscopy, Surface x-ray Diffraction, Polarization-Modulation InfraRed Reflection Absorption Spectroscopy and Planar Laser Induced Fluorescence at semi-realistic conditions has been used to study planar model catalysts or industrial materials under operating conditions. 2D-Surface Optical Reflectance has recently received attention as a useful experimental tool used in gaseous and liquid harsh conditions by providing complementary experimental information on planar model samples as well as being a powerful experimental tool on its own. The simplicity of the approach and the cost of the equipment makes it an attractive alternative and useful tool for surface science studies under reaction conditions. In this topical review, we review some recent studies that have been promoted by the technical development in optical components, image acquisition and computational image analysis.
A novel decomposition-reconstruction-prediction hybrid model to predict precipitable water vapor from GNSS observations
Authors: Wu Fanming , Li Dengao , Zhao Jumin , Jiang Hairong , Shi Danyang 
Published: January 2025

Abstract
Precipitable water vapor (PWV) is one of the key factors in weather disaster preparedness and water forecasting. Due to the nonlinearity and nonstationarity of the PWV sequence, the existing models cannot achieve stable prediction accuracy. Therefore, this paper proposes a novel decomposition–reconstruction-prediction hybrid prediction model, named improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN)-permutation entropy (PE)-autoregressive integrated moving average with exogenous (ARIMAX)-one-dimensional convolution neural network-bidirectional long-short-term memory (1D CNN-BiLSTM), for predicting PWV. Firstly, the PWV sequence derived from the Global Navigation Satellite System (GNSS) is decomposed using the ICEEMDAN. Secondly, the PE of each decomposed modal is calculated and the PWV sequence is reconstructed into low- and high-frequency components. Then, considering spatio–temporal information, geographic information and meteorological data (longitude, latitude, altitude, day of year, hour of day, surface air pressure and temperature) aided modeling, the low- and high-frequency components are predicted using ARIMAX and 1D CNN-BiLSTM, respectively, and superimposed to obtain the predicted value and prediction intervals. Finally, the proposed model is validated for performance using the PWV derived from six GNSS stations. Compared with other models, the results show that ICEEMDAN-PE-ARIMAX-1D CNN-BiLSTM significantly improves PWV prediction performance, the mean root mean square errors for the six stations are 0.3765 mm, 0.7517 mm and 1.4696 mm for the 1 h, 12 h, and 24 h forecasts, respectively.