bluuebunny/crossref_metadata_2025 huggingface dataset:
Multidisciplinary Optimization of Gyroid Topologies for a Cold Plate Heat Exchanger Design
Authors: Daifalla Elhusseiny , Shahpar Shahrokh , Tristanto Indi , Carta Mario
Published: September 2024

The strive to reduce the environmental impact of aviation has led to electrification and increasing demand for powerful on-board power electronic systems. These high-performance electrical components are bound to produce significant amounts of low-quality heat waste that, if not dissipated properly, will lead to malfunctioning and even permanent damage. For this reason, high-performance heat exchangers (HX) represent a key enabler for future advances in aircraft systems electrification and are vital to meet net zero goals and reduce the aviation's carbon footprint. For a given volume of the exchanger, the heat flow rate can be increased by adopting more sophisticated fluid domains. However, excessive geometrical complexity will lead to an increase in pressure losses, often resulting in inhomogeneous temperature distributions. In this paper, a novel optimization procedure is employed to maximize the efficiency of a high-performance heat exchanger, while minimizing overall pressure loss and temperature gradients. The optimization is performed with full three-dimensional high-fidelity computational flow simulations. The geometry of the fluid domain is constituted by triply periodic minimal surfaces (TPMS), with a parametrization based on thickness and aspect ratios, done by using the ntopology suite. To assess the performance gain, the topology-optimized design is compared against the datum case and a conventional serpentine design.
Thermal History Coatings: Influence of Atmospheric Plasma Spray Parameters on Performance
Authors: Araguás-Rodríguez Silvia , Ferran-Marqués Marta , Pilgrim Christopher C. , Kamnis Spyros , Feist Jörg P. , Nicholls John R.
Published: September 2024

Thermal history coatings (THCs) provide a novel method for measuring temperature profiles in the 900–1600 °C range. Given the steadily increasing firing temperatures in turbomachinery, it is crucial to understand temperature distribution across the majority of a component surface (>80%) to verify the design and component durability. This new temperature profiling capability records the past maximum exposure temperature in such a way that it can be determined once the component has already cooled down. THCs are comprised of oxide ceramics deposited via atmospheric plasma spraying (APS) to create a robust coating. APS deposition employs several variable parameters; spray settings such as gun power, gas flow, or scan rate can affect the particle exposure and thus the microstructure of the coating and its temperature sensing performance. This work shows, for the first time, the influence of APS parameters on luminescent measurements due to changes in the material microstructure. This enabled optimization of the thermal history coatings sensing performance. Extensive calibration data were used to develop a new model to relate the APS spray parameters to the luminescent properties in the as-deposited condition and consequent performance as a temperature sensor. The powder composition and the power and gas flow used during deposition were found to be the most influential parameters. The model identified the optimum spray parameters and was used to demonstrate THCs can achieve measurements in excess of 1600 °C.
High-Fidelity Sensing Modality for Anomaly Detection in Inkjet Printing
Authors: Chivate Aditya , Sun Hongyue , Zhou Chi
Published: September 2024

Inkjet three-dimensional (3D) printing has emerged as a transformative manufacturing technique, finding applications in diverse fields such as biomedical, metal fabrication, and functional materials production. It involves precise deposition of materials onto a moving substrate through a nozzle, achieving submillimeter scale resolution. However, the dynamic nature of droplet deposition introduces uncertainties, challenging consistent quality control. Current process monitoring, relying on image-based techniques, is slow and limited, hindering real-time feedback in erratic droplet ejection. In response to these challenges, we present the zero-dimensional ultrafast sensing (0-DUS) system, a novel, cost-effective, in situ monitoring tool designed to assess the quality of drop-on-demand inkjet printing. The 0-DUS system leverages the sensitivity of the light-beam field interference effect to rapidly and precisely detect and analyze localized droplets. Two core technical advancements drive this innovation: first, the exploration of integral sensing of the computational light-beam field, which allows for efficient extraction of temporal and spatial information about droplet evolution, introducing a novel in situ sensing modality; second, the establishment of a robust mapping mechanism that aligns sensor data with image-based data, facilitating accurate estimation of droplet characteristics. We successfully implemented the 0-DUS system within a commercial inkjet printer and conducted a comparative analysis with ground truth data. Our experimental results demonstrate a detection accuracy exceeding 95%, even at elevated speeds, allowing for an impressive in situ certification throughput of up to 500 Hz. Consequently, our proposed 0-DUS system meets the stringent quality assurance requirements, thereby expanding the potential applications of inkjet printing across a wide spectrum of industrial sectors.
Computational Design of Additively Manufactured Curvilinear Scaffolds for Bone Repair With Analytical Sensitivities
Authors: Cohen David O. , Aboutaleb Sohaila M. G. , Wagoner Johnson Amy , Norato Julian A.
Published: September 2024

This work introduces a computational method for designing ceramic scaffolds fabricated via direct ink writing (DIW) for maximum bone growth, whereby the deposited rods are curvilinear. A mechanobiological model of bone adaptation is used to compute bone growth into the scaffold, taking into account the shape of the defect, the applied loading, and the density distribution of bone in which the scaffold is implanted. The method ensures that smooth, continuously varying rod contours are produced, which are ideal for the DIW process. The method uses level sets of radial basis functions to fully define the scaffold geometry with a small number of design variables, minimizing the optimization’s computational cost. Effective elastic properties of the scaffold as a function of the scaffold design and the bone density are obtained from previously constructed surrogates. These property surrogates are in turn used to perform bone adaptation simulations of the scaffold-bone system. Design sensitivities of the bone growth within the scaffold are computed using the direct sensitivity method. A demonstration of the methodology on a scaffold implanted in a pig mandible is presented. The scaffold is optimized to maximize bone ingrowth with geometric constraints to conform to the manufacturing process.
NURBS-OT: An Advanced Model for Generative Curve Modeling
Authors: Yang Shaoliang , Wang Jun , Wang Kang
Published: September 2024

This paper presents NURBS-OT (non-uniform rational B-splines—optimal transport), a new approach in the field of computer graphics and computer-aided design (CAD)/computer-aided manufacturing (CAM) for modeling complex free-form designs like aerodynamic and hydrodynamic structures, traditionally shaped by parametric curves such as Bézier, B-spline, and NURBS. Unlike prior models that used generative adversarial networks (GANs) involving large and complex parameter sets, our approach leverages a much lighter (0.37M versus 5.05M of BézierGAN), theoretically robust method by blending optimal transport with NURBS. This integration facilitates a more efficient generation of curvilinear designs. The efficacy of NURBS-OT has been validated through extensive testing on the University of Illinois Urbana-Champaign (UIUC) airfoil and superformula datasets, where it showed enhanced performance on various metrics. This demonstrates its ability to produce precise, realistic, and esthetically coherent designs, marking a significant advancement by merging classical geometrical techniques with modern deep learning.
Phenomenological Muscle Constitutive Model With Actin–Titin Binding for Simulating Active Stretching
Authors: Sampaio de Oliveira Manuel Lucas , Uchida Thomas K.
Published: September 2024

The force produced by a muscle depends on its contractile history, yet human movement simulations typically employ muscle models that define the force–length relationship from measurements of fiber force during isometric contractions. In these muscle models, the total force–length curve can have a negative slope at fiber lengths greater than the fiber length at which peak isometric force is produced. This region of negative stiffness can cause numerical instability in simulations. Experiments have found that the steady-state force in a muscle fiber following active stretching is greater than the force produced during a purely isometric contraction. This behavior is called residual force enhancement. We present a constitutive model that exhibits force enhancement, implemented as a hyperelastic material in the febio finite element software. There is no consensus on the mechanisms responsible for force enhancement; we adopt the assumption that the passive fiber force depends on the sarcomere length at the instant that the muscle is activated above a threshold. We demonstrate the numerical stability of our model using an eigenvalue analysis and by simulating a muscle whose fibers are of different lengths. We then use a three-dimensional muscle geometry to verify the effect of force enhancement on the development of stress and the distribution of fiber lengths. Our proposed muscle material model is one of the few models available that exhibits force enhancement and is suitable for simulations of active lengthening. We provide our implementation in febio so that others can reproduce and extend our results.
Ideological self-selection in online news exposure: Evidence from Europe and the US
Authors: Mangold Frank , Schoch David , Stier Sebastian
Published: September 2024

Today’s high-choice digital media environments allow citizens to completely refrain from online news exposure and, if they do use news, to select sources that align with their ideological preferences. Yet due to measurement problems and cross-country differences, recent research has been inconclusive regarding the prevalence of ideological self-selection into like-minded online news. We introduce a multi-method design combining the web-browsing histories and survey responses of more than 7000 participants from six major democracies with supervised text classification to separate political from nonpolitical news exposure. We find that political online news exposure is both substantially less prevalent and subject to stronger ideological self-selection than nonpolitical online news exposure, especially in the United States. By highlighting the peculiar role of political news content, the results improve the understanding of online news exposure and the role of digital media in democracy.
Twisting vortex lines regularize Navier-Stokes turbulence
Authors: Buaria Dhawal , Lawson John M. , Wilczek Michael
Published: September 2024

Fluid flows are intrinsically characterized via the topology and dynamics of underlying vortex lines. Turbulence in common fluids like water and air, mathematically described by the incompressible Navier-Stokes equations (INSE), engenders spontaneous self-stretching and twisting of vortex lines, generating a complex hierarchy of structures. While the INSE are routinely used to describe turbulence, their regularity remains unproven; the implicit assumption being that the self-stretching is ultimately regularized by viscosity, preventing any singularities. Here, we uncover an inviscid regularizing mechanism stemming from self-stretching itself, by analyzing the flow topology as perceived by an observer aligned with the vorticity vector undergoing amplification. While, initially, vorticity amplification occurs via increasing twisting of vortex lines, a regularizing anti-twist spontaneously emerges to prevent unbounded growth. By isolating a vortex, we additionally demonstrate the genericity of this self-regularizing anti-twist. Our work, directly linking dynamics of vortices to turbulence statistics, reveals how the Navier-Stokes dynamics avoids the development of singularities even without the aid of viscosity.
A pleiotropic recurrent dominant
ITPR3
variant causes a complex multisystemic disease
Authors: Molitor Anne , Lederle Alexandre , Radosavljevic Mirjana , Sapuru Vinay , Zavorka Thomas Megan E. , Yang Jianying , Shirin Mahsa , Collin-Bund Virginie , Jerabkova-Roda Katerina , Miao Zhichao , Bernard Alice , Rolli Véronique , Grenot Pierre , Castro Carla Noemi , Rosenzwajg Michelle , Lewis Elyssa G. , Person Richard , Esperón-Moldes Uxía-Saraiva , Kaare Milja , Nokelainen Pekka T. , Batzir Nurit Assia , Hoffer Gal Zaks , Paul Nicodème , Stemmelen Tristan , Naegely Lydie , Hanauer Antoine , Bibi-Triki Sabrina , Grün Sarah , Jung Sophie , Busnelli Ignacio , Tripolszki Kornelia , Al-Ali Ruslan , Ordonez Natalia , Bauer Peter , Song Eunkyung , Zajo Kristin , Partida-Sanchez Santiago , Robledo-Avila Frank , Kumanovics Attila , Louzoun Yoram , Hirschler Aurélie , Pichot Angélique , Toker Ori , Mejía Cesar Andrés Muñoz , Parvaneh Nima , Knapp Esther , Hersh Joseph H. , Kenney Heather , Delmonte Ottavia M. , Notarangelo Luigi D. , Goetz Jacky G. , Kahwash Samir B. , Carapito Christine , Bajwa Rajinder P. S. , Thomas Caroline , Ehl Stephan , Isidor Bertrand , Carapito Raphael , Abraham Roshini S. , Hite Richard K. , Marcus Nufar , Bertoli-Avella Aida , Bahram Seiamak
Published: September 2024

Inositol 1,4,5-trisphosphate (IP3) receptor type 1 (
ITPR1
),
2
(
ITPR2
), and
3
(
ITPR3
) encode the IP3 receptor (IP3R), a key player in intracellular calcium release. In four unrelated patients, we report that an identical
ITPR3
de novo variant—NM_002224.3:c.7570C>T, p.Arg2524Cys—causes, through a dominant-negative effect, a complex multisystemic disorder with immunodeficiency. This leads to defective calcium homeostasis, mitochondrial malfunction, CD4
+
lymphopenia, a quasi-absence of naïve CD4
+
and CD8
+
cells, an increase in memory cells, and a distinct TCR repertoire. The calcium defect was recapitulated in Jurkat knock-in. Site-directed mutagenesis displayed the exquisite sensitivity of Arg
2524
to any amino acid change. Despite the fact that all patients had severe immunodeficiency, they also displayed variable multisystemic involvements, including ectodermal dysplasia, Charcot-Marie-Tooth disease, short stature, and bone marrow failure. In conclusion, unlike previously reported
ITPR1-3
deficiencies leading to narrow, mainly neurological phenotypes, a recurrent dominant
ITPR3
variant leads to a multisystemic disease, defining a unique role for IP3R3 in the tetrameric IP3R complex.
Coupling is key for the tropical Indian and Atlantic oceans to boost super El Niño
Authors: Fan Hanjie , Wang Chunzai , Yang Song , Zhang Guangli
Published: September 2024

The influences of the tropical Indian and Atlantic oceans on the development of El Niño Southern Oscillation (ENSO), especially regarding super El Niño events, have been a subject of debate. In particular, several studies argue that these cross-basin influences may be mere statistical artifacts resulting from the high auto-correlation of ENSO. To clarify this issue, we conduct a series of perfect model hindcast experiments to untangle the individual and synergistic effects of the tropical Indian and Atlantic oceans. Our results clearly demonstrate that without these cross-basin effects, the Pacific warming would rarely reach super El Niño level. Specifically, the individual effect of the Indian Ocean efficiently enhances the development of super El Niño events. In contrast, the Atlantic’s effect is initially limited because it fails to establish the Bjerknes feedback in the Pacific. However, when coupled with the Indian Ocean, the Atlantic’s effect becomes more pronounced as it is amplified by the Bjerknes feedback established by the Indian Ocean.
A cGAS-mediated type I interferon response in human CD4+ T cells depends on productive infection and is conserved over HIV types and strains
Authors: Janevska Marija , Cammaert Timothy , Naessens Evelien , Verhasselt Bruno
Published: September 2024

Human immunodeficiency virus (HIV) type 2 is known to be less pathogenic than HIV-1, possibly due to more effective immune control mechanisms. The mechanism of innate sensing of HIV-2 by T cells is at present unclear. In this study, we show that several primary isolates of HIV-2 (CBL20 and CI85) and HIV-1 (A8 and D2), similar to the molecular clone HIV-1 NL4.3-GFP-I, induce a significant type I interferon response in its main target, activated CD4+ T cells. However, they are unable to do so after shRNA-mediated knock-down of cGAS. In addition, both HIV-1- and HIV-2-induced type I interferon response in CD4+ T cells was dependent on productive infection and integration, as the presence of RT or integrase inhibitor dramatically suppressed the sensing. Our findings collectively showed that the cGAS-dependent type I interferon response of CD4+ T cells to HIV infection is conserved over HIV types and critically depends on productive infection.

IMPORTANCE

By unveiling the role of cGAS in sensing Human immunodeficiency virus types 1 and 2 (HIV-1 and HIV-2) across CD4+ T cells and highlighting its broader relevance that might be mirrored in other cell types, our research provides insights into the uniform mechanism of innate immune activation by different HIV isolates. By demonstrating the necessity of productive infection, we highlight the robust and specific nature of the observed cGAS-mediated innate response, dispelling concerns about contaminating plasmids triggering an immune response. Our preliminary data suggest that the lower pathogenicity of HIV-2 may not be directly correlated to superior innate immune control mediated by cGAS.
Effect of concentration, temperature, and time on the stability of hepatitis C virus nucleic acid in serum
Authors: Wang Ya-pei , Yang Shu-wen , Jia Fan , Wang Wei , Xu Xue , Wang Yi-xuan , Bi Jing-feng , Li Bo-an
Published: September 2024

To explore the influence of storage temperature and time on the stability of different concentrations of hepatitis C virus nucleic acid (HCV RNA) samples and to provide data reference for laboratory quality control. Serum samples of 10 patients with HCV RNA detection quantitation of 10
6
–10
8
IU/mL were collected. The samples of each patient were diluted into three concentrations: high, medium, and low. Then the samples of each concentration were divided into 21, which were divided into three groups according to the storage conditions of −20°C, 4°C, and 25°C, with seven samples in each group. The samples were selected from each group for quantitative detection of HCV RNA on day 0, day 1, day 3, day 5, day 7, day 14, and day 30. The results of each concentration and storage temperature sample remained stable within 5 days. Based on the mixed-effect linear model, the main effects of temperature, time, and concentration were statistically significant (
P
< 0.01). There was an interaction effect between concentration and time (
P
= 0.0448), and there was also an interaction effect between temperature and time (
P
< 0.01). There was no interaction effect between concentration and temperature (
P
= 0.11) or between concentration, temperature, and time (
P
= 0.90). The results of serum samples with different concentrations of the HCV RNA remained stable within 5 days. The lower the initial concentration of HCV RNA serum sample, the worse the stability; the higher the storage temperature, the worse the stability. If conditions permit, the laboratory should store such samples at −20°C.

IMPORTANCE

Previously, there were few reports about the influence of different concentrations of sample nucleic acid on the stability of samples at various temperatures and times in various literatures. Therefore, it is necessary to analyze the influence of concentration factors on the stability of samples and test results at different storage times and temperatures. This study took the concentration of hepatitis C virus nucleic acid as the research object to further understand the stability of hepatitis C virus nucleic acid test samples under various storage conditions, to provide data reference for the treatment of hepatitis C virus nucleic acid and RNA test samples before clinical laboratory test, and provide guidance and help for the improvement of laboratory quality control.
Radiometric dating (40Ar/39Ar and 14C), compositions, and erupted volumes of volcanoes of the Valle de Santiago area (Michoacán-Guanajuato Volcanic Field, Mexico)
Authors: Rangel-Granados Elizabeth , Siebe Claus , Suárez-Jiménez Juan Enrique , Schliz-Antequera Mélida Pilar , Reyes-Guzmán Nanci , Guilbaud Marie-Noëlle , Salinas Sergio , Miggins Daniel Paul
Published: September 2024

The Valle de Santiago (VS) area is located in the Michoacán-Guanajuato Volcanic Field (MGVF), within the Trans-Mexican Volcanic Belt (TMVB). By geological mapping of an ~2800 km2 quadrangle, 40Ar/39Ar and radiocarbon dating, morphometry, and whole-rock chemical and petrographic analyses of the volcanic products, we established the stratigraphy and eruptive history of the VS area. A total of 118 volcanic landforms was identified, including 61 scoria/spatter cones, 21 phreatomagmatic volcanoes, 20 medium-sized shield volcanoes, eight lava domes, and eight fissure-fed lava flows and plateaus. Volcanic activity in the VS area began ca. 8 Ma, persisting until the late Pleistocene, ca. 11 ka. During the Miocene to middle Pleistocene, volcanism was distributed throughout the VS area, and was predominantly effusive, giving rise to voluminous medium-sized shield volcanoes (15–47 km3). In the late Pleistocene, phreatomagmatic eruptions dominated the western sector of VS along an NNW-SSE–oriented strip. This phreatomagmatism was facilitated by fractured aquifers on the slopes of shield volcanoes (basaltic trachyandesitic and basaltic andesitic lava flows) and the humid climatic conditions that existed during the late Pleistocene, which guaranteed water-saturated conditions. Erupted products are mainly basaltic andesites/basaltic trachyandesites and andesites, and lesser basalts/trachybasalts, trachyandesites, and rhyolites. Their chemical affinity also shifted over time, transitioning from solely sub-alkaline to sub-alkaline and alkaline by the late Pleistocene. The VS area holds one of the largest phreatomagmatic clusters in the TMVB, offering an excellent opportunity to study the conditions favoring phreatomagmatism and providing records of intense volcanic activity during the Plio-Pleistocene in the MGVF.
ICON 2023: International Scientific Tendinopathy Symposium Consensus – the core outcome set for Achilles tendinopathy (COS-AT) using a systematic review and a Delphi study of professional participants and patients
Authors: de Vos Robert-Jan , Gravare Silbernagel Karin , Malliaras Peter , Visser Tjerk Sleeswijk , Alfredson Hakan , Akker-Scheek Inge van den , van Ark Mathijs , Brorsson Annelie , Chimenti Ruth , Docking Sean , Eliasson Pernilla , Farnqvist Kenneth , Haleem Zubair , Hanlon Shawn L , Kaux Jean-Francois , Kearney Rebecca Samantha , Kirwan Paul D , Kulig Kornelia , Kumar Bhavesh , Lewis Trevor , Longo Umile Giuseppe , Lui Tun Hing , Maffulli Nicola , Mallows Adrian James , Masci Lorenzo , McGonagle Dennis , Morrissey Dylan , Murphy Myles Calder , Newsham-West Richard , Nilsson-Helander Katarina Maria , Norris Richard , Oliva Francesco , O’Neill Seth , Peers Koen , Rio Ebonie Kendra , Sancho Igor , Scott Alex , Seymore Kayla D , Soh Sze-Ee , Vallance Patrick , Verhaar Jan A N , van der Vlist Arco C , Weir Adam , Zellers Jennifer Ann , Vicenzino Bill
Published: September 2024

To develop a core outcome set for Achilles tendinopathy (COS-AT) for use in clinical trials we performed a five-step process including (1) a systematic review of available outcome measurement instruments, (2) an online survey on truth and feasibility of the available measurement instruments, (3) an assessment of the methodological quality of the selected outcome measurement instruments, (4) an online survey on the outcome measurement instruments as COS and (5) a consensus in-person meeting. Both surveys were completed by healthcare professionals and patients. The Outcome Measures in Rheumatology guidelines with a 70% threshold for consensus were followed. We identified 233 different outcome measurement instruments from 307 included studies; 177 were mapped within the International Scientific Tendinopathy Symposium Consensus core domains. 31 participants (12 patients) completed the first online survey (response rate 94%). 22/177 (12%) outcome measurement instruments were deemed truthful and feasible and their measurement properties were evaluated. 29 participants (12 patients) completed the second online survey (response rate 88%) and three outcome measurement instruments were endorsed: the Victorian Institute of Sports Assessment-Achilles questionnaire, the single-leg heel rise test and evaluating pain after activity using a Visual Analogue Scale (VAS, 0–10). 12 participants (1 patient) attended the final consensus meeting, and 1 additional outcome measurement instrument was endorsed: evaluating pain during activity/loading using a VAS (0–10). It is recommended that the identified COS-AT will be used in future clinical trials evaluating the effectiveness of an intervention. This will facilitate comparing outcomes of intervention strategies, data pooling and further progression of knowledge about AT. As COS-AT is implemented, further evidence on measurement properties of included measures and new outcome measurement instruments should lead to its review and refinement.
Assessing the potential responses of 10 important fisheries species to a changing climate with machine learning and observational data across the province of Québec
Authors: Rodríguez Marco A. , Lemaire Marine , Fugère Vincent , Barrette Marie-France , Gagné Stéphanie , Leclerc Véronique , Morissette Olivier , Pouliot Rémy , St-Pierre Annick , Turgeon Katrine , Velghe Katherine , Guay Jean-Christophe , Beisner Beatrix E.
Published: September 2024

Models are needed to predict changes in game fish abundances with respect to climatic factors undergoing change, but such models are often limited by data availability and the capacity of statistical methods to fit challenging ecological datasets. We use current methods in machine learning to describe the responses of 10 fish species to climatic factors across Québec. We assembled a new province-wide, synthetic dataset of fish catches spanning almost 50 years and 6000 sites. Extreme Gradient Boosting (XGBoost) models revealed that climatic factors are more important predictors of trends in game fish catches than nuisance factors (sampling gear, time), lending support to collating other heterogeneous datasets for analyses. Mean annual temperature and precipitation were the most important drivers of species catches. Fish thermal preference guilds predicted primarily species responses to temperature, suggesting that warmer and wetter climates may not favour the same species. Despite the challenging nature of these datasets, XGBoost models provided excellent fit, predictive capacity, and interpretability, thereby illustrating that large, heterogeneous datasets can be used to inform freshwater fisheries management in a changing climate.
Dark matter phenomenology in 2HDMS in light of the 95 GeV excess
Authors: Dutta Juhi , Lahiri Jayita , Li Cheng , Moortgat-Pick Gudrid , Farah Tabira Sheikh , Ziegler Julia Anabell
Published: September 2024

The Two Higgs Doublet model extended with a complex scalar singlet (2HDMS) is a well-motivated Beyond Standard Model candidate addressing several open problems of nature. In this work, we focus on the dark matter (DM) phenomenology of the complex scalar singlet where the real part of the complex scalar obtains a vacuum expectation value. The model is characterized by an enlarged Higgs spectrum comprising six physical Higgs bosons and a pseudoscalar DM candidate. We address the impact of accommodating the 95 GeV excess on the 2HDMS parameter space and DM observables after including all theoretical and experimental constraints. Finally, we look into the prospects of this scenario at HL-LHC and future lepton colliders for a representative benchmark.
Searching for beyond the Standard Model physics using the improved description of 100Mo $$2\nu \beta \beta $$ decay spectral shape with CUPID-Mo
Authors: Augier C. , Barabash A. S. , Bellini F. , Benato G. , Beretta M. , Bergé L. , Billard J. , Borovlev Yu. A. , Cardani L. , Casali N. , Cazes A. , Celi E. , Chapellier M. , Chiesa D. , Dafinei I. , Danevich F. A. , De Jesus M. , Dixon T. , Dumoulin L. , Eitel K. , Ferri F. , Fujikawa B. K. , Gascon J. , Gironi L. , Giuliani A. , Grigorieva V. D. , Gros M. , Helis D. L. , Huang H. Z. , Huang R. , Imbert L. , Juillard A. , Khalife H. , Kleifges M. , Kobychev V. V. , Kolomensky Yu. G. , Konovalov S. I. , Kotila J. , Loaiza P. , Ma L. , Makarov E. P. , de Marcillac P. , Mariam R. , Marini L. , Marnieros S. , Navick X. F. , Nones C. , Norman E. B. , Olivieri E. , Ouellet J. L. , Pagnanini L. , Pattavina L. , Paul B. , Pavan M. , Peng H. , Pessina G. , Pirro S. , Poda D. V. , Polischuk O. G. , Pozzi S. , Previtali E. , Redon Th. , Rojas A. , Rozov S. , Sanglard V. , Scarpaci J. A. , Schmidt B. , Shen Y. , Shlegel V. N. , Šimkovic F. , Singh V. , Tomei C. , Tretyak V. I. , Umatov V. I. , Vagneron L. , Velázquez M. , Ware B. , Welliver B. , Winslow L. , Xue M. , Yakushev E. , Zarytskyy M. , Zolotarova A. S.
Published: September 2024

The current experiments searching for neutrinoless double-$$\beta $$
β
($$0\nu \beta \beta $$

0
ν
β
β

) decay also collect large statistics of Standard Model allowed two-neutrino double-$$\beta $$
β
($$2\nu \beta \beta $$

2
ν
β
β

) decay events. These can be used to search for Beyond Standard Model (BSM) physics via $$2\nu \beta \beta $$

2
ν
β
β

decay spectral distortions. 100Mo has a natural advantage due to its relatively short half-life, allowing higher $$2\nu \beta \beta $$

2
ν
β
β

decay statistics at equal exposures compared to the other isotopes. We demonstrate the potential of the dual read-out bolometric technique exploiting a 100Mo exposure of 1.47 kg $$\times $$
×
 years, acquired in the CUPID-Mo experiment at the Modane underground laboratory (France). We set limits on $$0\nu \beta \beta $$

0
ν
β
β

decays with the emission of one or more Majorons, on $$2\nu \beta \beta $$

2
ν
β
β

decay with Lorentz violation, and $$2\nu \beta \beta $$

2
ν
β
β

decay with a sterile neutrino emission. In this analysis, we investigate the systematic uncertainty induced by modeling the $$2\nu \beta \beta $$

2
ν
β
β

decay spectral shape parameterized through an improved model, an effect never considered before. This work motivates searches for BSM processes in the upcoming CUPID experiment, which will collect the largest amount of $$2\nu \beta \beta $$

2
ν
β
β

decay events among the next-generation experiments.
Heat kernel coefficients on Kähler manifolds
Authors: Liu Kefeng , Xu Hao
Published: September 2024

Polterovich proved a remarkable closed formula for heat kernel coefficients of the Laplace operator on compact Riemannian manifolds involving powers of Laplacians acting on the distance function. In the case of Kähler manifolds, we prove a combinatorial formula for powers of the complex Laplacian and use it to derive an explicit graph-theoretic formula for the numerics in heat coefficients as a linear combination of metric jets based on Polterovich’s formula.
Modeling and analysis of heterogeneous traffic flow with mixed regular and connected human-driven vehicles considering driver stochasticity
Authors: Luo Ying , Chen Yanyan , Lu Kaiming , Zhang Jian , Wang Tao , Yi Zhiyan
Published: September 2024

This paper presents a novel microscopic modeling framework to explore the impact of driver stochasticity and other related factors on heterogeneous traffic flows, consisting of both regular human-driven vehicles (RHDVs) and connected human-driven vehicles (CHDVs). We apply the stochastic optimal velocity car-following model for RHDVs, while an extended version of the stochastic continuous car-following model, taking into account optimal velocity guidance and driver compliance, is devised for CHDVs. The stability of CHDV car-following model is examined theoretically and numerically. Simulation experiments are conducted to analyze the stochastic heterogeneous traffic flow properties (i.e. stability and safety) with the proposed microscopic modeling framework under diverse parameter settings including CHDV penetration rate, driver compliance, and driver stochasticity. Results show that traffic flow stability and safety improve with the increase in CHDV penetration rate and driver compliance but deteriorate as the driver’s stochasticity strength increases. CHDVs significantly enhance traffic stability when the CHDV penetration rate or driver compliance exceeds a certain threshold, typically ranging between 0.5 and 0.7. Additionally, there is an interaction between driver stochasticity and CHDV penetration rate in their effect on traffic flow stability, where the contribution of stochasticity to traffic oscillations first increases and then decreases as the penetration rate rises. When the penetration rate is between 0 and 0.4, the traffic risk in emergency situations can be significantly reduced as the penetration rate increases. These findings may guide the management and control strategies of heterogeneous traffic flow.
A novel high applicability link prediction based on biased random walks
Authors: Li Cong , Cao Yuhan , Zhao Ying , Liao Xingxing , Wang Zilong , Zhang Meng , Tao Jian
Published: September 2024

Complex systems are prevalent in nature, and link prediction is crucial for analyzing these systems. This method has gained attention for its ability to uncover various irregular movements with underlying similarities. While individual particle behavior is unpredictable, the collective behavior of large groups can be forecasted more accurately. The variability at lower scales vs universal similarities at higher scales is often overlooked. To address this, we investigate the random walk process on directed networks at a global scale. We propose an improved link prediction method using biased random walks to enhance accuracy and applicability. We first define out-degree neighbors as valid transmission options to prevent conflicts with in-degree paths. We then analyze how out-degrees and in-degrees affect particle transition probabilities, guiding particles toward high out-degrees and low in-degrees for a sustainable process. Finally, we use particle stabilization probabilities at different nodes as a similarity measure for predicting potential connections. Our method improves prediction precision and practicality, as validated by experiments on nine real-world networks, showing significant gains in accuracy and AUC scores.
Analysis of the three possible event horizons of anti-de Sitter space–time in the Klein–Gordon equation
Authors: de Oliveira M. D. , Schmidt Alexandre G. M.
Published: September 2024

In this paper, we calculate exactly the solution of Klein–Gordon equation in anti-de Sitter space–time. Due to spherical symmetry, the angular wave functions are given by spherical harmonics. The radial wave functions are given by local Heun functions. We analyze the behavior of the radial wave function in regions near three possible event horizon positions [Formula: see text] and investigate the decay rate, Hawking radiation and Hawking temperature for these three cases. Comparing the results, we verify that if the decay rate and Hawking radiation are greater, then the closer the event horizon is to the singularity of the black hole. Finally, we analyze the special case of a small black hole limit.
Review of Hyperspectral Image Classification Based on Deep Learning
Authors: Liu Yujuan , Hao Aoxing , Liu Yanda , Liu Chunyu , Zhang Zhiyong , Cao Yiming
Published: September 2024

Hyperspectral Image (HSI) with its high resolution spatial and spectral information, has important applications in military, aerospace and civil applications. The classification methods have become the focus of the field as a significant research aspect of hyperspectral remote monitor engineering for earth reflexion. Because of its high dimensional nature, high relation between bands and spectral variety, traditional classification methods are difficult to achieve high precision and accuracy which limits the development of HSI classification technology. In the past years, with the fast recrudesce of deep learning engineering, its powerful feature extraction ability can remarkably ameliorate the accuracy of HSI classification, HSI classification on account of deep learning has become a feasibility study hotspot. In this paper, the methods of HSI classification on account of deep learning are reviewed. First, the research background of HSI classification is introduced and the deep neural network models which are expensively used in the field of HSI classification are summarized. On this basis, some HSI classification methods on account of deep learning are introduced in detail. Finally, the breakthrough aspects of deep learning in the map of HSI classification are summarized at the current stage and the future research direction is prospected.
Detection of Novel Classes in Dynamic Data Streams
Authors: Nagendhiran Nalini , Kuppusamy Lakshmanan
Published: September 2024

Every second, a huge volume of multi-dimensional data is generated in fields such as Social Networking, Industrial Internet of Things, Stock market and E-commerce applications. Knowledge and pattern extraction are a challenging task in the evolving nature of data stream. Major issues are (i) ‘concept drift’ occurs as a result of pattern changes in the data distribution and (ii) ‘concept evolution’ occurs when a new class evolves in the data stream. These issues degrade the performance of learning models. In this paper, we focus on detection of concept evolution and enhance the performance of classifiers. For this, we propose a new model to identify novel classes, namely, Detection of Novel Classes (DNC). The proposed method adopts long short term memory to continuously observe the streaming data in order to detect emerging classes. The continuous monitoring allows the model to distinguish between existing classes and the novel classes which save time and memory. Also, the proposed method is demonstrated for identifying more than one novel class. The experiments are performed over seven different datasets. The results confirm the efficiency is increased ranging from 6% to 34% by the proposed method in identifying new concepts in the evolving data stream than the existing methods available in the literature.
Advancing Incremental Few-Shot Video Action Recognition with Cluster Compression and Generative Separation
Authors: Qin Yanfei , Chu Renxin , Liu Baolin
Published: September 2024

Few-Shot Class Incremental Learning (FSCIL) is a trending topic in deep learning, addressing the need for models to incrementally learn novel classes, particularly in real-world scenarios where continuously emerging classes come with limited labeled samples. However, the majority of FSCIL research has been dedicated to image classification and object recognition tasks, with limited attention given to video action classification. In this paper, we present a new Cluster Compression and Generative Separation (CCGS) method for Incremental Few-Shot Video Action Recognition (iFSVAR), which introduces contrastive learning to boost the degree of class separation in the base session. Simultaneously, it creates numerous fine-grained classes with diverse semantics, effectively filling the unallocated representation space. Experimental results on UCF101, Kinetics, and Something-Something-V2[Formula: see text]demonstrate the effectiveness of the framework.
Lightweight and Efficient Wheat Spike Detection for Small Targets
Authors: Wang Bo , Li Yawen , Zhang Jun , Huang Liqiong
Published: September 2024

Wheat spike detection is a crucial component of wheat yield prediction. In this study, n lightweight and efficient wheat spike detection model is proposed. The model employs a novel Wheat Spike Net Block (WSNB) within a lightweight network architecture, integrating Depth-Wise Convolution (DW-Conv) and Efficient Window Multi-Head Self-Attention (EW-MHSA) to rapidly process images and accurately identify wheat spikes, even under compact small target conditions. The model is equipped with four detection heads to effectively handle targets of varying scales and incorporates the innovative EMF-IOU loss function for refined bounding box estimation. Tested on a self-constructed Shangluo winter wheat dataset, the model achieves a detection speed of 96.1 FPS on NVIDIA Tesla V100 and mAP@0.5 of 95.3%, surpassing YOLOv5, EfficientV2, YOlOX,transformer, and MobileVIt3 in terms of accuracy and efficiency. The model’s performance across diverse hardware platforms highlights its potential for practical implementation in real-time wheat yield estimation and precision agriculture.
Reliable Synchronous and Asynchronous Counter Design in QCA
Authors: Saketha Y. S. S. Gowri Sai , Alagarsamy Aravindhan , Raj Marshal , Cardarilli Gian Carlo , Ko Seok-Bum
Published: September 2024

Due to rapid growth in the integrated circuit (IC) industry, the demand for compact digital system design is high. However, the continued technology reductions made the feasibility of further scaling down transistor size more challenging. In response to the growing demand for ultra-compact IC designs, the revolutionary quantum-dot cellular automata (QCA) technology has emerged as a promising solution. In a digital era, the counters are widely adopted in the peer-to-peer process flow to establish a mechanism for generating unique values for each identifier/number. In this work, a unique synchronous and asynchronous counters architecture is proposed with a reliable D and T flip-flop design. The proposed QCA architecture is implemented and validated with the QCA designer tool. Furthermore, in QCA technology, unreliable QCA designs can lead to frequent errors and malfunctions in the implemented logic. To overcome this challenge, the proposed design prioritizes cell placement (the relative positions of QCA cells) to make the circuit more robust. As a result, the circuit can still produce the expected functionality even if some QCA cells malfunction. Hence, to ensure the reliability of the proposed QCA architecture, the missing cell defect analysis is carried out in comparison with existing state-of-the-art designs. Based on comparison results, the unique designs like the proposed multiplexer, D flip-flop and T flip-flop design exhibit success rates of 67.28, 77.04 and 85.15%, respectively. The experimental results demonstrate that the proposed counter-architecture outperforms existing architectures.
Analytic continuation of differential cross-sections as a way to determine asymptotic normalization coefficients. Application to the 16O(d,p)17O reaction
Authors: Blokhintsev L. D. , Savin D. A.
Published: September 2024

Asymptotic normalization coefficients (ANC) are important nuclear characteristics. This paper discusses a method for determining ANC values from experimental data on differential cross-sections of nuclear transfer reactions. The method is based on the use of the analytic continuation of these cross-sections to the pole point of the reaction amplitude with respect to the variable [Formula: see text], where [Formula: see text] is the center-of-mass scattering angle. The method under consideration is used to determine the ANC for the channel [Formula: see text]O(1/2[Formula: see text]; 0.871[Formula: see text]MeV) [Formula: see text]O(0[Formula: see text]; 0[Formula: see text]MeV) [Formula: see text] from the data on the [Formula: see text]O(0[Formula: see text]; 0[Formula: see text]MeV)[Formula: see text]O (1/2[Formula: see text]; 0.871[Formula: see text]MeV) reaction. When determining the ANC, the corrections caused by the Coulomb interaction in the initial, final and intermediate states of the reaction were taken into account. It is shown that these corrections have a great impact on the extracted ANC value.
THE FRACTAL MODIFICATION OF THE ROSENAU–BURGERS EQUATION AND ITS FRACTAL VARIATIONAL PRINCIPLE
Authors: XU PENG , LONG FU-TANG , SHAN CHUN , LI GENG , SHI FENG , WANG KANG-JIA
Published: September 2024

A new fractal Rosenau–Burgers equation with He’s fractal derivative is proposed in this work. Exerting the semi-inverse method, two different kinds of the generalized fractal variational principles (GFVPs) of the fractal Rosenau–Burgers equation are constructed. The GFVPs extracted in this paper are expected to bring some new inspiration for the study and application of the variational method in the fractal space.
SPHERICAL GRAPHENE FILM GROWN ON CARBIDE FOR SENSOR MATRIX
Authors: HUANG GUANGDONG , JIA YUQIAO
Published: September 2024

Graphene has amazing applications for sensors due to its excellent performances like high strength and good conductivity, but the transfer issue is in the way of its application perspective. Direct growth of spherical graphene films (SGFs) on cemented carbide may offer a good avenue for various applications in sensor technology, especially for electrochemical sensors. Four common methods for graphene preparation are chemical stripping, chemical vapor deposition (CVD), metal catalysis, and laser fabrication; and subject to transfer issues during usage. In order to overcome this limitation, the fabrication of in-situ growth of SGFs on carbide is proposed as a solution for constructing sensor matrices. This review explores various in-situ SGFs and their potential applications in sensors. The findings presented here shed light on transfer-free graphene with controllable structures that can serve as excellent candidates for sensor matrices.
ASSOCIATION OF THE FECAL MICROBIOME WITH IDIOPATHIC SCOLIOSIS IN ADOLESCENTS
Authors: Smirnova Yuliya D. , Burakova Inna Yu. , Gryaznova Mariya V. , Morozova Polina D. , Togidnyy Alexander A. , Kryukova Olga N. , Korneeva Olga S. , Syromyatnikov Mikhail Yu.
Published: September 2024

Background: Adolescent idiopathic scoliosis is a frequent spinal disorder that manifests itself in varying degrees of severity. However, the etiology of this disease is still unclear. Lately, 16S rRNA sequencing has been increasingly used as a common method to analyze the composition of the faecal microbiota in different diseases. This increased interest has led to investigations into the bacterial composition of people with scoliosis.

Methods: We examined the V3 region of the 16S rRNA gene in children diagnosed with adolescent idiopathic scoliosis using NGS sequencing.

Results: It was established that in the fecal microbiome of a group of children with scoliosis there is an increase in the number of bacterial genera Erysipelotrichaceae UCG-003, Eubacterium fissicatena, Paeniclostridium, Monoglobus, Blautia and Christensenellaceae R-7, as well as a decrease in the number of genera Dialister, Pseudobutyrivibrio, Prevotella and Escherichia-Shigella. Our study also found a correlation between bacteria and the degree of scoliosis.

Conclusion: High abundance of Bilophila, Oscillospira and Paludicola was associated with more severe forms of scoliosis, and the prevalence of Clostridium sensu stricto 1 and Dialister was associated with decreased disease severity. The results of our study may indicate new bacterial markers associated with the development and severity of scoliosis in children.