bluuebunny/crossref_metadata_2025 huggingface dataset:
Cultured endothelial cells present organ-specific RTK distributions: advancing receptor measurement and data standardization via quantitative flow cytometry
Authors: Liu Xinming , Fang Yingye , Imoukhuede Princess I
Published: February 2025

Purpose Receptor tyrosine kinase (RTK) concentrations on the plasma membrane correlate with angiogenic functions in vitro and in rodent models. The intracellular RTK pool also regulates plasma membrane receptor availability and signaling pathways. Organs have specialized angiogenic functions essential to their distinct roles, supporting the hypothesis that plasma membrane and intracellular RTK concentrations vary across endothelial cells (ECs) from different organs. Methods Using quantitative flow cytometry on human ECs derived from dermis, umbilical vein, kidney, liver, and brain, we measured and statistically analyzed the concentrations of selected RTKs within ECs and on their plasma membranes. Results VEGFR1 exhibited the lowest concentrations on the plasma membrane (300 - 900 VEGFR1/cell) among VEGFRs. HDMECs (dermis) showed the lowest VEGFR1 level among the examined EC types. Whole-cell VEGFR1 concentrations were 2500 - 7500 VEGFR1/cell, with 12 - 26% located on the plasma membrane. The proportion of VEGFR2 located on the plasma membrane was higher at > 30%, except in HGMECs (kidney) where it was 24%. Plasma membrane VEGFR2 was significantly lower in HDMECs and HGMECs compared with HBMECs (brain), whereas whole-cell VEGFR2 levels were consistently in the range of 14,100 - 22,500 molecules/cell. VEGFR3 was the least localized to the plasma membrane, from 2% in HGMECs to 14% in HDMECs at the highest level of 4400 VEGFR3/cell. Whole-cell VEGFR3 concentrations ranged from 32,400 in HDMECs to 62,000 VEGFR3/cell in HLiSMECs (liver), with no significant differences among EC types. NRP1 was most abundant on the plasma membrane of HUVECs (umbilical vein) at 39,700 NRP1/cell; other ECs displayed 26,000 - 29,900 NRP1/cell, approximately 5-fold higher than the numbers of VEGFRs. Across EC types, Axl was present on the plasma membrane at levels (6900 - 12,200 Axl/cell) similar to those of VEGFR2. Conclusions We quantified and statistically analyzed plasma membrane and whole-cell expression of angiogenic RTKs across cultured human ECs from five different organs. Our findings suggest that RTK protein distribution might not fully reflect the differential angiogenic capacities in cultured ECs. In vitro monoculture conditions might reduce EC organ-specific features essential for refining vascular models.
Extracellular matrix proteolysis maintains synapse plasticity during brain development
Authors: Nakajo Haruna , Cao Ran , Mula Supriya A. , McKetney Justin , Silva Nicholas J. , Shah Muskaan , Rose Indigo V.L. , Kampmann Martin , Swaney Danielle L. , Kirst Christoph , Molofsky Anna V.
Published: February 2025

Maintaining a dynamic neuronal synapse pool is critical to brain development. The extracellular matrix (ECM) regulates synaptic plasticity via mechanisms that are still being defined and are studied predominantly in adulthood. Using live imaging of excitatory synapses in zebrafish hindbrain we observed a bimodal distribution of short-lived (dynamic) and longer-lived (stable) synapses. Disruption of ECM via digestion or brevican deletion destabilized dynamic but not stable synapses and led to decreased synapse density. Conversely, loss of matrix metalloproteinase 14 (MMP14) led to accumulation of brevican and increased the stable synapse pool, resulting in increased synapse density. Microglial MMP14 was essential to these effects in both fish and human iPSC-derived cultures. Both MMP14 and brevican were required for experience-dependent synapse plasticity in a motor learning assay. These data, complemented by mathematical modeling, define an essential role of ECM remodeling in maintaining a dynamic subset of synapses during brain development.
Nuclear Astrophysics in the Storage Ring: Background Suppressed Simultaneous Measurement of
(p,γ)
and
(p,n)
Reactions
Authors: Varga L. , Glorius J. , Aliotta M. , Blaum K. , Bott L. , Brandau C. , Brückner B. , Bruno C. G. , Chen X. , Chen R. , Dababneh S. , Davinson T. , Dmytriiev D. , Dellmann S. F. , Dillmann I. , Erbacher P. , Fiebiger S. , Forstner O. , Gaßner T. , Göbel K. , Goriely S. , Griffin C. J. , Grisenti R. E. , Groothuis M. , Gumberidze A. , Gyürky G. , Heil M. , Hensch R. , Hess R. , Hillenbrand P.-M. , Hillmann P. , Hinrichs O. , Joseph R. , Jurado B. , Kausch T. , Khasawneh K. , Khodaparast A. , Kisselbach T. , Klapper N. , Kozhuharov C. , Kurtulgil D. , Lane G. J. , Langer C. , Leckenby G. , Lederer-Woods C. , Lestinsky M. , Litvinov Yu. A. , Litvinov S. , Löher B. , Lorenz E. , Lorentz B. , Marini P. , Marsh J. , Menz E. , Morgenroth T. , Nguyen T. T. , Nolden F. , Petridis N. , Popp U. , Psaltis A. , Reed M. , Reifarth R. , Sanjari M. S. , Savran D. , Sguazzin M. , Simon H. , Sidhu R. S. , Slavkovská Z. , Spillmann U. , Steck M. , Stöhlker T. , Stumm J. , Surzhykov A. , Swartz J. , Szücs T. , Taremi Zadeh A. , Thomas B. , Torilov S. Yu. , Törnqvist H. , Träger M. , Trageser C. , Trotsenko S. , Vescovi D. , Volknandt M. , Weick H. , Weigand M. , Wolf C. , Woods P. J. , Xing Y. M. , Yamaguchi T.
Published: February 2025

We report the application of the new elimination of Rutherford elastic scattering technique for the measurement of proton-induced reaction cross sections utilizing stored ions decelerated to astrophysical energies. This approach results in a background reduction factor of about 1 order of magnitude, enabling the first measurement of a (p, n) cross section in a storage ring. Here, the reaction channels Xe124(p,n) and Xe124(p,γ) have been studied just above the neutron threshold energy. The new data provide valuable constraints for Hauser-Feshbach theory and extrapolation of the (p,γ) cross section to lower energies. Most importantly, for nuclei of limited availability, the method represents a powerful improvement to efficiently study proton-induced reactions at energies within or close to the astrophysical Gamow window, bringing many reaction measurements within reach that were previously inaccessible in the laboratory.

Published by the American Physical Society
2025
If you cannot see it, is it still there?
Authors: Leitner Lukas , Hudspeth Jesse , Werten Sebastiaan , Rupp Bernhard
Published: February 2025

Protein crystallographers rely on electron density to build atomic models of molecular structures, yet flexible regions often remain unseen in electron density and are omitted. We suggest that ensemble refinement can be used to visualize and analyse the conformational landscape of such `invisible' protein segments, which is particularly useful in cases where molecular flexibility plays a functional role. Using ensemble refinement on multiple crystal forms of the fungal methyltransferase PsiM as an example, we illustrate the dynamic nature of a key substrate recognition loop, demonstrating its potential role in substrate binding and release. Ensemble refinement provides a persuasive visualization of biologically relevant flexible regions and can be a powerful tool for exploring molecular plasticity and aiding the modelling of dynamic protein components.
2,2′-[(4-Butoxyphenyl)methylene]bis(3-hydroxy-5,5-dimethylcyclohex-2-en-1-one)
Authors: Suresh Babu N. , Anbu Chudar Azhagan S. , Loganathan B. , Sughanya V. , Ayyappan J.
Published: February 2025

In the title compound, C27H36O5, the dihedral angles between the planes of the benzene ring and the cyclohexenone rings are 60.87 (10) and 65.04 (10)°, while the dihedral angle between the mean planes of the two cyclohexenone rings is 39.33 (10)°. Each cyclohexenone ring has a carbon atom bonded to two methyl groups, which acts as the flap atom, resulting in an envelope conformation. The opposite orientation of the hydroxy and carbonyl oxygen atoms allows for the formation of two intramolecular O—H...O hydrogen bonds and C—H...π (ring) interactions also help to establish the molecular conformation.
Championing green sustainability in manufacturing of a developing economy: implications for sustainable performance through eco-regulatory compliance
Authors: Opoku Richard Kofi
Published: February 2025

Purpose

Given the unprecedented rise in environmental problems today, global manufacturing businesses are strategically diverting their attention toward green sustainability. Green sustainability emphasises environmental management throughout manufacturing processes to address firms’ sustainable performance. This study investigates whether green sustainability and eco-regulatory compliance, as strategic management approaches, influence manufacturers’ economic, social and environmental performances.

Design/methodology/approach

Using structured questionnaires, this quantitative-based explanatory research obtained a usable dataset of 385 from manufacturing firms in Ghana, a developing country. Data analysis was conducted using structural equation modelling.

Findings

The study found green sustainability and eco-regulatory compliance to influence manufacturers’ sustainable performance positively. Also, eco-regulatory compliance partially mediated the green sustainability-sustainable performance nexus in a developing economy, particularly Ghana.

Research limitations/implications

The study’s conceptual model is limited to manufacturing industries in developing economies, particularly Ghana. It was also limited to the natural resource-based view, quantitative approach and cross-sectional design.

Practical implications

The study found green sustainability and eco-regulatory compliance to influence manufacturers’ sustainable performance positively. Also, eco-regulatory compliance partially mediated the green sustainability-sustainable performance nexus in a developing economy, particularly Ghana.

Social implications

The study raises awareness among industry players, consumers and the public about the significance of green sustainability practices in manufacturing. This will foster support and heavy investments in eco-friendly manufacturing businesses. Also, the study promotes local initiatives that advocate for sustainability, contributing to higher community involvement in environmentally conscious efforts. It contributes to waste and pollution (emission and water) minimisation while improving water, land and air quality by emphasising green sustainability and eco-regulatory compliance throughout manufacturing operations.

Originality/value

The study contributes significantly to the growing debate on sustainability in manufacturing by unearthing how green sustainability and eco-regulatory compliance enhance firms’ sustainable performance. It also demonstrates the intervening role of eco-regulatory compliance in the green sustainability–sustainable performance interplay.
Empirical investigation of barriers and benefits of smart farming
Authors: Narayanamurthy Gopalakrishnan , Shiva Jayanth R. Sai , Tortorella Guilherme , Fogliatto Flávio
Published: February 2025

Purpose

Smart farming (SF) holds immense potential in making farming viable and improving farmers' livelihoods. However, its adoption is still in the early stages, and the resulting impacts are underexplored. This study investigates the information systems/policy and implementation barriers to the adoption of SF and its implications for various socioeconomic aspects.

Design/methodology/approach

This survey research used a structured questionnaire to collect data on farm details, farmer characteristics and usage of SF technologies from a sample of 197 farmers based in the State of Karnataka, India. Exploratory factor analysis with principal component extraction is used to validate the proposed questionnaire constructs. Results are analyzed using one-way and two-way ANOVAs and interaction plots.

Findings

Our study throws light on the benefits and barriers of SF technologies. Advanced SF technologies displayed a significant positive effect on socioeconomic variables compared to startup SF technologies, which displayed no significant effect. Overcoming information systems/policy barriers for adopting startup and advanced SF technologies displayed significant positive effects on farmers' health and net income, whereas overcoming implementation barriers for adopting advanced SF technologies led to improvement in the farmers' gross income.

Originality/value

Although the technical feasibility of SF has been explored in the literature, its adoption barriers and socioeconomic impacts have been underexplored. To the best of our knowledge, the interaction between different types of barriers and the level of SF adoption has not yet been investigated in the literature. Our study addresses those research gaps using data from a previously underexplored context, viz. developing nations.
Effect of laser energy density on the fretting wear behavior of TC4 alloys prepared by selective laser melting (SLM)
Authors: Li Wenlong , Zhang Po , Yue Zhiwen , Duan Wei , Cai Yun , Cai Zhaobing , Gu Le
Published: February 2025

Purpose

This paper aims to investigate the effect of laser energy density on the fretting wear properties of TC4 alloys prepared by selective laser melting to enhance their service life.

Design/methodology/approach

The friction test used a ball-to-plane contact structure and simulated the actual working conditions by applying a linear reciprocating motion. In the experiments, the authors prepared TC4 alloys using different laser energy densities and performed fretting wear tests with D = 100 µm on a friction machine, as well as comparative analyses with conventional cast TC4 materials. 3D optical microscope, scanning electron microscopy and energy spectrum x-ray spectrometer were used to analyze the surface morphology and elemental content of the samples.

Findings

The results indicate that the friction coefficient and wear volume of selective laser melting (SLM)-TC4 are lower than those of cast TC4, demonstrating superior wear resistance. As the laser energy density increases, the grain size of the SLM-TC4 samples gradually coarsens, leading to an initial improvement followed by a decline in friction coefficient and wear resistance. Among the samples, ET3 (42 J/mm³) exhibits the lowest friction coefficient and wear volume, with the friction coefficient ranging from 0.67 to 0.7 and the wear volume being only 9.92% of that of cast TC4.

Originality/value

The main contribution of this work is to provide a new reference for improving the wear resistance of TC4 prepared by selective laser melting. By studying the effect of different laser energy densities on the wear resistance of TC4, it provides a theoretical basis for the preparation of SLM-TC4 alloys for industrial applications.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2024-0414/
Maslahah value optimization in exploring Muslim consumption behavior: a study of impulse buying on e­wallet users in East Java, Indonesia
Authors: Yudha Ana Toni Roby Candra , Atiya Nikmatul , Faidah Amelia Riski , Febriyanti Novi , Masrufah Nur
Published: February 2025

Purpose

This study aims to analyze the value of maslahah in impulse buying behavior by investigating the influence of free shipping, cashback and religiosity of Muslim e-wallet users in East Java, Indonesia. Impulse buying, which is prevalent post-COVID-19, accounts for 60%–65% of total shopping, in contrast to conventional shopping, which is only 35%–40%.

Design/methodology/approach

This study used a survey study aimed at Millennials and Generation Z. There were 236 respondents, but only 207 were valid and complete. In addition, this study used structural equation modeling-partial least square (SEM-PLS) to validate the hypothesis and evaluate the model. Additional tests were also carried out using multigroup analysis (MGA) to obtain results based on gender perspective.

Findings

Free shipping and cashback were shown to have a significant positive impact on impulse buying behavior. Contrary to the initial hypothesis, religiosity showed a significant positive influence on impulse buying. Therefore, consumption behavior should be evaluated using the concept of maslahah, which prioritizes fulfilling the most important needs. Responsible consumption for a Muslim should align with Islamic principles, which teach that wealth should be used for good things. While ideally, maslahah comes first, in a 5.0 society influenced by discounts and added incentives, impulse buying has become a normalized phenomenon. Regarding gender, differences show that men prioritize practical incentives, whereas women focus more on rational considerations and opportunities.

Research limitations/implications

This study uses a sample of several e-wallet brands with the most users in Indonesia; the respondents come from Millennials and Generation Z who are on the island of Java, Indonesia. Thus, it needs to be considered for generalization purposes by adding other brands and respondents from areas outside Java.

Practical implications

The results of this study include implications regarding strengthening the value of religiosity and maslahat in impulse buying of goods.

Social implications

In line with the results and analysis of this research, which provides a maslahah perspective in the analysis and a gender perspective in the methodology. Thus, this can be recognized as a contribution of thought related to social implications.

Originality/value

This study explores impulse buying based on the gender of respondents, which is not often found in previous research.
The environment effect and health benefit evaluation based on machine learning and prediction
Authors: Zhu Suling , Li Min , Shi Yujie , Weng Qinnan , Liu Bowen , Zhang Zhenhua
Published: February 2025

Purpose

To maximize health synergistic benefits and provide a scientific foundation for enhancing air pollution control policies, this research proposed a causal inference framework with a decomposition ensemble prediction model for comprehensive policy assessment.

Design/methodology/approach

We introduced the CD-OASVR-Ensemble-CC method, a policy assessment approach that combined machine learning-based decomposition ensemble prediction (CD-OASVR-Ensemble) with counterfactual contrast (CC) analysis. The CD-OASVR-Ensemble model incorporated support vector regression (SVR) optimized through swarm intelligent optimization algorithms (OA), complete ensemble empirical model decomposition of adaptive noise (CD) and a linear ensemble model (Ensemble). This approach was applied to analyze patterns in historical PM2.5 data and predict the future trend. The predicted PM2.5 served as a counterfactual trend, enabling an evaluation of the policy’s environmental and health effects.

Findings

Analysis of prediction errors confirmed the proposed CD-OASVR-Ensemble model’s accuracy and robustness in predicting PM2.5 levels. The findings indicated that the implementation of “Regulation 2019” led to a significant reduction in PM2.5 concentration, preventing an estimated 7,960 premature deaths and saving approximately 2,602.95 m yuan in health-related economic costs.

Originality/value

This study introduces an innovative framework for evaluating the environmental effect of policies, with a specific emphasis on health synergistic benefits.
Development of electric/near-infrared light-driven shape memory rGO/EVA composite films for deployable structures
Authors: Jiang Xiaojian , Zhang Zhonggui , Cheng Jiafei , Ai Yongjie , Zhang Ziyue , Wang Shuolei , Xu Shi , Gao Hongyu , Dong Yubing
Published: February 2025

Purpose

This study aims to fabricate the reduced graphene oxide (rGO)/ethylene vinyl acetate copolymer (EVA) composite films with electric-driven two-way shape memory properties for deployable structures application. The effect of dicumyl peroxide (DCP) and rGO on the structure and properties of the rGO/EVA composite films were systematically investigated.

Design/methodology/approach

The rGO/EVA composite films were fabricated by melting blend and swelling-ultrasonication method, DCP and rGO were used the crosslinking agent and conductive filler, respectively.

Findings

The research results indicate that the two-way shape memory properties of rGO/EVA composite films were significantly improved with the increase of DCP content. The rGO endowed rGO/EVA composite films with excellent electric-driven reversible two-way shape memory and anti-ultraviolet aging properties. The sample rGO/EVA-9 can be heated above Tm within 8 s at a voltage of 35 V and can be heated above the Tm temperature within 12 s under near-infrared light (NIR). Under a constant stress of 0.07 MPa, the reversible strain of the sample rGO/EVA-9 was 8.96% and its electric-driven shape memory behavior maintained great regularity and stability.

Research limitations/implications

The rGO/EVA composite films have potential application value in the field of deployable structures.

Originality/value

With the increase of DCP content, the two-way shape memory properties of rGO/EVA composite films were significantly improved, which effectively solved the problem that the shape memory properties of EVA matrix decreased caused by swelling. The rGO endowed rGO/EVA composite films with excellent electric/NIR driven reversible two-way shape memory properties.
Investigation of material extrusion parameters and printing material impacts on wear and friction using the Taguchi method
Authors: Aslan Enes
Published: February 2025

Purpose

The purpose of this study is to find optimum production parameters using the Taguchi method in terms of printing material (a composite material produced from polylactic acid [PLA] and polypropylene [PP]) impacts on wear and friction.

Design/methodology/approach

A composite filament coil was fabricated from PLA and PP pellets using a lab-based extrusion device. The hardness and chemical structure of the filaments were examined. The filament-based material extrusion process was used to produce cylindrical shapes for tribological (pin-on-disc) analyses. Moreover, Taguchi methodology was performed to find the most influential parameter on tribological characteristics.

Findings

The hardness (Shore D) values of the filaments were polylactic acid (PLA) (85), polypropylene (PP) (58) and PLA and PP mixture of 50:50 (PLAPP) (63). Fourier-transform infrared spectroscopy (FTIR) and thermogravimetric analysis results show that PLA and PP mixtured successfully. The diameter deviation of all samples was found as lower than 5%. The honeycomb pattern presented the best dimensional accuracy. Changing printing patterns and temperatures affect the friction profile. Coefficient of friction (COF) values of cylindrical samples of PLA and PP samples around 0.35 and 0.31, respectively. Overall, material type for wear resistance applications is a key point.

Originality/value

To the best of the author’s knowledge, there seems to be a lack of 3D-printed PP and PLAPP studied in terms of tribological aspects as a neat polymer. The tribological profiles of PP, PLA and PLAPP (PLA and PP mixture of 50:50) were investigated in this study. The author believe that this is a preliminary study that might close the gap and add some novel information to the current literature.
Memorial K-means clustering for cooperative spectrum sensing in cognitive wireless sensor networks at low SNR regimes
Authors: Tao Boyan , Wu Jun , Dou Xiaoyu , Wang Jiayu , Xu Yanhong
Published: February 2025

Purpose

The spectrum resources are becoming increasingly scarce and underutilized, and cooperative spectrum sensing (CSS) in cognitive wireless sensor networks (CWSNs) offers many solutions with good results, but this paper aims to address the significant issue of CSS in the context of low signal-to-noise ratio (SNR).

Design/methodology/approach

This study proposes Pearson Correlation Coefficient (PCC) to obtain value feature values under the Rayleigh channel model, which are then used for Memorial K-means Clustering (MKC) analysis of CSS in CWSNs at low SNR regimes. In addition, MKC algorithm is used for training and converted it into supervised model.

Findings

A series of numerical simulation results demonstrate that the correctness and effectiveness of the proposed MKC, especially the detection and false alarm probabilities in a low SNR condition. The detection probability is increased by 5%–12% at low SNR compared with other methods.

Originality/value

The MKC algorithm can reduce the impact of randomness on the clustering centers for multiple groups, which combined with PCC can effectively reduce the influence of noise at low SNR, and the unsupervised transformed model effectively reducing the complexity of re-discrimination.
Inertial effects on single-perforation plates resistivity at high flow rates: Computational fluid dynamics and experimental studies
Authors: Lopez Maël , Benchikh Le Hocine Alla Eddine , Kone Tenon Charly , Dupont Thomas , Panneton Raymond
Published: February 2025

This article is focused on the viscous and inertial effects on airflow resistivity of periodic arrays of single-perforation plates spaced by thin air cavities. Analyzing this effect would provide better insight into losses within the material, including additional losses due to increasing sound excitation levels. In this way, the material pressure drop is predicted by computational fluid dynamics function (CFD) of the flow rate for corresponding pore Reynolds numbers between 0.3 and 1500. The static airflow resistivity coefficient is determined by the linear part of the pressure drop (viscous effect) and the Forchheimer coefficient from the nonlinear part of the pressure drop (inertial effect). Both coefficients are determined on the entirety of the material (globally) and at the plate levels (locally). Good agreement is observed between CFD predictions and experimental measurements on the whole range of studied Reynolds numbers. By locally investigating the pressure drops, the observations show that the viscous effects are constant through the material. With increasing pore Reynolds number, inertial effects of the first plate dominate over those of the other plates. The consideration of the local inertial effect will be a key component in the acoustic modeling of this type of material under high sound excitation levels.
HfZrO-based synaptic resistor circuit for a Super-Turing intelligent system
Authors: Lee Jungmin , Shenoy Rahul , Deo Atharva , Yi Suin , Gao Dawei , Qiao David , Xu Mingjie , Asapu Shiva , Rong Zixuan , Nathan Dhruva , Hei Yong , Paladugu Dharma , Zheng Jian-Guo , Yang J. Joshua , Williams R. Stanley , Wu Qing , Chen Yong
Published: February 2025

Computers based on the Turing model execute artificial intelligence (AI) algorithms that are either programmed by humans or derived from machine learning. These AI algorithms cannot be modified during the operation process according to environmental changes, resulting in significantly poorer adaptability to new environments, longer learning latency, and higher power consumption compared to the human brain. In contrast, neurobiological circuits can function while simultaneously adapting to changing conditions. Here, we present a brain-inspired Super-Turing AI model based on a synaptic resistor circuit, capable of concurrent real-time inference and learning. Without any prior learning, a circuit of synaptic resistors integrating ferroelectric HfZrO materials was demonstrated to navigate a drone toward a target position while avoiding obstacles in a simulated environment, exhibiting significantly superior learning speed, performance, power consumption, and adaptability compared to computer-based artificial neural networks. Synaptic resistor circuits enable efficient and adaptive Super-Turing AI systems in uncertain and dynamic real-world environments.
Sea ice pattern effect on Earth’s energy budget is characterized by hemispheric asymmetry
Authors: Zhou Chen , Wang Qingming , Tan Ivy , Zhang Lujun , Zelinka Mark D. , Wang Minghuai , Bloch-Johnson Jonah
Published: February 2025

Earth’s energy budget is sensitive to the spatial distribution of sea surface temperature and sea ice concentration (SIC) change, but the global radiative effect of changes in SIC spatial distribution has not been quantified. We show that SIC-induced radiation anomalies at the top of the atmosphere are sensitive to the location of SIC reduction in each season, which qualitatively explains how and why the effect of sea ice loss on Earth’s energy budget is determined by its spatial pattern. Idealized experiments indicate that SIC-induced surface warming is greater in the Arctic regions, resulting in a more negative Planck feedback. Global low-level cloud cover responses to Arctic and Antarctic SIC reduction are also distinct, leading to more negative SIC-cloud feedback in Arctic regions. SIC-induced albedo feedback is sensitive to latitude due to inhomogeneous solar radiation at the surface. As a result, the simulated radiative effect of SIC anomalies during 1980–2019 is dominated by variations in the spatial pattern of SIC.
DOG1 controls dormancy independently of ABA core signaling kinases regulation by preventing AFP dephosphorylation through AHG1
Authors: Krüger Thorben , Brandt Dennis , Sodenkamp Johanna , Gasper Michael , Romera-Branchat Maida , Ahloumessou Florian , Gehring Elena , Drotleff Julia , Bell Christopher , Kramer Katharina , Eirich Jürgen , Soppe Wim J. J. , Finkemeier Iris , Née Guillaume
Published: February 2025

Seed dormancy determines germination timing, influencing seed plant adaptation and overall fitness. DELAY OF GERMINATION 1 (DOG1) is a conserved central regulator of dormancy cooperating with the phytohormone abscisic acid (ABA) through negative regulation of ABA HYPERSENSITIVE GERMINATION (AHG) 1 and AHG3 phosphatases. The current molecular mechanism of DOG1 signaling proposes it regulates the activation of central ABA-related SnRK2 kinases. Here, we unveil DOG1’s functional autonomy from the regulation of ABA core signaling components and unravel its pivotal control over the activation of ABSCISIC ACID INSENSITIVE FIVE BINDING PROTEINs (AFPs). Our data revealed a molecular relay in which AFPs’ genuine activation by AHG1 is contained by DOG1 to prevent the breakdown of maturation-imposed ABA responses independently of ABA-related kinase activation status. This work offers a molecular understanding of how plants fine-tune germination timing, while preserving seed responsiveness to adverse environmental cues, and thus represents a milestone in the realm of conservation and breeding programs.
Cystic fibrosis alters the structure of the olfactory epithelium and the expression of olfactory receptors affecting odor perception
Authors: Caballero Ignacio , Mbouamboua Yvon , Weise Susanne , López-Gálvez Raquel , Couralet Marie , Fleurot Isabelle , Pons Nicolas , Barrera-Conde Marta , Quílez-Playán Nayima , Keller Matthieu , Klymiuk Nikolai , Robledo Patricia , Hummel Thomas , Barbry Pascal , Chamero Pablo
Published: February 2025

A reduced sense of smell is a common condition in people with cystic fibrosis (CF) that negatively affects their quality of life. While often attributed to nasal mucosa inflammation, the underlying causes of the olfactory loss remain unknown. Here, we characterized gene expression in olfactory epithelium cells from patients with CF using single-nuclei RNA sequencing and found altered expression of olfactory receptors (ORs) and genes related to progenitor cell proliferation. We confirmed these findings in newborn, inflammation-free samples of a CF animal model and further identified ultrastructural alterations in the olfactory epithelium and bulbs of these animals. We established that CFTR, the anion channel whose dysfunction causes CF, is dispensable for odor-evoked signaling in sensory neurons, yet CF animals displayed defective odor-guided behaviors consistent with the morphological and molecular alterations. Our study highlights CF’s major role in modulating epithelial structure and OR expression, shedding light on the mechanisms contributing to olfactory loss in CF.
Composition and function of AChR chimeric autoantibody receptor T cells for antigen-specific B cell depletion in myasthenia gravis
Authors: Oh Sangwook , Khani-Habibabadi Fatemeh , O’Connor Kevin C. , Payne Aimee S.
Published: February 2025

In acetylcholine receptor (AChR)–seropositive myasthenia gravis (MG), anti-AChR autoantibodies impair neuromuscular transmission and cause severe muscle weakness. MG therapies broadly suppress immune function, risking infections. We designed a chimeric autoantibody receptor (CAAR) expressing the 210–amino acid extracellular domain of the AChR α subunit (A210) linked to CD137-CD3ζ cytoplasmic domains to direct T cell cytotoxicity against anti-AChRα B cells. A210-CAART incorporating a CD8α transmembrane domain (TMD8α) showed functional but unstable surface expression, partially restored by inhibiting lysosomal degradation. A210-CAART with a CD28 TMD showed sustained surface expression, independent of TMD dimerization motifs. In a mouse xenograft model, A210.TMD8α-CAART demonstrated early control of anti-AChR B cell outgrowth but subsequent rebound and loss of surface CAAR expression, whereas A210.TMD28-CAART induced sustained surface CAAR expression and target cell elimination. This study demonstrates the importance of the CD28 TMD for CAAR stability and in vivo function, laying the groundwork for future development of precision cellular immunotherapy for AChR-MG.
Adaptive cold-atom magnetometry mitigating the trade-off between sensitivity and dynamic range
Authors: Ma Zhu , Han Chengyin , Tan Zhi , He Haihua , Shi Shenzhen , Kang Xin , Wu Jiatao , Huang Jiahao , Lu Bo , Lee Chaohong
Published: February 2025

Cold-atom magnetometers can achieve an exceptional combination of superior sensitivity and high spatial resolution. One key challenge that these quantum sensors face is improving the sensitivity within a given timeframe while preserving a high dynamic range. Here, we experimentally demonstrate an adaptive entanglement-free cold-atom magnetometry with both superior sensitivity and high dynamic range. Using a tailored adaptive Bayesian quantum estimation algorithm designed for Ramsey interferometry using coherent population trapping (CPT), cold-atom magnetometry facilitates adaptive high-precision detection of a dc magnetic field with high dynamic range. Through implementing a sequence of correlated CPT-Ramsey interferometry, the sensitivity significantly surpasses the standard quantum limit with respect to total interrogation time. We yield a sensitivity of 6.8 ± 0.1 picotesla per square root of hertz over a range of 145.6 nanotesla, exceeding the conventional frequentist protocol by 3.3 ± 0.1 decibels. Our study opens avenues for the next generation of adaptive cold-atom quantum sensors, wherein real-time measurement history is leveraged to improve their performance.
Postselection shifts the transition frequency of helium in an atomic beam
Authors: Wen Jin-Lu , Tang Jia-Dong , Lv Ya-Nan , Sun Yu R. , Zou Chang-Ling , Dong Jun-Feng , Hu Shui-Ming
Published: February 2025

Postselecting output states can effectively amplify weak signals in measurements. However, the postselection (PS) effect may also introduce unintended biases in precision measurements. Here, we investigate the influence of PS in the precision spectroscopy of the 2
3
S
− 2
3
P
transition of helium (
4
He) using an atomic beam. We directly observe that PS based on atomic positions causes a shift in the measured transition frequency, amounting to approximately −55 kHz. After accounting for this PS shift, we obtain a corrected frequency of 276,764,094,712.45 ± 0.86 kHz for the 2
3
S
1
− 2
3
P
0
transition. Combining this result with existing data for
3
He, we derive a value for the difference in squared nuclear charge radii, which shows a σ deviation from measurements of muonic helium ions, potentially pointing to new physics that challenges lepton universality in quantum electrodynamics.
Effects of pedestal-mounted electric fans on self-reported symptoms and mood-state in older adults exposed to indoor overheating during a simulated heatwave: an exploratory analysis
Authors: O'Connor Fergus , McGarr Gregory W. , Harris-Mostert Roberto C. , Boulay Pierre , Sigal Ronald J , Meade Robert D. , Kenny Glen P.
Published: February 2025

Recent evidence from modelling and laboratory-based studies showed that electric fans are ineffective at lowering core temperature in older adults at air temperatures of 36°C. However, their influence on self-reported environmental symptoms and mood-state during daylong use in hot indoor environments remains unclear. Eighteen older adults (8 females, median [interquartile range]; 72 [67-76 years]) completed three randomized 8-hour heat exposures (36°C, 45% relative humidity) with a fan generating air speeds of 0 (no fan, Control), 2, or 4 m/s at the front of the body positioned 1-m away. Participants were seated throughout, except for 4 x 10-min periods of simulated activities of daily living (stepping [~2.25 METs]). Core temperature, mean skin temperature, and heart rate areas under the curve (AUC, hours 0-8) were calculated to assess cumulative physiological strain. Total symptom scores (68-item environmental symptoms questionnaire) as well as total mood disturbance and energy index (40-item profile of mood states questionnaire) were evaluated at end-heating (adjusted for pre-exposure). Core temperature, mean skin temperatures, and heart rate AUCs were not different between conditions (all P≥0.087). Total symptom scores were 0.89-fold [0.81,0.97] lower with fan use (combined across speeds) compared to no fan (P=0.009). Energy index scores were 2.4 points [0.8,4.0] higher with fan use compared to no fan (P=0.004). However, mood disturbance was not significantly different between conditions (P=0.345). Our exploratory analysis show that fans can reduce self-reported symptoms and increase perceived energy levels in older adults in overheated indoor environments, despite no meaningful attenuation of physiological strain.
A Lightweight Deep Learning-Based Method for Anomalous Traffic Detection in Wireless Communication Networks
Authors: Lu Yan , Yang Qiufen , Kuang Yunxin
Published: February 2025

Aiming at the problem that the application of deep learning method in abnormal traffic detection of wireless communication network is limited due to its high complexity, a new method based on lightweight deep learning for abnormal traffic detection of wireless communication networks is proposed. According to the actual situation of wireless communication network traffic, the collection strategy is dynamically adjusted through the adaptive traffic collection method to ensure the effective collection of key traffic data. After the collected network traffic data are converted into a two-dimensional gray-scale image, the image is input into the lightweight convolutional neural network MobileNetV3 model. This model significantly reduces the amount of parameters and computation of the model through deeply separable convolution, effectively reducing the computational complexity and dealing with the problem of low fusion of different channel features when detecting wireless communication network traffic with a large amount of noise and redundant information, quickly extracts important features useful for traffic anomaly detection. At the same time, based on the extracted features, the model classifies the traffic data through the Softmax layer to detect abnormal traffic in wireless communication networks. Experimental results show that this method not only improves the efficiency and accuracy of detection, but also significantly enhances the stability and adaptability of wireless communication networks in the face of complex environments. It can be effectively applied to the field of wireless communication network anomaly detection.
Image-Enhanced Asphalt Crack Detection Research
Authors: Ye Wangping , Wu Guibin , Peng Hao , Wu Chengzhong
Published: February 2025

The main environmental factors that interfere with asphalt pavement crack detection include shadows from ambient light of different intensities, trees, signboards, railings, etc. Traditional crack detection methods usually eliminate the effect of light during pre-processing or improve the recognition results by local consistency and light normalization during image segmentation. However, the current methods can only improve the image brightness uniformity and cannot completely eliminate the effect of light, so the usual methods are only effective when the image brightness uniformity is good. So, this study puts out an approach to improving images. Machine learning is used to suggest a method for detecting cracks in asphalt pavement, with the help of an attention mechanism, using photos of real roads as the experimental dataset. Experiments show that the method can preprocess image data well and enhance the robustness of training in machine learning structures. Test results show that our method can be well applied to practical testing work.
Application of Big Data Analytics in Financial Decision-Making: Integrating Computational Models to Optimize Investment Strategies
Authors: Zhou Qing
Published: February 2025

The application of big data analytics in financial decision-making has become pivotal in addressing the complexities of modern financial markets. With the growing availability of high-dimensional and high-frequency data, traditional investment strategies often fail to capture dynamic market behaviors and multi-scale dependencies. Conventional methods, grounded in static models and linear assumptions, lack the flexibility and robustness required for optimizing financial decision-making in volatile and interconnected markets. This paper aligns with the scope of computational advancements in financial systems, introducing an Adaptive Investment Optimization Model (AIOM) that integrates deep learning, stochastic modeling, and reinforcement learning to enhance investment strategies. By leveraging multi-scale feature extraction, dynamic market state estimation, and a reinforcement learning-based optimization engine, the model achieves superior adaptability and precision. Our novel Market-Aware Optimization Framework (MOF) further refines portfolio management by dynamically adjusting allocations based on predictive market signals and advanced risk measures, such as Conditional Value at Risk (CVaR) and drawdown control. Experimental results demonstrate significant improvements in portfolio returns and risk management compared to traditional methods. This work exemplifies the potential of computational innovations in transforming financial decision-making, offering robust solutions for real-time, adaptive investment optimization.
Duffin–Kemmer–Petiau equation with Mie-Type potential in the noncommutative space
Authors: Bagheri F. Z. , Motevalli S. M. , Hosseini S. S.
Published: February 2025

In this paper, we investigate the approximate analytical solutions of the relativistic Duffin–Kemmer–Petiau equation in the presence of a Mie-Type potential in noncommutative space by using the Nikiforov–Uvarov method. We determine the energy eigenvalues and eigenfunctions of the DKP equation. Furthermore, energy shift due to noncommutativity space–time is obtained via the perturbation theory. We observe that this feature is comparable to the Zeeman effect and the degeneracy of the classical spectral line is fractured in the transition from commutative to noncommutative space by the splitting of the states.
Impact of density fluctuations on solvent-induced interaction: A combined theoretical and simulation study
Authors: Deng Youer , Zhou Shiqi
Published: February 2025

This study investigates solvent-induced interactions between two large particles immersed in a Lennard-Jones (LJ) solvent bath using molecular dynamics simulations and classical density functional theory. The LJ energy parameter between the large particles and the solvent particles is 1.439 times that of solvent–solvent interactions. The predictions of excess mean force align well under supercritical conditions with moderate or lower bulk solvent densities and moderate temperatures. However, deviations arise at high-density and high-temperature conditions, attributed to the reflective boundary conditions used in the theoretical calculations, which inadequately capture solid-like ordering effects. The study further explores the temperature dependence of the excess potential of mean force (PMF) at fixed reduced bulk densities ranging from 0.1 to 0.6 (in increments of 0.1). Within the gas density range, the excess PMF exhibits attractive behavior, with potential depths reaching up to 30 times the solvent particle LJ energy parameter as the gas density decreases and the temperature approaches saturation. Conversely, in the solvent liquid density range, the excess PMF remains repulsive, even near the saturation temperature. As the temperature increases, the excess PMF shifts upward, becoming less attractive or more repulsive, with the gas density range showing greater temperature sensitivity compared to the liquid density range. The substantial deepening of the potential well in the excess PMF leads to a significant increase in the critical temperature. Consequently, under a fixed system temperature, the working fluid operates in subcritical conditions. This behavior opens avenues for various phenomena, including wetting transition, enhanced adsorption and modified self-assembly, which can be exploited to achieve specific technical objectives.
Novel singular and non-singular complexiton, interaction wave and the complex multi-soliton solutions to the generalized nonlinear evolution equation
Authors: Wang Kang-Jia , Liu Xiao-Lian , Wang Wei-Dong , Li Shuai , Zhu Hong-Wei
Published: February 2025

The main task of this paper is to plumb some new exact solutions of the (3 + 1)-dimensional generalized nonlinear evolution equation (gNEE) for shallow water waves. In the light of the Hirota method and symbolic computation, a novel ansatz function is proposed to develop the singular complexiton solutions. Meanwhile, the nonsingular complexiton solutions are derived with the introduction of certain constraints. In addition, the interaction wave solutions and the complex multi-soliton solutions are also explored. The profiles of the acquired exact solutions are depicted graphically to exhibit the corresponding physical behaviors. To the best of the authors’ knowledge, the outcomes presented in the work are entirely new and have not been investigated in other literature works, which can extend the exact solutions of the considered equation and enable us to study its nonlinear dynamics better.
Exploration of variable fluid properties in a pressure gradient driven generalized vortex flow dynamics using numerical approach
Authors: Shakeel Ariba , Mustafa Meraj , Naganthran Kohilavani
Published: February 2025

Motivation: Vortex flow, which refers to the movement of fluid around an axis called a vortex line, finds applications in designing aircraft wings, mixing processes in chemical, and pharmaceutical processes, and understanding flows around tornadoes and cyclones. Background: Previous research on variable properties has demonstrated they are crucial in scenarios with significant temperature gradients. Methodology: This paper looks at the boundary layer developments under a generalized vortex flow considering temperature-dependent fluid properties. The generalized vortex represents the far-field tangential velocity in a power-law format and can be simplified to two specific cases: (i) rigid-body rotation and (ii) potential vortex. For mathematical analysis, two distinct variable viscosity models are employed, where a correlation between viscosity and temperature is inversely linear, while the other one is on the exponential temperature dependency model. Numerical Method: A highly robust and convenient built-in tool of MATLAB known as bvp5c is implemented to present exact similarity analyses of the models. Main Findings: The study concludes that velocity profiles obtained under variable physical properties are lower than those calculated with constant properties. Moreover, when liquid properties are considered, the solution curves from the two variable viscosity models show a close resemblance. Thicker thermal diffusion layers and reduced boundary heat flux are associated with increased values of the power law parameter.