bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel GSIP: GAN-based sperm-inspired pixel imputation for robust energy image reconstruction
Authors: Mahmoud Gamal M. , Said Wael , Fadel Magdy M. , Elbaz Mostafa
Published: January 2025

Missing pixel imputation is a critical task in image processing, where the presence of high percentages of missing pixels can significantly degrade the performance of downstream tasks such as image segmentation and object detection. This paper introduces a novel approach for missing pixel imputation based on Generative Adversarial Networks (GANs). We propose a new GAN architecture incorporating an identity module and a sperm motility-inspired heuristic during filtration to optimize the selection of pixels used in reconstructing missing data. The intelligent sperm motility heuristic navigates the image’s pixel space, identifying the most influential neighboring pixels for accurate imputation. Our approach includes three essential modifications: (1) integration of an identity module within the GAN architecture to mitigate the vanishing gradient problem; (2) introduction of a metaheuristic algorithm based on sperm motility to select the top 10 pixels that most effectively contribute to the generation of the missing pixel; and (3) the implementation of an adaptive interval mechanism between the discriminator’s actual value and the weighted average of the selected pixels, enhancing the generator’s efficiency and ensuring the coherence of the imputed pixels with the surrounding image context. We evaluate the proposed method on three distinct datasets (Energy Images, NREL Solar Images, and NREL Wind Turbine Dataset), demonstrating its superior performance in maintaining pixel integrity during the imputation process. Our experiments also confirm the approach’s effectiveness in addressing everyday challenges in GANs, such as mode collapse and vanishing gradients, across various GAN architectures.
Water and seawater splitting with MgB2 plasmonic metal-based photocatalyst
Authors: Kravets Vasyl G. , Grigorenko Alexander N.
Published: January 2025

Plasmonic nanostructures can help to drive chemical photocatalytic reactions powered by sunlight. These reactions involve excitation of plasmon resonances and subsequent charge transfer to molecular orbitals under study. Here we engineered photoactive plasmonic nanostructures with enhanced photocatalytic performance using non-noble metallic MgB2 high-temperature superconductor which represents a new family of photocatalysts. Ellipsometric study of fabricated MgB2 nanostructures demonstrates that this covalent binary metal with layered graphite-like structure could effectively absorb visible and infrared light by excitation of multi-wavelengths surface plasmon resonances. We show that a MgB2 plasmonic metal-based photocatalyst exhibit fundamentally different behaviour compared to that of a semiconductor photocatalyst and provides several advantages in photovoltaics applications. Excitation of localised surface plasmon resonances in MgB2 nanostructures allows one to overcome the limiting factors of photocatalytic efficiency observed in semiconductors with a wide energy bandgap due to the usage of a broader spectrum range of solar radiation for water splitting catalytic reactions conditioned by enhanced local electromagnetic fields of localised plasmons. Excitation of localised surface plasmon resonances induced by absorption of light in MgB2 nanosheets could help to achieve near full-solar spectrum harvesting in this photocatalytic system. We demonstrate a conversion efficiency of ~ 5% at bias voltage of V

bias
 = 0.3 V for magnesium diboride working as a catalyst for the case of plasmon-photoinduced seawater splitting. Our work could result in inexpensive and stable photocatalysts that can be produced in large quantities using a mechanical rolling mill procedure.
Genome-wide identification, characterization, and functional analysis of the CHX, SOS, and RLK genes in Solanum lycopersicum under salt stress
Authors: Maghraby Amaal , Alzalaty Mohamed
Published: January 2025

The cation/proton exchanger (CHX), salt overly sensitive (SOS), and receptor-like kinase (RLK) genes play significant roles in the response to salt stress in plants. This study is the first to identify the SOS gene in Solanum lycopersicum (tomato) through genome-wide analysis under salt stress conditions. Quantitative reverse transcription PCR (qRT-PCR) results indicated that the expression levels of CHX, SOS, and RLK genes were upregulated, with fold changes of 1.83, 1.49, and 1.55, respectively, after 12 h of exposure to salt stress. Genome-wide analysis revealed 21 CHX, 5 SOS, and 86 RLK genes in S. lycopersicum. CHX genes were found on chromosomes 2, 3, 4, 5, 6, 7, 8, 9, 11, and 12 of S. lycopersicum. SOS genes were found on chromosomes 1, 4, 6, and 10. RLK genes were found on all chromosomes of S. lycopersicum. The Ka/Ks ratios indicate that the CHX, SOS, and RLK genes have been primarily influenced by purifying selection. This suggests that these genes have faced strong environmental pressures throughout their evolution. Purifying selection typically results in a decrease in genetic diversity. The estimated duplication time for CHX paralogous gene pairs ranged from approximately 26.965 to 245.413 million years ago (Mya), while the duplication time for SOS paralogous gene pairs ranged from around 116.682 to 275.631 Mya. For RLK paralogous gene pairs, the duplication time varied from approximately 27.689 to 239.376 Mya. Synteny analysis of the CHX, SOS, and RLK genes demonstrated collinear relationships with orthologous genes in Arabidopsis thaliana, but no collinearity orthologous relationships in Oryza sativa (rice). Furthermore, the analysis revealed that there were 6 orthologous SlCHX genes, 2 orthologous SlSOS genes, and 44 orthologous SlRLK genes paired with those in A. thaliana. The results of the present study may help to elucidate the role of the CHX, SOS, and RLK genes in salt stress in S. lycopersicum.
Patchiness of plankton ecosystem structure due to nutrient mixing along the shelf edge in the North Sea
Authors: Cordier Axelle , Bendtsen Jørgen , Daugbjerg Niels , From Nikolaj , Jónasdóttir Sigrún Huld , Mousing Erik Askov , Christensen Jens Tang , Silva Teresa , Richardson Katherine
Published: January 2025

Mid-water column turbulence has been shown to cause elevated vertical nutrient flux at the shelf edge in the northeastern North Sea. Here, we demonstrate that phytoplankton communities in this region tend to be dominated by larger cells (estimated from percentage of chlorophyll captured on a 10 μm filter) than beyond the shelf edge. Fv/Fm (PSII electron transport capacity) corrected for photoinhibition in the surface layer correlated in this study with the percentage of chlorophyll captured on a 10 µm filter (assumed to be large cells), suggesting that the phytoplankton community was responding to increased nutrients in the euphotic zone by increasing photosynthetic efficiency and altering community composition. The greatest abundances of larger copepods and the highest rates of Centropages typicus egg production were also generally found at the shelf edge. These results suggested that impact from increased nutrient fluxes cascaded up the planktonic food web. As these regions of nutrient flux were very localised, this led to sub-mesoscale heterogeneity in plankton ecosystem structure. Reports of higher abundances of fish and mammals at the shelf edge are common and we hypothesise that their distributions are a response to the impact of mid-water column nutrient upwelling on the plankton food web in the region.
Optimising detector readout settings for the detection of spatial correlations between SPDC photon-pairs
Authors: Roberts K. , Gregory T. , Wolley O. , Padgett M. J.
Published: January 2025

SPDC photon-pairs exhibit spatial correlations which can be measured using detector arrays sensitive to single photons. However, these detector arrays have multiple readout modes and in order to optimise detection it is important to select the optimum mode to detect the correlations against a background of optical and electronic noise. These quantum correlations enable applications in imaging, sensing, communication, and optical processing. Here we compare the measurement of spatial correlations for a broad range of readout modes of an EMCCD camera and attempt to characterise the optimal readout mode for our purposes. This assessment is important for the use of detector arrays of different types for use in quantum, low-light, enhanced resolution, imaging systems.
Qualitative comparison of decalcifiers for mouse bone cryosections for subsequent biophotonic analysis
Authors: Mandal Shibarjun , Motganhalli Ravikumar Ramya , Tannert Astrid , Urbanek Annett , Guliev Rustam R. , Naumann Max , Coldewey Sina M. , Dahmen Uta , Carvalho Lina , Bastião Silva Luís , Neugebauer Ute
Published: January 2025

Bone tissue, with its complex structure, often necessitates decalcification of the hard tissue for ex vivo morphological studies. The choice of a suitable decalcification method plays a crucial role in preserving desired features and ensuring compatibility with diverse imaging techniques. The search for a universal decalcification method that is suitable for a range of biophotonic analyses remains an ongoing challenge. In this study, we systematically assessed five standard bone decalcification protocols, encompassing strong mineralic acids (3% and 5% nitric acid), a commercially available formulation of hydrochloric and formic acid), as well as weak organic acids (5% trichloroacetic acid and 8% formic acid), and a chelating agent (25% ethylenediamine-tetraacetic acid) with varying decalcification durations, using mouse long bones as our experimental model. Our imaging analysis panel included classical histological staining (Hematoxylin and Eosin, H&E), immunofluorescence staining, and label-free Raman microspectroscopic imaging. We used cryosections instead of paraffin sections since paraffin interferes with tissue Raman signals. This approach is not as commonly used as it is more prone to handling artifacts, but is the preferred method for subsequent Raman analysis. Decalcification efficacy was evaluated based on various qualitative and some quantitative imaging parameters by 2–3 independent observers. Our systematic approach revealed that the chelating agent, when used for 24 h, optimally preserved bone features and, thus, would be the ideal decalcifying agent for comprehensive subsequent analysis. However, the choice of decalcifier and the ideal decalcification duration may vary depending on the type and thickness of bone, necessitating tailored adjustments to meet specific experimental requirements.
Impact of early initiation of renal replacement therapy in patients on venoarterial ECMO using target trial emulation with Japanese nationwide data
Authors: Kubo Toshihiro , Takeuchi Tomonori , Inoue Norihiko , Cama-Olivares Augusto , Chandramohan Deepak , Tolwani Ashita J. , Wille Keith M. , Fushimi Kiyohide , Neyra Javier A. , Wakabayashi Kenji
Published: January 2025

While renal replacement therapy (RRT) allows for precise fluid management as well as addressing electrolyte imbalances and the removal of other necessary compounds, its early initiation has not shown benefit in the general critically ill population. Moreover, the effects of early RRT initiation specifically in patients on venoarterial extracorporeal membrane oxygenation (VA-ECMO) also remain unclear. This retrospective study investigated adult patients who underwent VA-ECMO between April 2018 and March 2022 and used the clone-censor-weight method to emulate a hypothetical target trial and compare two groups: patients who initiated RRT within 2 days of VA-ECMO initiation (Early) and those who did not (Late). The primary outcomes were 28-day and 90-day hospital mortality analyzed by Cox proportional hazards models and the secondary outcome was 90-day RRT dependence by pooled logistic regression models. Inverse probability censoring weights were applied to adjust the models. A total of 2,513 VA-ECMO patients were cloned into both groups. The 28-day and 90-day mortalities were lower in the Early group (HR 0.59 [95% CI 0.53–0.68] and 0.67 [0.61–0.75]). However, the early group experienced greater RRT dependence at 90 days than the late group (OR 2.58 [1.94–3.46]). In conclusion, early initiation of RRT (within 2 days of VA-ECMO) was associated with lower hospital mortality but with a higher likelihood of 90-day RRT dependence in adult patients on VA-ECMO.
Repeated 5-aminolevulinic acid mediated sonodynamic therapy using magnetic resonance guided focused ultrasound in rat brain tumour models
Authors: Wu Sheng-Kai , Tsai Chia-Lin , Mir Aisha , Marcus Stuart L. , Hynynen Kullervo
Published: January 2025

Sonodynamic therapy is an emerging therapeutic approach against brain tumours. However, the treatment scheme and ultrasound parameters have yet to be explored for clinical translation. Our study aimed to optimize ultrasound parameters for sonodynamic therapy (SDT) with 5-ALA as a sonosensitizing agent and to evaluate its therapeutic outcome on the rodent 9L gliosarcoma and the human U87 glioblastoma models. We stereotactically implanted brain tumour cells in rats and monitored tumour volume via MRI. SDT was conducted weekly using a 60 mg/kg dose of 5-ALA, injected intravenously 6 h before sonication. We used a driving frequency of 580 kHz with 0.75 MPa and evaluated the effect of different burst lengths to optimize ultrasound parameters. We also tested SDT against advanced-stage brain tumours to verify its efficacy further. Our results showed that a longer burst length could improve therapeutic outcomes. Tumour growth inhibition was established only in the first three weeks with 10 ms and 50 ms burst length sonication, but 86 ms burst length greatly improved the survival outcome. Therefore, the therapeutic efficacy is proportionate to the burst length and, thus, the total delivered energy. Repeated SDT using multiple targets to cover the entire tumour volume with optimal ultrasound parameters can achieve significant anti-tumour effects in both 9L and U87 models. Lastly, our results on late-stage tumour treatments showed that SDT can still provide prolonged survival. These promising findings demonstrate that repeated SDT using transcranial-focused ultrasound together with 5-ALA can optimize anti-tumour effects and even lead to complete clearance of the tumours. This weekly treatment with pulsed ultrasound sonication strategy is practical for future clinical translation.
The optimal grouting area and cable distribution design for guaranteeing roadway stability while considering fluid mechanical effects via the CMOEAD algorithm
Authors: Li Peng , Guo Yinghai , Cheng Yinghao , Zhang Jiaming
Published: January 2025

Water inrush in roadways frequently occurs in coal mines when the rock mass is enriched with underground water. To avoid underground water flow into the roadway and guarantee the stability of the roadway, grouting and cables are commonly used to prevent water inrush and guarantee the stability of the roadway. In this work, FLAC3D (fast lagrangian analysis of continua 3 dimension) numerical simulation software was used, and the fluid‒mechanical coupling effects were considered. In combination with the CMOEAD (constrained multi-objective evolution algorithm based on decomposition) optimization method, the optimal grouting area and cable distribution were determined: the center point of the ellipse (grouting area) is (0.01, 1.59), the long axis length is 4.73 m, the short axis length is 4.60 m, and the inclination angle of the ellipse is 53.15°. The cable length is 6.51 m, the total number of cables is 11. The grouting area and cable distribution design from numerical simulation results were applied to engineering practice, the degree of water inrush was markedly reduced, and the displacement of the roadway was within control, indicating that the proposed method is workable and reliable.
Advancing macromolecular structure determination with microsecond X-ray pulses at a 4th generation synchrotron
Authors: Orlans Julien , Rose Samuel L. , Ferguson Gavin , Oscarsson Marcus , Homs Puron Alejandro , Beteva Antonia , Debionne Samuel , Theveneau Pascal , Coquelle Nicolas , Kieffer Jerome , Busca Paolo , Sinoir Jeremy , Armijo Victor , Lopez Marrero Marcos , Felisaz Franck , Papp Gergely , Gonzalez Herve , Caserotto Hugo , Dobias Fabien , Gigmes Jonathan , Lebon Guillaume , Basu Shibom , de Sanctis Daniele
Published: January 2025

Serial macromolecular crystallography has become a powerful method to reveal room temperature structures of biological macromolecules and perform time-resolved studies. ID29, a flagship beamline of the ESRF 4th generation synchrotron, is the first synchrotron beamline in the world capable of delivering high brilliance microsecond X-ray pulses at high repetition rate for the structure determination of biological macromolecules at room temperature. The cardinal combination of microsecond exposure times, innovative beam characteristics and adaptable sample environment provides high quality complete data, even from an exceptionally small amount of crystalline material, enabling what we collectively term serial microsecond crystallography (SµX). After validating the use of different sample delivery methods with various model systems, we applied SµX to an integral membrane receptor, where only a few thousands diffraction images were sufficient to obtain a fully interpretable electron density map for the antagonist istradefylline-bound A2A receptor conformation, providing access to the antagonist binding mode. SµX, as demonstrated at ID29, will quickly find its broad applicability at upcoming 4th generation synchrotron sources worldwide and opens a new frontier in time-resolved SµX.
Two types of motifs enhance human recall and generalization of long sequences
Authors: Wu Shuchen , Thalmann Mirko , Schulz Eric
Published: January 2025

Whether it is listening to a piece of music, learning a new language, or solving a mathematical equation, people often acquire abstract notions in the sense of motifs and variables—manifested in musical themes, grammatical categories, or mathematical symbols. How do we create abstract representations of sequences? Are these abstract representations useful for memory recall? In addition to learning transition probabilities, chunking, and tracking ordinal positions, we propose that humans also use abstractions to arrive at efficient representations of sequences. We propose and study two abstraction categories: projectional motifs and variable motifs. Projectional motifs find a common theme underlying distinct sequence instances. Variable motifs contain symbols representing sequence entities that can change. In two sequence recall experiments, we train participants to remember sequences with projectional and variable motifs, respectively, and examine whether motif training benefits the recall of novel sequences sharing the same motif. Our result suggests that training projectional and variables motifs improve transfer recall accuracy, relative to control groups. We show that a model that chunks sequences in an abstract motif space may learn and transfer more efficiently, compared to models that learn chunks or associations on a superficial level. Our study suggests that humans construct efficient sequential memory representations according to the two types of abstraction we propose, and creating these abstractions benefits learning and out-of-distribution generalization. Our study paves the way for a deeper understanding of human abstraction learning and generalization.
Crafting tailored, well-defined block copolymers of cyclic esters with an organomagnesium initiator
Authors: Nath Priyanku , Sagar Shweta , Ray Aranya , Karmakar Himadri , Sarkar Alok , Chandrasekhar Vadapalli , Panda Tarun K.
Published: January 2025

An efficient route to synthesize block copolymers of ε-CL and rac-LA via ROCOP and sequential addition in the presence of a magnesium catalyst is reported. All the reactions were performed without using any external initiator.
Metallic vanadium activated by an in situ dissolution–deposition process for a superior aqueous zinc ion battery cathode
Authors: Guo Kai , Li Ye , Yang Changchen , Xiang Yijing , Pan Shanqi , Zeng Qingpu , Li Zhuyao , Yu Neng , Wang Xianfu
Published: January 2025

Metallic vanadium is in situ oxidized into amorphous V2O5·3H2O exhibiting excellent capability for storing Zn2+ in aqueous zinc ion batteries.
Modulating electronic properties in hydrogenated silicon nanotubes
Authors: Liu Hsin-Yi , Wu Jhao-Ying
Published: January 2025

Hydrogen adsorption on SiNTs tunes bandgaps, with full adsorption enhancing stability and partial adsorption inducing metallicity.
Recent progress in understanding the role of graphene oxide, TiO2 and graphene oxide–TiO2 nanocomposites as multidisciplinary photocatalysts in energy and environmental applications
Authors: Badoni Ayush , Thakur Sahil , Vijayan Narayanasamy , Swart Hendrik Christoffel , Bechelany Mikhael , Chen Zhengsen , Sun Shuhui , Cai Qiran , Chen Ying , Prakash Jai
Published: January 2025

A review on graphene oxide (GO)–TiO2 nanocomposites with emphasis on the role of GO as a co-catalyst and photocatalyst, providing a synergistic effect as well as multidisciplinary photocatalytic activities in the fields of energy and the environment.
Deep learning for augmented process monitoring of scalable perovskite thin-film fabrication
Authors: Laufer Felix , Götz Markus , Paetzold Ulrich W.
Published: January 2025

Augmenting characterization methods with deep learning and other machine learning methods allows the identification of material inconsistencies, device performance predictions, and the generation of in situ AI recommendations.
Interface diagnostics platform for thin-film solid-state batteries
Authors: Ferrari Victoria C. , Lee Sang Bok , Rubloff Gary W. , Stewart David M.
Published: January 2025

Understanding the impedances of battery materials remains a major challenge. Features of Electrochemical Impedance Spectroscopy (EIS) can now be accurately attributed using a new materials-agnostic methodology.
Molten salt electrolytes with enhanced Li+-transport kinetics for fast-cycling of high-temperature lithium metal batteries
Authors: Yan Shuaishuai , Yao Nan , Liu Hao , Zhang Zheng , Lu Yang , Liu Zhi , Hou Wenhui , Zhou Pan , Zhou Hangyu , Chen Xiang , Liu Kai , Zhang Qiang
Published: January 2025

A solvent-free molten salt electrolyte with enhanced Li+-transport kinetics was reported for high-temperature lithium batteries. The cation–cation concerted effect and inorganic CEI/SEI interphases endow fast-cycling and long-cycling abilities.
Seasonal variation and risk assessment for the presence of pharmaceuticals in Brazilian urban rivers
Authors: dos Santos Miraldo Santa Rosa , Vidal Cristiane , Santos Vinicius Sarracini , Domingues Ramon , Montagner Cassiana Carolina
Published: January 2025

A comparative analysis of the occurrence of pharmaceuticals in four water bodies across three Brazilian metropolitan areas shows that the contamination level in water depends on the river basin use and occupation, but is less related to seasonality.
Dietary polyphenols for tumor therapy: bioactivities, nano-therapeutic systems and delivery strategies
Authors: Wang Minglu , Wang Ying , Zhang Hongyan
Published: January 2025

This review provides a comprehensive evaluation of the anti-tumor bioactivities and delivery strategies of dietary polyphenols, as well as their application in the development of nano-therapeutic systems for tumor.
Zwitterionic alcoholic solutions for integrated CO2 capture and hydrogenation
Authors: Cândido Bruno A. , Zanirati Marcelli L. C. , dos Santos Francisco P. , Villarreal Wilmer , Dupont Jairton , Migowski Pedro
Published: January 2025

Zwitterionic phenolate bases are superior to tertiary amines to capture CO2 in alcohols as alkylcarbonates (AKC). An integrated CO2 capture and conversion scheme that reduces these AKC to formate or methanol with H2 using Ru catalysts was developed.
Construction of organic heterojunctions as metal-free photocatalysts for enhancing water splitting and phenol degradation by regulating charge flow
Authors: You Yang , Shi Xiaoyu , Huang Liang , Zhao Jie , Ji Wen , Li Libo , Bu Donglei , Huang Shaoming
Published: January 2025

Electron–hole separation efficiency and catalytic site activity can be simultaneously enhanced by tuning the charge flow direction.
Polyglyoxylamide hydrogels for the traceless stimulus-mediated release of covalently-immobilized drugs
Authors: Gong Jue , Tavsanli Burak , Gillies Elizabeth R.
Published: January 2025

Depolymerizable polyglyoxylamides with pendent azides and photocleavable drug linkers were combined with 4-arm PEG-alkyne to obtain hydrogels. Traceless drug release was achieved with light, while depolymerization was accelerated by mild acid.
Synthesis and properties of pure and intergrown CHA/PHI zeolites from inorganic multi-cation colloidal suspensions
Authors: Magisson Aymeric , Clatworthy Edwin B. , Piva Diógenes Honorato , Ghojavand Sajjad , Lebedev Oleg I. , Mintova Svetlana
Published: January 2025

Pure and intergrown CHA/PHI nanocrystalline zeolites are synthesised using multiple inorganic cations as structure directing agents only, whereby the amount of each zeolite phase can be tuned. Their CO2 and N2 adsorption properties are explored.
Excited Pd-catalyzed dearomative 1,4-dicarbofunctionalization of nonactivated aromatic rings
Authors: Jiang Kai , Zhao Ziyan , Yin Xiaodong , Chen Fangjun , Yin Biaolin
Published: January 2025

1,4-difunctionalization of nonactivated arenes has been accomplished by the excited-palladium catalysis via the radical generation of a cyclohexadienyl-Pd(ii) intermediate.
Dibenzyl isophthalates as versatile hosts in room temperature phosphorescence host–guest systems
Authors: Molkenthin Martin , Hupf Emanuel , Nachtsheim Boris J.
Published: January 2025

Simple yet powerful: dibenzyl isophthalates are easy to modify hosts for room-temperature phosphorescence. These systems achieve record-setting quantum yields and lifetimes while offering unprecedented color tunability across the visible spectrum.
Microtextured coatings from superhydrophobic bark-derived bioparticles for fog harvesting
Authors: Mhatre Sameer , Niu Xun , Rojas Orlando
Published: January 2025

Microtextured hybrid coatings made from superhydrophobic bioparticles derived from birch bark greatly enhance the water collection efficiency of fog harvesters.
Optimisation of a P3 phase with superior high voltage reversibility
Authors: Linnell Stephanie F. , Choi Yong-Seok , Liao Yingling , Pateli Ioanna M. , Naden Aaron B. , Irvine John T. S. , House Robert A. , Scanlon David O. , Armstrong A. Robert
Published: January 2025

The electrochemical performance of P3-structure Na0.7Mn0.75Ni0.25O2 has been optimised via chemical substitutions, with Na0.7Mn0.58Ni0.25Zn0.07Ti0.1O2 showing best cyclability. Properties are explained by combined experimental and DFT results.
Revealing the surface oxidation mechanism and performance evolution of Nd–Fe–B sintered magnets
Authors: Zhou Liang , Jin Jiaying , Chen Wang , Ren Shaoqing , Bu Mengfan , Li Xu , Xin Bo , Wu Chen , Yan Mi
Published: January 2025

Via wide-range oxidation experiments, a new strategy of constructing tunable surface oxidation layer is proposed, generating an excellent synergy of improved corrosion resistance and mechanical performance without compromising magnetic properties.
Optimizing the short-wavelength infrared photoluminescence quantum yield and brightness of Er3+, Yb3+ co-doped yttrium orthophosphate phosphors for tracer-based sorting
Authors: Bhiri Nisrin Mohamed , Duim Herman , Madirov Eduard , Nyarige Justine , Richards Bryce S. , Turshatov Andrey
Published: January 2025

Development of efficient inorganic luminescent tracers is essential for various applications, including plastic sorting.
Engineering of imidazo[1,2-a]pyridine into multifunctional dual-state emissive (DSE) luminogens for hydrazine sensing and cell-imaging
Authors: Yashwantrao Gauravi , Gosavi Prajakta , Naik Vaishnavi , Debnath Monalisha , Seth Saona , Badani Purav , Srivastava Rohit , Saha Satyajit
Published: January 2025

Balancing the donor–acceptor (D–A) systems and spatial configurations to precisely modulate dual-state emission (DSE) properties in imidazo[1,2-a]pyridine-derived luminogens for applications in cell imaging and hydrazine sensing.
Design and analysis of a vertically extended gate field effect transistor (VEG-FET)-based hydrogen gas sensor: a comprehensive modeling and simulation approach
Authors: Martha Pramod , Kohli Mayank , Kumar Rahul , Behera Santosh Kumar
Published: January 2025

In this work, Pt–H2 interaction and Pt work function dependency on H2 pressure and desorption area were modeled. Based on the analysis, a novel vertically extended gate FET (VEG-FET) based amplifier was developed for varying H2 pressures.
Teletraining to Teach Communication Partners to Support Students With Multiple Disabilities Including Cortical Visual Impairment and Emerging Symbolic Communication in Communicating Choices
Authors: McCarty Tara V. , Light Janice C.
Published: January 2025

Purpose:

The purpose of the current study was to investigate the impact of a teletraining to teach adult communication partners the “Communicating Choices–Cortical Visual Impairment (CVI)” strategy to support participation for students with multiple disabilities.

Method:

A nonconcurrent, multiple-probe, across-participants design was implemented with four adult communication partner (i.e., speech-language pathologist, paraeducators, and parent) and student dyads to determine the effects of a teletraining administered over a video-calling platform on the partner's implementation of the substeps from the Communicating Choice–CVI strategy. Dyads completed a randomly predetermined number of baseline sessions, two teletraining sessions to instruct the partners in the strategy, and five intervention probes.

Results:

Results of the study indicated that communication partners successfully implemented an increased number of the strategy substeps following two short teletraining sessions and that all students communicated choices in every opportunity when they were provided with a structured opportunity. Communication partners reported that the strategy was successful for the students and that the strategy could be applied to other contexts or students.

Conclusions:

This study provides evidence for the importance of communication partner training for students with complex needs in domains such as vision and communication. Furthermore, the Communicating Choices–CVI strategy may lead to increased opportunities for academic participation, social engagement, and self-determination for students whose opportunities to take on active roles in educational settings are often severely restricted.

Supplemental Material:

https://doi.org/10.23641/asha.28108139
Cognitive Predictors of Perception and Adaption to Dysarthric Speech in Older Adults
Authors: Lansford Kaitlin L. , Hirsch Micah E. , Barrett Tyson S. , Borrie Stephanie A.
Published: January 2025

Purpose:

In effortful listening conditions, speech perception and adaptation abilities are constrained by aging and often linked to age-related hearing loss and cognitive decline. Given that older adults are frequent communication partners of individuals with dysarthria, the current study examines cognitive–linguistic and hearing predictors of dysarthric speech perception and adaptation in older listeners.

Method:

Fifty-eight older adult listeners (aged 55–80 years) completed a battery of hearing and cognitive tasks administered via the National Institutes of Health Toolbox. Participants also completed a three-phase familiarization task (pretest, training, and posttest) with one of two speakers with dysarthria. Elastic net regression models of initial intelligibility (pretest) and intelligibility improvement (posttest) were constructed for each speaker with dysarthria to identify important cognitive and hearing predictors.

Results:

Overall, the regression models indicated that intelligibility outcomes were optimized for older listeners with better words-in-noise thresholds, vocabulary knowledge, working memory capacity, and cognitive flexibility. Despite some convergence across models, unique constellations of cognitive–linguistic and hearing parameters and their two-way interactions predicted speech perception and adaptation outcomes for the two speakers with dysarthria, who varied in terms of their severity and perceptual characteristics.

Conclusion:

Here, we add to an extensive body of work in related disciplines by demonstrating age-related declines in speech perception and adaptation to dysarthric speech can be traced back to specific hearing and cognitive–linguistic factors.
Conflicting Evidence for a Motor Timing Theory of Stuttering: Choral Speech Changes the Rhythm of Both Neurotypical and Stuttering Talkers, but in Opposite Directions
Authors: Meekings Sophie , Eijk Lotte , Stankova Stefany , Maruthy Santosh , Scott Sophie Kerttu
Published: January 2025

Purpose:

Talking in unison with a partner, otherwise known as choral speech, reliably induces fluency in people who stutter (PWS). This effect may arise because choral speech addresses a hypothesized motor timing deficit by giving PWS an external rhythm to align with and scaffold their utterances onto. This study tested this theory by comparing the choral speech rhythm of people who do and do not stutter to assess whether both groups change their rhythm in similar ways when talking chorally.

Method:

Twenty adults who stutter and 20 neurotypical controls read a passage on their own and then a second passage chorally with a neurotypical partner. Their speech rhythm was evaluated using Envelope Modulation Spectrum (EMS) analysis to derive peak frequency, a measure of the dominant rate of modulation in the sound envelope, as well as peak amplitude (the amplitude of the peak frequency), across several octave bands associated with different features of speech.

Results:

The two groups displayed opposing patterns of rhythmic change during choral reading. People with a stutter increased their EMS peak frequency when they read chorally, while neurotypical talkers' choral speech was characterized by reduced peak frequency compared to solo reading.

Conclusions:

Our findings show that the choral speech rhythm of PWS differs from that of neurotypical talkers. This indicates limited support for the hypothesis that choral speech addresses a motor timing deficit by giving PWS a rhythmic cue with which to align.
Speech-Language Pathologists' Language Practices During Speech-Language Therapy for Bilingual Children
Authors: Gross Megan C. , Dubé Kylie
Published: January 2025

Purpose:

Previous research and clinical practice guidelines indicate that it is best practice to support bilingual children with communication disorders in both of their languages. However, there is a shortage of bilingual speech-language pathologists (SLPs) in the United States. Therefore, it is important to examine how SLPs with varying linguistic backgrounds serve their bilingual clients. This study investigated the language practices of SLPs during intervention with bilingual children and identified needed resources.

Method:

This convergent mixed-methods study included a survey and semistructured interviews, with interviewees sampled purposively based on survey responses. Quantitative analyses were examined alongside qualitative themes to address each research question.

Results:

Overall, 21.5% of the bilingual clients described by survey respondents were reported to receive intervention in both of their languages. SLPs who shared both languages with their clients and had a professional level of proficiency were more likely to provide services in both languages and to engage in code-switching during sessions. Qualitative analysis revealed creative strategies that SLPs used to overcome their own linguistic limitations when they lacked skills in a client's heritage language. Although practices varied based on the SLP's linguistic background, respondents identified similar priorities, including more bilingual providers and access to training, multilingual materials, and interpreters.

Conclusions:

This study contributes insights into how SLPs serve their bilingual clients and what resources are needed to improve services. Although this study focused on Massachusetts and had a small sample, the findings may apply to other states, and there may be benefits to addressing these questions at a state level to provide targeted advocacy, training, and resources.
Enhancement of first carbon hit rate in converter steelmaking through integrated learning‐based data cleansing
Authors: Yang Lingyun , Zhao Qianchuan , Li Tan , Gu Mu , Yang Kaiwu , Song Weining
Published: January 2025

First carbon hit rate (FCHR) is an essential indicator of steel converter smelting, reflecting the proportion of steel tapping completed without additional oxygen blowing. However, significant data loss has occurred due to equipment ageing and worker operations, resulting in difficulties in analysing the FCHR. This paper uses mechanism analysis and feature screening to determine the model input, predicts and fills in abnormal data through ensemble learning, and then optimises it through data transformation. Finally, the Stacking model predicts the FCHR, with a training accuracy of up to 94.5% and a test set accuracy of 90.5%. In addition, the authors also conducted a predictive study on oxygen consumption, and the hit rate performed well under different error thresholds, with a maximum of 97.9%. These results provide powerful decision support for steel production and effectively overcome the challenges of data missingness.
Enhancing intrusion detection against denial of service and distributed denial of service attacks: Leveraging extended Berkeley packet filter and machine learning algorithms
Authors: Anand Nemalikanti , M A Saifulla , Aakula Pavan Kumar , Ponnuru Raveendra Babu , Patan Rizwan , Reddy Chegireddy Rama Prakasha
Published: January 2025

As organizations increasingly rely on network services, the prevalence and severity of Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks have emerged as significant threats. The cornerstone of effectively addressing these challenges lies in the timely and precise detection capabilities offered by advanced intrusion detection systems (IDS). Hence, an innovative IDS framework is introduced that seamlessly integrates the extended Berkeley Packet Filter (eBPF) with powerful machine learning algorithms—specifically Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and TwinSVM—enabling unparalleled real‐time detection of DDoS attacks. This cutting‐edge solution provides a robust and scalable IDS framework to combat DoS and DDoS threats with high efficiency, leveraging eBPF's capabilities within the Linux kernel to bypass typical user space constraints. The methodology encompasses several key steps: (a) Collection of data from the renowned CIC‐IDS‐2017 repository; (b) Processing the raw data through a meticulous series of steps, including transmission, cleaning, reduction, and discretization; (c) Utilizing an ANOVA F‐test for the extraction of critical features from the preprocessed data; (d) Application of various ML algorithms (DT, RF, SVM, and TwinSVM) to analyze the extracted features for potential intrusion; (e) Implementing an eBPF program to capture network traffic and harness trained model parameters for efficient attack detection directly within the kernel. The experimental results reveal outstanding accuracy rates of 99.38%, 99.44%, 88.73%, and 93.82% for DT, RF, SVM, and TwinSVM, respectively, alongside remarkable precision values of 99.71%, 99.65%, 84.31%, and 98.49%. This high‐speed, accurate detection model is ideally suited for high‐traffic environments such as data centers. Furthermore, its foundational architecture paves the way for future advancements, including the potential integration of eBPF with XDP to achieve even lower‐latency packet processing. The experimental code is available at the GitHub repository link: https://github.com/NemalikantiAnand/Project.
KLMS‐Net: Deep unrolling for kernel least mean square algorithm
Authors: Tang Yu , Zhang Tingsen , Gao Jinrong , Bi Dongjie , Li Xifeng , Xie Yongle
Published: January 2025

The performance of the kernel least mean square (KLMS) algorithm heavily depends on the utilized kernel function and its associated parameters. To address this inherent limitation, this letter proposes a novel network framework based on the deep unrolling of KLMS (KLMS‐Net). KLMS‐Net transforms the iterative process of KLMS into the forward propagation of deep neural networks (DNNs), which learn the implicit feature mappings in a model‐driven manner, providing DNNs with explicit interpretability. Compared to standalone DNNs, KLMS‐Net compresses the size of the solution space of DNNs within the mathematical framework of KLMS. Through prediction experiments on nonlinear systems across various scenarios, KLMS‐Net exhibits significantly enhanced convergence speed and prediction accuracy, achieving improvements of approximately two orders of magnitude compared to the original KLMS and standalone DNNs. These findings highlight the substantial potential of KLMS‐Net in processing data with complex nonlinear structures and connect the fields of kernel adaptive filtering and deep learning.
YOLOv7‐SFWC: A detection algorithm for illegal manned trucks
Authors: Wu Xuan , Wang Yanan , Nie Tengtao , Pan Wenlin
Published: January 2025

Automatic analysis and evidence collection of obvious traffic violations, such as illegal manned trucks, is one of the critical operational challenges of the traffic police department's business. For the enormous volume of road surveillance images generated daily, traditional manual screening is highly time‐intensive and resource‐draining. Therefore, this article proposes an improved detection model YOLOv7‐SFWC for illegally manned trucks. First of all, the pictures of illegal manned vehicles obtained by relevant departments are expanded and labeled, and the dataset of illegal manned vehicles is created. Building upon the foundational YOLOv7 model, this study replaces the traditional convolution module with the FasterNet convolution module and SCConv module, and introduces the Wise‐IoU (WIoU) loss function algorithm and Coordinate Attention (CA) mechanism. The results show that the mAP value of the YOLOv7‐SFWC model is improved by 4.15% and FPS by 7.6 compared with the original YOLOv7 model, and the computational complexity is reduced to adapt to the deployment. Moreover, the model's effectiveness is validated through extensive comparison experiments. Finally, the visual results show the accurate performance of the model and verify the progress of YOLOv7‐SFWC. This advancement has the potential to transform traffic violation enforcement by reducing reliance on manual screening, effectively combating traffic violations, and purifying traffic order.
Polyvinyl chloride thermal stabilizer from high-acid crude rice bran oil: a non-food utilization of rice bran oil
Authors: Putrawan I Dewa Gede Arsa , Rahmawati Novia
Published: January 2025

Rice bran is a source of healthy oil which contains antioxidants and essential vitamins. Without pretreatment, the rapid activity of lipase enzyme causes the oil to contain high amounts of free fatty acids, making it unsuitable for edible purposes. In such cases, utilizing it for chemicals becomes an option. This study presents the synthesis of reverse ester organotin (REOT) as a thermal stabilizer for polyvinyl chloride (PVC) from high-acid crude rice bran oil. The success of the synthesis was confirmed through FTIR spectroscopy. The stabilizing effect of the resulting REOT was examined through dehydrochlorination and two-roll mill tests. Both tests confirmed that the obtained REOT could significantly increase the thermal stability of PVC. At relatively low dosages of 0.5 to 1.5 phr (parts per hundred resin), it maintained the initial color of PVC for up to 45–60 min when rolled under heating at 190 °C. Additionally, its thermal stabilizing effects were comparable to REOT derived from tall oil fatty acid (TOFA), a conventional raw material. The impact on flowability of PVC melt was also statistically similar to that of REOT from TOFA. Overall, crude rice bran oil fatty acid has been proven to be an effective alternative raw material for REOT based PVC thermal stabilizer.
Decision-making in clinical diagnostic for brain tumor detection based on advanced machine ‎learning algorithm‎
Authors: Huang Tangsen , Yin Xiangdong , Jiang Ensong
Published: January 2025

Brain tumors, abnormal growths in the brain or spinal canal, can be benign or malignant, causing symptoms like headaches, seizures, and cognitive decline by disrupting brain function. Therefore, developing reliable predictive models for diagnosis and prognosis is crucial. In this paper, the prediction of brain tumors is made using machine learning models enhanced by an optimizer, namely Escaping Bird Search Optimization. Optimized models incorporate Ada Boost Classifier (ADEB), Gaussian Process Classifier (GPEB), and Support Vector Classifier (SVC) which, after being tested on a few databases, were named ADEB, SVEB, and GPEB, respectively, and their predictive power was assessed. The best single model performance overall on all databases is the SVC with an average accuracy of 0.981, while among enhanced models, the optimized model, called SVEB, using SVC, attained the highest accuracy for all models and reached as high as 0.990. These findings underscore the role of optimization techniques and demonstrate the effectiveness of machine learning in predicting brain cancers. The improved performance of the enhanced SVC model, SVEB, suggests it could offer a reliable approach for accurate brain tumor prediction. Enhanced patient outcomes and early diagnosis could be an implication of this in the field of neuro-oncology.
Shapes of Regular Curves Defined by Hyperbolic Functions
Authors: ZHNAG Yanfang , JIN Chenxiang , FAN Changhong
Published: January 2025

This article discusses the shapes of a class of regular curves defined by hyperbolic functions. We first make a preliminary judgment using its torsion and then get more precise descriptions using its curvature and algebraic invariants. In addition, we study the shape of the generalization of the curve.
Energy Stable BDF2-SAV Scheme on Variable Grids for the Epitaxial Thin Film Growth Models
Authors: LI Juan
Published: January 2025

The second-order backward differential formula (BDF2) and the scalar auxiliary variable (SAV) approach are applied to construct the linearly energy stable numerical scheme with the variable time steps for the epitaxial thin film growth models. Under the step-ratio condition 0[see formula in PDF]4.864, the modified energy dissipation law is proven at the discrete levels with regardless of time step size. Numerical experiments are presented to demonstrate the accuracy and efficiency of the proposed numerical scheme.