bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forecasting fluid-injection induced seismicity to choose the best injection strategy for safety and efficiency
Authors: Boyet Auregan , Vilarrasa Víctor , Rutqvist Jonny , De Simone Silvia 
Published: June 2024

Induced seismicity poses a challenge to the development of Enhanced Geothermal Systems (EGS). Improving monitoring and forecasting techniques is essential to mitigate induced seismicity and thereby fostering a positive perception of EGS projects among local authorities and population. Induced seismicity is the result of complex and coupled thermo-hydro-mechanical-chemical mechanisms. Injection flux and pressure are crucial controlling parameters for both hydraulic stimulation and circulation protocols. We develop a methodology combining a hydro-mechanical model with a seismicity rate model to estimate the magnitude and frequency of mainshocks and aftershocks induced by fluid injection. We apply the methodology to the case of the Basel EGS (2006, Switzerland) to compare the effects of progressive, cyclic and constant injections on the mechanical response of discrete faults. Results from the coupled hydro-mechanical models show that the pore pressure diffusion and consequent enhancement of fault permeability are limited to the vicinity of the injection well during cyclic injection. Additionally, constant injection induces seismicity from the start of the injection but enhances the permeability of most of the faults within a shorter duration, inducing less post-injection seismicity. The methodology can be adapted to any numerical model and allows new projects to be developed by anticipating the safest injection protocol.
This article is part of the theme issue ‘Induced seismicity in coupled subsurface systems’.
Functional and Structural Cerebellar-Behavior Relationships in Aging
Authors: Hicks Tracey H. , Magalhães Thamires N. C. , Jackson T. Bryan , Ballard Hannah K. , Herrejon Ivan A. , Bernard Jessica A. 
Published: June 2024

AbstractHealthy aging is associated with deficits in cognitive performance and brain changes, including in the cerebellum. Yet, the precise link between cerebellar function/structure and cognition in aging remains poorly understood. We explored this relationship in 138 healthy adults (aged 35-86, 53% female) using resting-state functional connectivity MRI (fcMRI), cerebellar volume, and cognitive and motor assessments in an aging sample. We expected to find negative relationships between lobular volume for with age, and positive relationships between specific lobular volumes with motor and cognition respectively. We predicted lower cerebellar fcMRI to cortical networks and circuits with increased age. Behaviorally, we expected higher cerebello-frontal fcMRI cerebellar connectivity with association areas to correlate with better behavioral performance. Behavioral tasks broadly assessed attention, processing speed, working memory, episodic memory, and motor abilities. Correlations were conducted between cerebellar lobules I-IV, V, Crus I, Crus II, vermis VI and behavioral measures. We found lower volumes with increased age as well as bidirectional cerebellar connectivity relationships with increased age, consistent with literature on functional connectivity and network segregation in aging. Further, we revealed unique associations for both cerebellar structure and connectivity with comprehensive behavioral measures in a healthy aging population. Our findings underscore cerebellar involvement in behavior during aging.
DiffuST: a latent diffusion model for spatial transcriptomics denoising
Authors: Jiao Shaoqing , Lu Dazhi , Zeng Xi , Wang Tao , Wang Yongtian , Dong Yunwei , Peng Jiajie 
Published: June 2024

AbstractSpatial transcriptomics technologies have enabled comprehensive measurements of gene expression profiles while retaining spatial information and matched pathology images. However, noise resulting from low RNA capture efficiency and experimental steps needed to keep spatial information may corrupt the biological signals and obstruct analyses. Here, we develop a latent diffusion model DiffuST to denoise spatial transcriptomics. DiffuST employs a graph autoencoder and a pre-trained model to extract different scale features from spatial information and pathology images. Then, a latent diffusion model is leveraged to map different scales of features to the same space for denoising. The evaluation based on various spatial transcriptomics datasets showed the superiority of DiffuST over existing denoising methods. Furthermore, the results demonstrated that DiffuST can enhance downstream analysis of spatial transcriptomics and yield significant biological insights.
Network-community analysis of cellular senescence
Authors: Sabalic Alda , Moiseeva Victoria , Cisneros Andres , Deryagin Oleg , Perdiguero Eusebio , Munñz-Cánoves Pura , Garcia-Ojalvo Jordi 
Published: June 2024

AbstractMost cellular phenotypes are genetically complex. Identifying the set of genes that are most closely associated with a specific cellular state is still an open question in many cases. Here we study the transcriptional profile of cellular senescence using a combination of network-based approaches, which include eigenvector centrality feature selection and community detection. We apply our method to cell-type-resolved RNA sequencing data obtained from injured muscle tissue in mice. The analysis identifies some genetic markers consistent with previous findings, and other previously unidentified ones, which are validated with previously published single-cell RNA sequencing data in a different type of tissue. The key identified genes, both those previously known and the newly identified ones, are transcriptional targets of factors known to be associated with established hallmarks of senescence, and can thus be interpreted as molecular correlates of such hallmarks. The method proposed here could be applied to any complex cellular phenotype even when only bulk RNA sequencing is available, provided the data is resolved by cell type.
Increased recognition memory precision with decreased neural discrimination
Authors: Güsten Jeremie , Berron David , Ziegler Gabriel , Düzel Emrah 
Published: June 2024

AbstractMnemonic discrimination (MD), the ability to distinguish between similar experiences in memory, is essential for memory precision. We hypothesized that training mnemonic discrimination should improve memory precision by increasing the neural activity differences between a new experience and a similar familiar experience (repeat). Participants performed a 2-week, web-based training program. For group 1, memory similarity was adapted to performance. Group 2 trained non-adaptively and group 3 served as active control. Adaptivity improved training gain and led to transfer to other memory tasks. Surprisingly, training reduced neural activity differences between new (lure) and similar familiar (repeat) experiences. Thus, instead of enhancing neural activity to lures and decreasing neural activity to repeats, training led to increased activity to repeats. In several brain regions this pattern was associated with improved MD. These findings highlight an unexpected neural mechanism underpinning improved memory precision in recognition memory.
Targeting dendritic cell-specific TNFR2 improves skin and joint inflammation by inhibiting IL-12/ IFN-γ pathways in a mouse model of psoriatic arthritis
Authors: Kaur Raminderjit , Harvey Jennifer M. , Brambilla Roberta , Chandrasekharan Unnikrishnan M. , Elaine Husni M. 
Published: June 2024

ABSTRACTPsoriasis (PsO) and Psoriatic arthritis (PsA) are immune-mediated inflammatory diseases affecting the skin and joints. Approximately, 30% of patients with PsO develop PsA over time with both conditions being associated with elevated tumor necrosis factor-alpha (TNF-α) expression. TNF-α mediates its effect through two membrane receptors, TNFR1 and TNFR2. While current TNF-α-neutralizing agents, targeting both TNFR1 and TNFR2 receptors, constitute the primary treatment for psoriatic diseases, their long-term use is limited due to an increase in opportunistic infections, tuberculosis reactivation and malignancies likely attributed to TNFR1 inactivation.Recent findings suggest a pivotal role of TNFR2 in psoriatic disease, as evidenced by its amelioration in global TNFR2-knockout (TNFR2KO) mice, but not in TNFR1KO mice. The diminished disease phenotype in TNFR2KO mice is accompanied by a decrease in DC populations. However, the specific contribution of TNFR2 in dendritic cells (DCs) remains unclear. Here, utilizing a mannan-oligosaccharide (MOS)-induced PsA model, we demonstrate a significant reduction in PsA-like skin scaling and joint inflammation in dendritic cell-specific TNFR2 knockout mice (DC-TNFR2KO). Notably, MOS treatment in control mice (TNFR2 fl/fl) led to an increase in conventional type 1 dendritic cells (cDC1) population in the spleen, a response inhibited in DC-TNFR2KO mice. Furthermore, DC-TNFR2KO mice exhibited reduced levels of interleukin-12 (IL-12), a Th1 cell activator, as well as diminished Th1 cells, and interferon-gamma (IFN-γ) levels in the serum compared to controls following MOS stimulation.In summary, our study provides compelling evidence supporting the role of TNFR2 in promoting PsA-like inflammation through cDC1/Th1 activation pathways.
Off-target drift of the herbicide dicamba disrupts plant-pollinator interactionsvianovel pathways
Authors: Baucom Regina S , Iriart Veronica , Soble Anah , Armstrong Matthew R. , Ashman Tia-Lynn 
Published: June 2024

AbstractAssessing the impact of herbicide drift on plant-pollinator interactions is crucial for providing insight into the causes of ongoing pollinator declines. The recent exponential increase in the use of the synthetic auxin herbicide dicamba, which is known to drift long distances following application, renders this concern especially acute. However, experimental data on the consequences of dicamba drift on plant-pollinator interactions are lacking from weed communities in natural settings. We assessed the indirect effects of dicamba drift on pollinator visits for 11 weeds of agricultural crops using a common garden field experiment, focusing on the potential for changes in pollinator abundance and alterations to both plant traits and patterns of pollinator visitation. We found variation among plant species in the extent of damage from dicamba drift exposure, and variation in how growth, flowering time, and flower displays were impacted, with some species showing negative impacts and others showing little effect. Pollinator frequencies were reduced in dicamba-exposed plots, and pollinator approaches and foraging visits were reduced for some weed species yet not others. Structural equation modeling revealed that the relationship between flower display and pollinator visits was disrupted in the presence of dicamba compared to control plots. Our study provides the most comprehensive picture to date of the impacts of dicamba drift on plant-pollinator interactions, with findings that highlight an underappreciated role of services supplied by weedy communities at the agroecological interface.
Bound-state stability of Coulomb three-body systems using numerical tensor methods
Authors: Brice Kammegne Tcheugam , Melgaard Michael , Cox Hazel 
Published: June 2024

In this paper we present a unified treatment of three-body atoms and molecules using numerical tensor methods. The Schrödinger equation in perimetric coordinates is recast in a canonical tensor format. It is shown that the Schrödinger equation can be solved in this full-tensor format but that by using a low-rank tensor decomposition, in particular the tensor-train and quantized-tensor-train formats, energies accurate to at least the nanohartree can be obtained for the He atom (in which the mass of the uniquely charged particle is much greater than the other two particles), the positronium negative ion (Ps−, in which all the masses are equal), and the non-Born-Oppenheimer H2+ molecule (in which the mass of the uniquely charged particle is much smaller than the other two particles).

Published by the American Physical Society
2024
Simultaneous multiband radio-frequency detection using high-orbital-angular-momentum states in a Rydberg-atom receiver
Authors: Allinson Gianluca , Jamieson Matthew J. , Mackellar Andrew R. , Downes Lucy , Adams C. Stuart , Weatherill Kevin J. 
Published: June 2024

We demonstrate simultaneous detection of radio-frequency (rf) fields ranging from the very high-frequency (VHF) band (128 MHz) to terahertz frequencies (0.61 THz) using high-orbital-angular-momentum (ℓ) states in a caesium Rydberg-atom receiver. rf fields are applied concurrently to a series of atomic transitions, where the application of each field allows access to the next-highest ℓ state and the energy separations between states become progressively smaller, allowing access to a very wide range of radio frequencies. We show that the optical response of the system in the presence of the rf fields can be reproduced theoretically using a simple Lindblad-master-equation approach. Furthermore, we demonstrate experimentally that a series of amplitude-modulated tones can be detected simultaneously using a wide range of carrier frequencies. This demonstration opens the way for Rydberg receivers to access low-frequency rf bands at low principal quantum number and allows for communications across multiple bands simultaneously using a single optical receiver. Moreover, the experimental method presented allows for high-resolution spectroscopy of high-orbital-angular-momentum states in alkali-metal atoms.

Published by the American Physical Society
2024
Redefining supply chain sustainability: introducing the context of extreme weather events
Authors: Orji Ifeyinwa Juliet , Ojadi Francis I. 
Published: June 2024

PurposeExtreme weather events are on the rise around the globe. Nevertheless, it is unclear how these extreme weather events have impacted the supply chain sustainability (SCS) framework. To this end, this paper aims to identify and analyze the aspects and criteria to enable manufacturing firms to navigate shifts toward SCS under extreme weather events.Design/methodology/approachThe Best-Worst Method is deployed and extended with the entropy concept to obtain the degree of significance of the identified framework of aspects and criteria for SCS in the context of extreme weather events through the lens of managers in the manufacturing firms of a developing country-Nigeria.FindingsThe results show that extreme weather preparedness and economic aspects take center stage and are most critical for overcoming the risk of unsustainable patterns within manufacturing supply chains under extreme weather events in developing country.Originality/valueThis study advances the body of knowledge by identifying how extreme weather events have become a significant moderator of the SCS framework in manufacturing firms. This research will assist decision-makers in the manufacturing sector to position viable niche regimes to achieve SCS in the context of extreme weather events for expected performance gains.
Intertwining entrepreneurial motivation and the global mindset: a look into entrepreneurial profiles and business outcomes
Authors: Mitan Andreea , Vătămănescu Elena-Mădălina , Dincă Violeta-Mihaela , Ghigiu Mihai-Alexandru 
Published: June 2024

PurposeThis article explores the connections between the entrepreneur's global mindset and entrepreneurial motivation in the quest for determining the underlying relationships among these constructs. The aim of the study resides in the advancement of various entrepreneurial profiles which imply specific configurations of the global mindset and motivational drivers, by also covering their correlations with the business outcomes.Design/methodology/approachData were collected in 2022 from over 100 entrepreneurs operating in the Romanian SMEs sector, using a questionnaire-based survey.FindingsThe results posit that at least three statistically relevant clusters can be observed in the studied population, stemming from the particularities of the entrepreneurs' global mindset. The findings reveal that the levels of development of the entrepreneur's social capital, psychological capital and intellectual capital are linked to different entrepreneurial motivations and impact the company in specific manners.Practical implicationsThe research offers useful cues to the entrepreneurs for identifying prospective partners for their local or cross-border operations.Originality/valueThe results foster a new topical framework for discussion on the motivational configurations of entrepreneurs and the global mindset.
Numerical approximation of parabolic singularly perturbed problems with large spatial delay and turning point
Authors: Sharma Amit , Rai Pratima 
Published: June 2024

PurposeSingular perturbation turning point problems (SP-TPPs) involving parabolic convection–diffusion Partial Differential Equations (PDEs) with large spatial delay are studied in this paper. These type of equations are important in various fields of mathematics and sciences such as computational neuroscience and require specialized techniques for their numerical analysis.Design/methodology/approachWe design a numerical method comprising a hybrid finite difference scheme on a layer-adapted mesh for the spatial discretization and an implicit-Euler scheme on a uniform mesh in the temporal variable. A combination of the central difference scheme and the simple upwind scheme is used as the hybrid scheme.FindingsConsistency, stability and convergence are investigated for the proposed scheme. It is established that the present approach has parameter-uniform convergence of OΔτ+K−2(lnK)2, where Δτ and K denote the step size in the time direction and number of mesh-intervals in the space direction.Originality/valueParabolic SP-TPPs exhibiting twin boundary layers with large spatial delay have not been studied earlier in the literature. The presence of delay portrays an interior layer in the considered problem’s solution in addition to twin boundary layers. Numerical illustrations are provided to demonstrate the theoretical estimates.
How a publicized leader transgression can affect member outcomes and gift purchasing of associated symbolic products
Authors: Briggs Elten , Torres Rico Abigail , Kizer Tracy R. , Yang Zhiyong 
Published: June 2024

Purpose
This study aims to examine the ramifications of an unfavorable public incident resulting from an organizational leader’s transgression on member outcomes and their intentions to purchase associated symbolic products as gifts. This study also considers how members’ attributions of organizational control affect the relationship between members’ organizational identification and their purchase behavior.

Design/methodology/approach
The study applies a longitudinal design involving two rounds of data collection over two years to examine a case of leadership transgression. Using the customer panel of a privately owned retailer, sorority members were surveyed before and after an unfavorable public incident involving their president. This study applied t-tests of mean differences and regression analyses to test the hypotheses.

Findings
After the leader’s transgressions were publicized, sorority members exhibited lower levels of cognitive organizational identification, satisfaction with the organization and purchase intention of organizational gifts. The association between cognitive organizational identification and gift purchase intentions was stronger after the incident. Further, controllability attributions positively moderated the association between cognitive organizational identification and the intended purchase quantity of organizational products after the incident.

Research limitations/implications
The sample limits the generalizability of the findings, as the study is conducted on one case of a leader’s transgression in an identity-based organization (IBO).

Practical implications
The findings imply that efforts to repair customer identification should be taken rather than satisfaction enhancement when a leader of an IBO commits a public transgression.

Originality/value
To the best of the authors’ knowledge, this is the first study to apply identity threat theory to understand how an organizational leader’s public transgression affects member outcomes and purchasing. The findings imply that it is critical to repair members’ identification when these situations arise. The use of a real case and a longitudinal research design are rare contributions to this research stream.
Efficient modeling of liquid splashing via graph neural networks with adaptive filter and aggregator fusion
Authors: Nan Jinyao , Feng Pingfa , Xu Jie , Feng Feng 
Published: June 2024

Purpose
The purpose of this study is to advance the computational modeling of liquid splashing dynamics, while balancing simulation accuracy and computational efficiency, a duality often compromised in high-fidelity fluid dynamics simulations.

Design/methodology/approach
This study introduces the fluid efficient graph neural network simulator (FEGNS), an innovative framework that integrates an adaptive filtering layer and aggregator fusion strategy within a graph neural network architecture. FEGNS is designed to directly learn from extensive liquid splash data sets, capturing the intricate dynamics and intrinsically complex interactions.

Findings
FEGNS achieves a remarkable 30.3% improvement in simulation accuracy over traditional methods, coupled with a 51.6% enhancement in computational speed. It exhibits robust generalization capabilities across diverse materials, enabling realistic simulations of droplet effects. Comparative analyses and empirical validations demonstrate FEGNS’s superior performance against existing benchmark models.

Originality/value
The originality of FEGNS lies in its adaptive filtering layer, which independently adjusts filtering weights per node, and a novel aggregator fusion strategy that enriches the network’s expressive power by combining multiple aggregation functions. To facilitate further research and practical deployment, the FEGNS model has been made accessible on GitHub (https://github.com/nanjinyao/FEGNS/tree/main).