bluuebunny/crossref_metadata_2025 huggingface dataset:
A new root–soil interface contact model to simulate the overturning behaviour of root system architectures
Authors: Zhu Jun , Leung Anthony Kwan , Knappett Jonathan Adam , Zhang Xingyu , Wang Yu
Published: February 2025

Correctly assessing overturning resistance of tree root systems is vital to designing sustainable and resilient urban forestry. In previous numerical modelling to investigate root anchorage behaviour, none of the root–soil contact models employed was able to capture slipping at the root–soil interface of complex root system architectures efficiently. This study proposed, derived and implemented a novel, computationally efficient, three-dimensional root–soil contact model that can capture interfacial strain-softening shearing behaviour for an arbitrary root system architecture independent from the spatial discretisation of the surrounding soil within a 3D finite-element model. Validation against existing pull-out test and centrifuge data revealed that the model well captured root pull-out and tree overturning behaviours. The validated model was subsequently used to investigate the transfer mechanisms of artificially generated root system architectures when growing with and without the presence of underground walls. Windward root segments that were more closely aligned with the lateral push provided the most contribution to resisting overturning. The presence of underground walls made the root system architecture highly asymmetric, forming a taproot complex that ‘interlocked’ the surrounding soil to provide overturning resistance. The walls also restricted the relative root–soil displacement, reducing the variability in the overturning moment.
From Programming to Prompting: Developing Computational Thinking through Large Language Model-Based Generative Artificial Intelligence
Authors: Hsu Hsiao-Ping
Published: February 2025

The advancement of large language model-based generative artificial intelligence (LLM-based GenAI) has sparked significant interest in its potential to address challenges in computational thinking (CT) education. CT, a critical problem-solving approach in the digital age, encompasses elements such as abstraction, iteration, and generalisation. However, its abstract nature often poses barriers to meaningful teaching and learning. This paper proposes a constructionist prompting framework that leverages LLM-based GenAI to foster CT development through natural language programming and prompt engineering. By engaging learners in crafting and refining prompts, the framework aligns CT elements with five prompting principles, enabling learners to apply and develop CT in contextual and organic ways. A three-phase workshop is proposed to integrate the framework into teacher education, equipping future teachers to support learners in developing CT through interactions with LLM-based GenAI. The paper concludes by exploring the framework’s theoretical, practical, and social implications, advocating for its implementation and validation.
Age-Associated B Cells in Autoimmune Diseases: Pathogenesis and Clinical Implications
Authors: Xie Guangyang , Chen Xiaojing , Gao Yixia , Yang Ming , Zhou Suqing , Lu Liwei , Wu Haijing , Lu Qianjin
Published: February 2025

As a heterogeneous B cell subset, age-associated B cells (ABCs) exhibit distinct transcription profiles, extrafollicular differentiation processes, and multiple functions in autoimmunity. TLR7 and TLR9 signals, along with IFN-γ and IL-21 stimulation, are both essential for ABC differentiation, which is also regulated by chemokine receptors including CXCR3 and CCR2 and integrins including CD11b and CD11c. Given their functions in antigen uptake and presentation, autoantibody and proinflammatory cytokine secretion, and T helper cell activation, ABCs display potential in the prognosis, diagnosis, and therapy for autoimmune diseases, including systemic lupus erythematosus, rheumatoid arthritis, Sjögren’s syndrome, multiple sclerosis, neuromyelitis optica spectrum disorders, and ankylosing spondylitis. Specifically targeting ABCs by inhibiting T-bet and CD11c and activating CD11b and ARA2 represents potential therapeutic strategies for SLE and RA. Although single-cell sequencing technologies have recently revealed the heterogeneous characteristics of ABCs, further investigations to explore and validate ABC-target therapies are still warranted.
Diverging Ethnic Hierarchies? Cultural Distance, Right-Wing Authoritarianism, and Social Distance Perceptions in the Netherlands
Authors: Soiné Hannah , Lancee Bram
Published: February 2025

The existence of hierarchies of ethnic preferences in society is well-documented. However, there is little research about how such ethnic hierarchies can be explained. Improving upon previous studies, we investigated whether individuals’ cultural distance toward ethnic outgroups and their level of right-wing authoritarianism (RWA) contribute to differences in their perception of social distance toward these groups. Our study is based on a survey in the Netherlands (N = 1249) and provides robust evidence for an ethnic hierarchy in the majority group’s perception of social distance toward 36 ethnic groups. However, this hierarchy is not universal. For more right-wing authoritarian individuals, the ethnic hierarchy is particularly steep, meaning they discriminate more between outgroups. By contrast, less right-wing authoritarian individuals differentiate little between outgroups. Furthermore, the relationship between RWA and social distance is moderated by cultural distance. We interpret this finding with symbolic threat theory, according to which greater cultural distance “activates” authoritarian attitudes, which affect the perception of social distance to varying degrees. Our results contribute to understanding the ethnic hierarchy in social distance perceptions by showing that it is determined by characteristics of the perceiving individual (RWA) and of the perceived group (cultural distance) as well as by their interaction.
Laser beam welding of copper under vacuum to extend the process limits
Authors: Schleser Markus , Liebe Philipp , Gerhards Benjamin , Gerhards Benedikt
Published: February 2025

This study explores challenges and innovations in laser beam welding of copper, focusing on infrared lasers, beam shaping and laser welding under vacuum (LaVa). Using a Trumpf TruFiber 2000 P and a Trumpf TruDisc 6000 with BrightLine technology, the research examines copper welding under reduced ambient pressure to improve process stability and seam quality. Single-mode welding shows improved stability with reduced melt ejection and minimal to no porosity. High-speed camera observations show unique behaviour for the analysed parameters, such as a smaller molten pool (2.4 to 4.0 times smaller) and capillary expansion (1.7 to 2.7 times larger) under vacuum conditions. BrightLine technology similarly shows a smaller molten pool (2.0 to 3.3 times smaller) and increased stability. While single-mode welding does not significantly increase penetration depth, multimode welding achieves greater penetration depth (up to 34%) at lower welding velocities (50 mm/s) under vacuum. Comparisons between atmospheric and vacuum welding highlight the benefits of the latter, emphasising uniformity and minimal melt ejection. Process stability correlates with weld quality, demonstrating the benefits of vacuum conditions. The combination of vacuum and established welding techniques extends process boundaries, achieving higher stability and seam quality with both types of lasers. The results indicate that vacuum conditions combined with proven welding approaches enhance copper laser welding. The potential for greater stability and improved weld quality under vacuum, particularly in single-mode welding, enables lower welding velocities down to 8.3 mm/s. Lower velocities, associated with higher energy per unit length, enable greater penetration depths.
Area Variations Under Legendrian Constraint
Authors: Rivière Tristan
Published: February 2025

In any 5-dimensional closed Sasakian manifold, we prove that any minmax operation on the area among Legendrian surfaces is achieved by a continuous conformal Legendrian map from a closed Riemann surface S into

$$N^5$$

N
5

equipped with an integer multiplicity bounded in

$$L^\infty $$

L
∞

. Moreover this map, equipped with this multiplicity, satisfies a weak version of the Hamiltonian Minimal Equation. We conjecture that any solution to this equation is a smooth branched Legendrian immersion away from isolated Schoen–Wolfson conical singularities with non-zero Maslov class.
The determinants of indigenous fruit value-added products packaging preferences among consumers in Bushbuckridge, Mpumalanga, South Africa
Authors: Mthombeni Danisile Leonah , Maluleke Mdungazi Knox
Published: February 2025

Packaging designs and materials have become increasingly important in the food sector because they assist consumers in recognising and understanding the benefits of a particular product. There seems to be scanty research on the suitable packaging materials for value-added products processed from indigenous fruits of Southern Africa. This study analysed the determinants of consumers' preferences regarding indigenous fruit product packaging (plastic containers, bottles, foam containers, and other packaging materials). The study was carried out in the Bushbuckridge Local Municipality, province of Mpumalanga, South Africa, in two malls and two retail complexes, namely: the Bushbuckridge Complex, Acornhoek Mall, Mkhuhlu Plaza, and Thulamahashe Mall. A purposive sampling technique was used to determine the sample size of each shopping mall. Furthermore, a random sampling technique was again used to sample 382 respondents within each shopping mall. A semi-structured questionnaire was used to collect data by interviewing 382 selected respondents. Statistical Package for Social Science (SPSS) version 29.0 was used to analyse data. Further analysis was carried out using descriptive statistics and a multinomial logistic model. The study findings revealed that 96.4% of respondents consumed indigenous fruits, with marula accounting for the most purchased and consumed indigenous fruit at (92.4%), when compared to other indigenous fruits. The multinomial logistic regression model analysis results revealed that market accessibility, colour of the packaging, consumers’ level of education, and shopping centres were significant determinants in the preferred choice of packaging, when comparing bottles and foam containers to plastic packaging. However, there were no significant factors impacting on consumers’ preferences for other packaging materials such as boxes, tins, papers, and cans, compared to plastic packaging. This implies that consumers had insignificant to no preference for other packaging materials used for the indigenous fruit in the study area. It is recommended that the indigenous fruit sellers and processors be informed by the findings of this study when choosing their packaging materials for indigenous fruit products.
Can ChatGPT Be Addictive? A Call to Examine the Shift from Support to Dependence in AI Conversational Large Language Models
Authors: Yankouskaya Ala , Liebherr Magnus , Ali Raian
Published: February 2025

The rapid rise of ChatGPT has introduced a transformative tool that enhances productivity, communication, and task automation across industries. However, concerns are emerging regarding the addictive potential of AI large language models. This paper explores how ChatGPT fosters dependency through key features such as personalised responses, emotional validation, and continuous engagement. By offering instant gratification and adaptive dialogue, ChatGPT may blur the line between AI and human interaction, creating pseudosocial bonds that can replace genuine human relationships. Additionally, its ability to streamline decision-making and boost productivity may lead to over-reliance, reducing users' critical thinking skills and contributing to compulsive usage patterns. These behavioural tendencies align with known features of addiction, such as increased tolerance and conflict with daily life priorities. This viewpoint paper highlights the need for further research into the psychological and social impacts of prolonged interaction with AI tools like ChatGPT.
Pragmatics in the Health Sciences
Authors: Garraffa Maria , Mazzaggio Greta
Published: February 2025

This Element aims to address a gap in the literature at the intersection of linguistics, particularly pragmatics, and health sciences, such as speech and language pathology. The first section introduces the application of pragmatics concepts in healthcare and neuroscience. Section 2 discusses the development of pragmatic abilities in childhood, focusing on pragmatic communication disorder. Section 3 reviews studies on pragmatic abilities in adolescents, adults, and clinical populations, including assessments of pragmatic skills in ageing. Section 4 broadens the scope by exploring pragmatic impairments in new populations. The final section reflects on the importance of pragmatics in healthcare practice, introducing studies on mental health and intercultural pragmatics. Each section proposes discussion points to contextualise the research within debates on health pragmatics. The Element also includes a glossary (available as online supplementary material) to assist interdisciplinary audiences in understanding clinical pragmatics terminology.
Probabilistic voting models with varying speeds of Correlation decay
Authors: Toth Gabor
Published: February 2025

We model voting behaviour in the multi-group setting of a two-tier voting system using sequences of de Finetti measures. Our model is defined by using the de Finetti representation of a probability measure (i.e. as a mixture of conditionally independent probability measures) describing voting behaviour. The de Finetti measure describes the interaction between voters and possible outside influences on them. We assume that for each population size there is a (potentially) different de Finetti measure, and as the population grows, the sequence of de Finetti measures converges weakly to the Dirac measure at the origin, representing a tendency toward weakening social cohesion as the population grows large. The resulting model covers a wide variety of behaviours, ranging from independent voting in the limit under fast convergence, a critical convergence speed with its own pattern of behaviour, to a subcritical convergence speed which yields a model in line with empirical evidence of real-world voting data, contrary to previous probabilistic models used in the study of voting. These models can be used, e.g., to study the problem of optimal voting weights in two-tier voting systems.
Potential role of report nudging on diagnosis and treatment of ventilator-associated pneumonia: a quantitative survey
Authors: Claeys Kimberly C. , Kenaa Blaine , Tripathi Ravi K. , Rayner Kristen , Newman Michelle , Leekha Surbhi
Published: February 2025

Diagnosis of ventilator-associated pneumonia (VAP) is challenging and relies heavily on respiratory culture results. The results of this survey underscore the potential for a diagnostic stewardship nudge limiting culture reports to “potential colonization or contamination” in those without clinical findings of VAP to decrease unnecessary antibiotic prescribing.
Invisible data in night-time governance: addressing policy gaps and building a digital rights framework for cities after dark
Authors: Reia Jess
Published: February 2025

As data becomes a key component of urban governance, the night-time economy is still barely visible in datasets or in policies to improve urban life. In the last 20 years, over 50 cities worldwide appointed night mayors and governance mechanisms to tackle conflicts, foster innovation, and help the night-time economy sector grow. However, the intersection of data, digital rights, and 24-hour cities still needs more studies, examples, and policies. Here, the key argument is that the increasing importance of the urban night in academia and local governments claims for much-needed responsible data practices to support and protect nightlife ecosystems. By understanding these ecosystems and addressing data invisibilities, it is possible to develop a robust framework anchored in safeguarding human rights in the digital space and create comprehensive policies to help such ecosystems thrive. Night-time governance matters for the data policy community for three reasons. First, it brings together issues covered in different disciplines by various stakeholders. We need to build bridges between sectors to avoid siloed views of urban data governance. Second, thinking about data in cities also means considering the social, economic, and cultural impact of datafication and artificial intelligence on a 24-hour cycle. Creating a digital rights framework for the night means putting into practice principles of justice, ethics, and responsibility. Third, as Night Studies is an emerging field of research, policy and advocacy, there is an opportunity to help shape how, why, and when data about the night is collected and made available to society.
The REDATAM format and its challenges for data access and information creation in public policy
Authors: Vargas Sepúlveda Mauricio , Barkai Lital
Published: February 2025

The REDATAM (retrieval of data for small areas by microcomputer) statistical package and format, developed by ECLAC, has been a critical tool for disseminating census data across Latin America since the 1990s. However, significant limitations persist, including its proprietary nature, lack of documentation, and restricted flexibility for advanced data analysis. These challenges hinder the transformation of raw census data into actionable information for policymakers, researchers, and advocacy groups. To address these issues, we developed Open REDATAM, an open-source and multiplatform tool that converts REDATAM data into widely supported CSV files and native R and Python data structures. By providing integration with R and Python, Open REDATAM empowers users to work with the tools they already know and perform data analyses without leaving their R or Python window. Our work emphasizes the need for a REDATAM official format specification to further enable informed policy debates that can improve policy processes’ implementation and feedback.
Complex roots of the cubic are associated with vector plane rotation
Authors: Nickalls R. W. D.
Published: February 2025

The all-real-roots configurations of the univariant cubic equation allow an easy visualisation of the roots as the orthogonal projection onto the real axis of the ends of three vectors of equal magnitude, radiating symmetrically in the XY plane from the origin of the reduced form [1].
The maximum modulus of a complex polynomial on the unit circle
Authors: Jameson G.J.O.
Published: February 2025

Consider a complex polynomial
$$f(z) = \sum\nolimits_{r = 0}^n {{a_r}{z^r}} $$
. Define
$$M(f) = {\rm sup}\left\{ {\left| {f(z)} \right|:\left| z \right| \le 1} \right\}.$$
Some characterisations of concurrency points in a triangle
Authors: De Prithwijit , MacHale Des
Published: February 2025

In geometry, we sometimes prove that a certain configuration Q has property P. If it turns out that Q is the only configuration that has property P, then we say that P is a characterisation of Q. For example, the centre of a circle is a point in the plane which is equidistant from every point on the circumference of the circle. In fact, the centre is the only point in the plane which is equidistant from every point on the circumference of a given circle. Thus we say that the centre of a circle is characterised by this property.
Plague history, Mongol history, and the processes of focalisation leading up to the Black Death: a response to Brack et al.
Authors: Green Monica H. , Fancy Nahyan
Published: February 2025

This essay responds to Brack et al., ‘Plague and the Mongol Conquest of Baghdad (1258)? A reevaluation of the sources’, which is a critique of our 2021 essay in this journal, ‘Plague and the Fall of Baghdad (1258)’. We argue that Brack and colleagues have misunderstood our investigation as an attempt to pinpoint the exact timing of the outbreak of plague connected with the Mongol siege of Baghdad, and so believe that an altered timeframe invalidates our suggestion that plague was involved. Taking this opportunity to revisit the state of plague historiography in western Asia, we address four issues: (1) why Mongol historiography has, until recently, avoided the question of plague’s late mediaeval resurgence within the Mongol Empire and why the ‘new genetics’ of plague now makes the question unavoidable; (2) why reconstruction of the biological processes of ‘focalisation’ is now the most urgent question in plague historiography since it constitutes what we call the prodromal stage of the Black Death pandemic; (3) how a newly informed biological perspective on disease history can allow a more sensitive reading of past observers’ reports of epidemics; and finally, (4) what a plausible scenario might look like for plague’s presence in western Asia and the eastern Mediterranean region in the late-thirteenth and early-fourteenth centuries as an emerging zoonotic disease with occasional epizootic and human outbreaks, before the more catastrophic outbreaks of the 1340s commonly referred to as ‘the Black Death’.
ON MALLE’S CONJECTURE FOR THE PRODUCT OF SYMMETRIC AND NILPOTENT GROUPS
Authors: MISHRA HRISHABH , RAY ANWESH
Published: February 2025

Let G be a finite nilpotent group and

$n\in \{3,4, 5\}$

. Consider

$S_n\times G$

as a subgroup of

$S_n\times S_{|G|}\subset S_{n|G|}$

, where G embeds into the second factor of

$S_n\times S_{|G|}$

via the regular representation. Over any number field k, we prove the strong form of Malle’s conjecture (cf. Malle (2002, Journal of Number Theory 92, 315–329)) for

$S_n\times G$

viewed as a subgroup of

$S_{n|G|}$

. Our result requires that G satisfies some mild conditions.
OPTIMAL INSDEL CODES FROM ALMOST MDS CODES
Authors: WANG JIAHUI , DING YANG
Published: February 2025

Determining the insdel distance of linear codes is a very challenging problem. Recently, Ji et al. [‘Strict half-Singleton bound, strict direct upper bound for linear insertion-deletion codes and optimal codes’, IEEE Trans. Inform. Theory69(5) (2023), 2900–2910] proposed their strict half-Singleton bound for linear codes that do not include the all-one vector. A natural question asks for linear codes with both large Hamming distance and insdel distance. Almost maximum distance separable (MDS) codes are a special kind of linear code with good Hamming error-correcting capability. We present a sufficient condition for the insdel distance of almost MDS codes to be bounded by the strict half-Singleton bound. In addition, we construct a class of two-dimensional near MDS codes that achieve the strict half-Singleton bound using twisted Reed–Solomon codes. Finally, we present a construction of optimal almost MDS insdel codes from Reed–Solomon codes for large dimensions.
DAMAGES FOR LATE PAYMENT OF INDEMNITY INSURANCE CLAIMS: A DEAD DUCK?
Authors: Eggleton Senara
Published: February 2025

Section 13A of the Insurance Act 2015 implies a term into every insurance contract that if the assured makes a claim under the contract, the insurer must pay any sums due in respect of the claim within a “reasonable time”. It provides contractual remedies, such as damages, in the event of breach. To date, a breach of section 13A has been pleaded in two cases which have resulted in judgments – Quadra Commodities S.A. v XL Insurance Co. S.E. and others [2022] EWHC 431 (Comm) and Delos Shipholding S.A. and others v Allianz Global Corporate and Specialty S.E. and others (“Win Win”) [2024] EWHC 719 (Comm) – and in each case the section 13A claim failed. Informed by the understanding of section 13A adopted in these two cases, this paper suggests that section 13A largely is symbolic. To this end, it considers three points and argues that two of these hinder the efficacy of section 13A.
Neural risk factors that predict the future onset of binge eating or compensatory weight control behaviors: A prospective 4-year fMRI study
Authors: Stice Eric , Yokum Sonja , Gau Jeff , Shaw Heather
Published: February 2025

Background

We conducted a prospective study to advance knowledge of biological factors that predict the future onset of binge eating and compensatory weight control behaviors because few biological risk factors for eating pathology have been identified.

Methods

Adolescent girls free of binge eating or compensatory behaviors (N = 88; Mage = 14.5; [SD = 0.9]) completed functional magnetic resonance imaging tasks assessing individual differences in neural responsivity hypothesized to increase risk for onset of binge eating and compensatory behaviors, along with additional self-report measures, and were assessed over a 4-year follow-up.

Results

Elevated responsivity of regions implicated in attention and valuation (dorsal anterior cingulate cortex; ventromedial prefrontal cortex) to thin models and lower responsivity of a reward valuation region (caudate) to anticipated milkshake tastes (which correlated with feeling fat) predicted the future onset of binge eating or compensatory behaviors over 4-year follow-up. Parental history of binge eating and compensatory behaviors, emotionality, weight/shape overvaluation, feeling fat, and elevated BMI also predicted the future onset of binge eating or compensatory behaviors.

Conclusions

The evidence that elevated attentional bias for, and valuation of the thin ideal, in combination with lower valuation of high-calorie foods, predicted the future onset of eating-disordered behaviors are novel findings. The evidence that weight/shape overvaluation, feeling fat, elevated body mass, emotionality, and parental history of eating pathology predicted the future onset of eating-disordered behaviors extend past findings.
Altered corticostriatal connectivity in long-COVID patients is associated with cognitive impairment
Authors: Troll Marie , Li Meng , Chand Tara , Machnik Marlene , Rocktäschel Tonia , Toepffer Antonia , Ballez Johanna , Finke Kathrin , Güllmar Daniel , Reichenbach Jürgen R. , Walter Martin , Besteher Bianca
Published: February 2025

Background

The COVID-19 pandemic has had a significant impact on the health of millions of people worldwide, and many manifest new or persistent symptoms long after the initial onset of the infection. One of the leading symptoms of long-COVID is cognitive impairment, which includes memory loss, lack of concentration, and brain fog. Understanding the nature and underlying mechanisms of cognitive impairment in long-COVID is important for developing preventive and therapeutic interventions.

Methods

Our present study investigated functional connectivity (FC) changes in patients with long-COVID and their associations with cognitive impairment. Resting-state functional MRI data from 60 long-COVID patients and 52 age- and sex-matched healthy controls were analyzed using seed-based functional connectivity analysis.

Results

We found increased FC between the right caudate nucleus and both the left and right precentral gyri in long-COVID patients compared with healthy controls. In addition, elevated FC was observed between the right anterior globus pallidus and posterior cingulate cortex as well as the right temporal pole in long-COVID patients. Importantly, the magnitude of FC between the caudate and the left precentral gyrus showed a significant negative correlation with Montreal Cognitive Assessment (MoCA) scores and a negative correlation with Trail Making Test B performance in the patient group.

Conclusion

Patients with long-COVID present enhanced FC between the caudate and the left precentral gyrus. Furthermore, those FC alterations are related to the severity of cognitive impairment, particularly in the domain of executive functions.
Protein Consumption and Personalized Nutrition in CKD: A Comprehensive Review
Authors: Alobaidi Sami
Published: February 2025

Chronic Kidney Disease (CKD) poses a global health challenge, with dietary protein intake being a key factor in disease management. This review synthesizes evidence on the impact of different protein intake strategies, including low-protein diet (LPD), very low-protein diet (VLPD), high-protein diet (HPD), and plant-based diet (PBD), on CKD progression and patient outcomes. The review explores personalised nutrition strategies and identifies gaps in the literature. A systematic search of PubMed, Cochrane Library, Web of Science, and Scopus was conducted, covering studies published from 1982 to 2024, including randomized controlled trials (RCTs), observational studies, and meta-analyses involving adult CKD patients. The findings suggest that LPDs and VLPDs may slow CKD progression, particularly when supplemented with ketoanalogues, but adherence and long-term benefits remain uncertain. PBDs are associated with reduced renal burden and improved metabolic health, although achieving adequate protein intake from plant sources requires careful planning. HPDs, particularly those rich in animal protein, may exacerbate CKD progression, although recent research indicates that higher protein intake may benefit specific populations, such as older adults with mild to moderate CKD. In conclusion, managing protein intake in CKD is complex and necessitates a personalised approach. While LPD and PBD offer potential benefits, their long-term success is contingent upon patient adherence, individualized dietary management, and further research into their sustained effects. Future research should focus on long-term RCTs and the development of personalised nutrition strategies incorporating emerging technologies and multidisciplinary care to optimise CKD management.
Machine Learning‐Driven Skillful Decadal Predictions of German Bight Storm Surges
Authors: Krieger Daniel , Weisse Ralf , Baehr Johanna , Borchert Leonard F.
Published: February 2025

The German Bight coastline is regularly affected by storm surges driven by extratropical cyclones. Decadal‐scale predictions of local surges would foster coastal protection and decision making in affected areas. We examine the prediction skill of the Max‐Planck‐Institute Earth System Model (MPI‐ESM) decadal prediction system for three different storm surge metrics at Cuxhaven (Germany), Esbjerg (Denmark), and Delfzijl (The Netherlands). To avoid dynamical downscaling from the coarse model output to local surge heights, we use machine learning and train a neural network on observed surge heights and reanalyzed fields of mean sea‐level pressure (MSLP). We apply this network to MSLP output of our prediction system to generate decadal predictions of surge heights. The prediction system falls short of generating skillful predictions for high water event durations and individual lead years in general, but windows for more skillful predictions arise for deterministic predictions at longer multi‐year lead times.
Contrasting CO2 Dynamics in Seagrass Meadows Between Organic Carbon (OC)‐Rich Reef and OC‐Poor Terrestrial Sediments: Implications for Enhanced Alkalinity Production
Authors: Chou Wen‐Chen , Fan Lan‐Feng , Natividad Mariche B. , Chen Jian‐Jhih , Tang Zih‐Wei , Chen Huei‐Fen , Chen Ping‐Chun , Kong En‐Cheng , Shih Yung‐Yen , Huang Wei‐Jen , Hung Chin‐Chang
Published: February 2025

Seagrass meadows are increasingly recognized across the globe as a natural climate solution due to their significant potential in alkalinity‐driven carbon dioxide (CO2) removal, which possibly represents an overlooked component of ocean carbon removal. This study comprehensively investigated the carbonate chemistry, sediment carbon content, mineral composition, and benthic alkalinity fluxes in two distinct sites with tropical seagrass meadows: one situated in organic carbon (OC)‐rich reef sediments and the other in OC‐poor terrestrial sediments. Results showed nearly two orders of magnitude higher benthic alkalinity fluxes in the OC‐rich reefs than in OC‐poor sediments (72.8 ± 64.4 vs. 0.53 ± 0.99 mmol m−2 d−1). This can further substantially increase alkalinity levels and reduce the partial pressure of CO2 in the overlying seawater, thereby enhancing the capacity for CO2 uptake. We propose that seagrass meadows on high‐OC reef sediments, the hotspots for alkalinity generation, could amplify the climate change mitigation potential of seagrass restoration initiatives.
Cd(ii) complexes of 9-anthracenyl-4′-benzoate and 4-pyridyl vinyl arenes: effect of steric hindrance on the solid-state photoreactivity
Authors: Baig K. Mohamed Yusuf , Kole Goutam Kumar
Published: February 2025

The effect of steric hindrance on the crystal packing and solid-state photoreactivity of four Cd(ii) complexes of 9-anthracenyl-4′-benzoate and 4-pyridyl-vinyl-arene ligands have been demonstrated.
Exploring the potential of metal–organic framework based composites as key players in bisphenol detection
Authors: Atkare Sayali , Jagtap Shweta , Late Dattatray J.
Published: February 2025

This review presents an insightful overview of the detection of bisphenol and its analogues using metal–organic framework composites via different detection techniques.
An innovative Ag/Cu-doped polypyrrole hybrid nanocomposite gas sensor for superior ammonia detection at room temperature
Authors: Verma Arunima , Kumar Tanuj , Singhal Rahul
Published: February 2025

Hybrid nanocomposites combining organic and inorganic materials offer enhanced responses to reducing and oxidizing gases.
Unveiling the synergistic interface effects of Ag-deposited Fe2O3/biochar catalysts to enhance wastewater degradation
Authors: Gu Jialin , Li Xinshang , Ma Yanping , Yang Tianyi , Zhang Rui , Zhou Wenquan , Wang He , Jiang Jiangang
Published: February 2025

This study uses biochar from rape pollen as a template to synthesize spiky Fe2O3, followed by Ag nanoparticle deposition. The catalyst shows high dye selectivity, E. coli antibacterial activity, and effective aquaculture wastewater treatment.
Recent advances in tailored chitosan-based hydrogels for bone regeneration and repair
Authors: Feng Peipei , He Chaonan , Li Guanrong , Li Jin , Ke Chunhai , Ma Jingyun
Published: February 2025

This paper summarizes the preparation processes of tailored chitosan-based hydrogels, along with their specific applications in bone regeneration, aiming to inspire innovative designs for chitosan-based hydrogels and foster expanded applications.
Sustainable antimicrobial formulations: vitamin-E based emulsions stabilized by plant-derived saponin from Acacia concinna
Authors: Begum Wasefa , Laha Rajlakshmi , Rahaman Sk Mehebub , Mondal Monohar Hossain , Dam Somasri , Saha Bidyut , Mandal Ujjwal
Published: February 2025

A stable oil-in-water emulsion was developed using vitamin-E and saponin from Acacia concinna. The emulsion exhibited significant antifungal activity against A. flavus and C. albicans, making it a promising natural and effective topical formulation.
Exploring the frontiers of emerging sensing of silver nanoprisms: recent progress and challenges
Authors: Kholafazad Kordasht Houman , Bahavarnia Parinaz , Bahavarnia Farnaz , Hasanzadeh Mohammad , Shadjou Nasrin
Published: February 2025

In recent years, the development and use of nanomaterials have transformed numerous aspects of biomedical science.
Synthesis, characterization, and biomedical applications (antibacterial, antibiofilm, anticancer and effects on hospital-acquired pneumonia infection) of copper titanium oxide nanostructures
Authors: Poudineh Mohsen , Valian Movlud , Jassim Amar Yasser , Ghorbani Zahra , Khaledi Azad , Salavati-Niasari Masoud
Published: February 2025

Investigating the antibacterial effects of Cu2Ti2O5 on Pseudomonas aeruginosa and Klebsiella pneumoniae isolated from respiratory infections using the broth microdilution MIC method and comparing it with standard isolates.
Boosting the efficiency and stability of two-step perovskite solar cells by a hydroxylamine-driven additive strategy
Authors: Chen Ming , Chen Yubo , Wang Nan , Zhu Xuejie , Yang Shaoan , Bai Dongliang , Yu Fengyang , Yang Dong , Liu Shengzhong(Frank)
Published: February 2025

In this study, perovskite solar cells were prepared using a two-step spin-coating solution method. By adding Cbz-hydroxylamine to the organic salt reduces PbI2 residue, enhances crystallization, and improves efficiency by defect suppression.
Silica biomineralization in plants alters the structure of lignin
Authors: Palakurthy Srinath , Elbaum Michael , Elbaum Rivka
Published: February 2025

Biomineralization of silica is a major process in plants, which may contribute 3-10% of tissue dry weight. For reasons that remain unclear, plants containing silica are less sensitive to abiotic...
Self-assembled monolayer boosts the air-stability and electrochemical reversibility of O3-type layered oxides for sodium-ion batteries
Authors: He Yan , Zhang Lei , Liu Hongguang , Yan Zichao , Zhu Zhiqiang
Published: February 2025

This study develops a self-assembled, hydrophobic, and compact C32H67O4P layer on O3-NaNi0.33Fe0.33Mn0.33O2 cathode, effectively shielding the electrode from air degradation and metal dissolution, thereby enhancing sodium-ion battery performance.
Dynamic Evaluation‐Based Real‐Time Coordinated Control Method for Multi‐Stack Fuel Cell System Considering Lifetime Consistency
Authors: Han Ying , Meng Weifeng , Li Luoyi , Deng Huiwen , Zhan Xiangwen , Chen Weirong
Published: February 2025

With the global energy shortage and excessive carbon emissions, hydrogen energy has received significant attention as a key component of a carbon‐neutral future, with fuel cells serving as a key component for hydrogen‐to‐power conversion. In high‐powered applications like rail transportation and buildings, the multi‐stack fuel cell system (MFCS) offers superior performance compared to a single‐stack fuel cells system, providing advantages such as higher efficiency, stronger robustness, and longer lifetime. However, the efficiency, lifetime, and economy of MFCS are limited by the power distribution and performance of single‐stack fuel cell, and the strong coupling between the performance of single‐stack fuel cells and their actual power and voltage in real‐time operation makes the energy management method of MFCS extremely complicated. The traditional strategies struggle to balance the various indexes in the MFCS and are limited in optimising individual indexes. To tackle this issue, this paper proposes a dynamic evaluation‐based real‐time coordinated control method for MFCS considering lifetime consistency. First, to comprehensively consider various indexes of the MFCS, a dynamic evaluation matrix (DEM) of the MFCS is established. The DEM consists of two essential components: the first is the dynamic performance evaluation matrix (DPEM), which thoroughly considers the impact of the performance variations in each single‐stack fuel cell on the MFCS; and the other is the evaluation matrix pertaining to the efficiency, lifetime, and economy of the MFCS, which builds upon the DPEM and fully balances the mutual influences among the indexes. Then the objective function is established according to the DEM, and the GSSA algorithm is used for real‐time optimisation. To demonstrate its effectiveness and advantages, the proposed method is applied in a hardware‐in‐the‐loop (HIL) simulation system based on RT‐LAB. The findings demonstrate that the proposed method facilitates comprehensiveoptimisation of the MFCS across efficiency, lifespan, and economic considerations. Furthermore, it realises the uniform lifetimes of each PEMFC and enhances the overall utilisation of the MFCS.
Generating peak‐aware pseudo‐measurements for low‐voltage feeders using metadata of distribution system operators
Authors: Treutlein Manuel , Schmidt Marc , Hahn Roman , Hertel Matthias , Heidrich Benedikt , Mikut Ralf , Hagenmeyer Veit
Published: February 2025

Distribution system operators (DSOs) face challenges such as restructuring distribution grids for climate neutrality and managing grid consumption and generation. Measurements within the grid are crucial for DSOs, yet many low‐voltage (LV) grids lack measurement devices. To address this, an approach is proposed to estimate pseudo‐measurements for non‐measured LV feeders using regression models. The models are based on feeder metadata, which includes the number of grid connection points, installed power of equipment, and billing data in the downstream LV grid. The authors also incorporate weather, calendar, and timestamp data as model features and use the existing measurements as the model target. For evaluation, a dataset of 2323 LV feeders is used and peak metrics for magnitude, timing, and shape of consumption and feed‐in are introduced, inspired by the BigDEAL challenge. The authors employ XGBoost, a multilayer perceptron (MLP), and a linear regression (LR) model, finding that XGBoost and MLP outperform LR. The results demonstrate that this approach effectively adapts to varying conditions and generates realistic load curves from feeder metadata. Additionally, the authors elaborate on feeders where pseudo‐measurements exhibit deficiencies. This method could be extended to other grid levels such as substations and contribute to research in load modelling, state estimation, and LV load forecasting.
Scaleable Multichannel Square‐Wave Sequence Generator Based on the RP2040 Microcontroller
Authors: Weber Martin , Hyvönen Jere , Nikolaev Dmitry , Hæggström Edward , Salmi Ari
Published: February 2025

Multichannel signal generators are used in many fields of science. For example, they are used to drive ultrasonic phased arrays and usually employ FPGAs or DSPs. We present a design based on the synchronization of multiple low‐cost RP2040 microcontrollers to generate digital square wave signals (PWM) with a granularity of . Due to its modular design, the device is directly scalable to an arbitrary number of output signals. The CPU clocks are synchronized, and PIO modules are used to generate synchronized interrupts across the system. This ensures a stable phase relation across all output signals with a remaining jitter of . We demonstrate the generation of chirp signals by utilizing the DMA for hardware‐level data transfer. This signal generator can be utilized, for example, to control ultrasonic phased arrays and to generate arbitrary test patterns for digital circuits.
Mathematical and software support for the automated knowledge control subsystem of process plant operators on a training complex
Authors: Polevshchikov Ivan , Mokrushin Sergey , Nedvetsky Vladimir , Dmitruk Maksim
Published: February 2025

This study focuses on the development of automated knowledge control systems for process plant operators based on computer training complexes. Functional requirements for the complex subsystem for automated knowledge control of production process operators have been developed. The subsystem allows instructors not only to manually create sets of test tasks but also to configure knowledge about the subject area of operators' professional activities for automatic generation of a required number of test tasks of a specific type and complexity level. A method for modeling the subject area has been developed to conduct automated testing of knowledge on safety rules when working with equipment and the sequence of actions during the operation of production equipment. An algorithm has been developed to evaluate the result of performing a test task on establishing the sequence of operator actions when working on a process plant. This algorithm allows for a detailed comparison of the reference result of the task, automatically generated based on the subject area settings, with the trainee's result. A prototype of the software for the computer complex automated knowledge control subsystem has been developed as a web application based on the described mathematical models and algorithms.
Calculation of reliability of radio-electronic systems using the Monte Carlo method
Authors: Legkiy Timofey
Published: February 2025

In various fields of knowledge, modeling methods are used to study objects and systems. The use of modeling is especially effective in cases where direct study of the object or system itself is either impossible or leads to a large expenditure of resources. For example, to assess the reliability of objects located in low-Earth orbit. The most popular method for predicting reliability is the Monte Carlo method. The Monte Carlo method is widely used in various fields of science and technology to analyze the reliability of technical systems. It has also found application in reliability calculations and forecasting of radio engineering systems. The article discusses the Monte Carlo method in relation to the calculation of the reliability of electronic means. The algorithm of the solution is given, an example of calculation is considered.
On the modifications of one method for rendering global illumination using a generative adversarial neural network
Authors: Rubinov Kirill , Frolov Alexander
Published: February 2025

Three variants for modifying one method for rendering 3D scenes using a generative adversarial network are proposed to generate realistic lighting in screen space. Experiments using software implementations of neural networks have shown that adding 25% resolution ray traced rendering to the generator input improves image quality when assessed by both the SSIM structural similarity index and the peak signalto- noise ratio PSNR. Adding noise to the discriminator layers improves the quality of network performance in both respects, but not significantly. Passing the ray traced rendering to the hidden convolutional layers of the generator instead of the input leads to a decrease in quality in both metrics compared to other modifications, but avoids unwanted effects on the edges of objects.
Algorithms for big data mining of hub patent transactions based on decision trees
Authors: Zhukov Aleksandr , Pronichkin Sergey , Mihaylov Yuri , Kartsan Igor
Published: February 2025

Dysfunctions of the patent supply and demand market have a negative impact on the sustainability of the national innovation system, which stimulates the growth of prices for knowledge-intensive products. It is necessary to establish a relationship between fiscal decisions regarding patent transactions and the prospects for the development of commercialization of the results of intellectual activity. One of the most promising methods for improving the accuracy of system analysis of big and semi-structured patent transaction data is the use of decision trees. Existing methods based on the error backpropagation method are quite slow, and their accelerated versions lose in training accuracy. To effectively solve the problem of forecasting the cost of hub patent transactions, parametric algorithms have been developed based on response bias and with the additional use of predicative structures of the model of successive geometric transformations. The optimal number of decision tree predicates has been established taking into account computational efforts and the accuracy of forecasting the cost of hub patent transactions. Based on evolutionary computing, the optimal values of the parameters of algorithms for big data mining of hub patent transactions have been established.
The impact of laser radiation frequency on the formation of the main characteristics of ions in a mono-element laser plasma
Authors: Japakov Azamat I. , Bedilov Ravshan M. , Kamalova Jamilya O. , Davletov Ikram Y. , Matnazarov Anvar R.
Published: February 2025

The purpose of these studies is to study the patterns of development of the characteristics of multiply charged ions in the plasma generated during the interaction of laser radiation with a target operating in the frequency mode. The characteristics of multiply charged ions in monoelement aluminum plasma were studied using laser time of flight mass spectrometers. By changing the laser radiation power in the range from 0.1 to 100 GW/sm2 and different pulse repetition frequencies (1, 3, 5, 10, and 12 Hz), spectra of charged ions of the plasma formed in each case were obtained.