bluuebunny/crossref_metadata_2025 huggingface dataset:
Axially symmetric solutions in Ricci-inverse modified gravity
Authors: Ahmed F. , de Souza J. C. R. , Santos A. F.
Published: September 2024

We investigate a family of axial symmetry solution constructed in general relativity (GR) within the framework of Ricci-inverse (RI) gravity theory. In GR, these solutions admitted closed time-like curves at an instant of time from an initial spacelike hypersurface in a causally well-behaved manner, thus, violates the causality condition. Our aim is to examine these axial symmetry solutions within the context of Ricci-inverse gravity theory to determine whether closed time-like curves still appear in this new gravity theory. We consider two Classes of RI-gravity models: (i) Class-II models defined by a function $$f=f({\mathcal {R}}, A^{\mu \nu }\,A_{\mu \nu })$$

f
=
f
(
R
,

A

μ
ν

A

μ
ν

)

gravity and (ii) Class-III models defined by $$f=f({\mathcal {R}},{\mathcal {A}}, A^{\mu \nu }\,A_{\mu \nu })$$

f
=
f
(
R
,
A
,

A

μ
ν

A

μ
ν

)

, where $$A^{\mu \nu }$$

A

μ
ν

is the anti-curvature tensor, $${\mathcal {A}}=g_{\mu \nu }\,A^{\mu \nu }$$

A
=

g

μ
ν

A

μ
ν

as its scalar, and $$R^{\mu \nu }$$

R

μ
ν

is the Ricci tensor. We are able solved the modified field equations considering these axial symmetry solutions as background in RI-gravity with null radiation as the matter content and the cosmological constant. This confirms that the chosen family of axial symmetry solutions are valid solutions in RI-gravity theory and, consequently, closed time-like curves is still form, analogous to their formation in GR.
A new perspective on gravitational collapse: a comprehensive analysis using $$\Theta $$ parametrization
Authors: Kumar Rajesh , Jaiswal Annu , Srivastava Sudhir Kumar , Pacif Shibesh Kumar Jas
Published: September 2024

In this article, we have studied some new facets of gravitational collapse, beyond conventional notions of black holes, and naked singularities. The present work is focused on the unresolved problems of theoretical physics concerning the final fate of the gravitational collapse of any massive star. By generalizing the foundational work of Oppenheimer and Snyder (Phys Rev 56:455, 1939), we have considered the homogeneous gravitational collapsing system filled with perfect fluid distributions (devoid of dust fluid) within the framework of GR theory. The article investigates a homogeneous gravitational collapsing system using a parametrization scheme for the expansion-scalar $$(\Theta )$$

(
Θ
)

and determining the exact solution of field equations. Further, by employing the known Darmois–Israel boundary condition, we have discussed the solution in more detail, and the model’s physical and geometrical quantities are obtained in terms of stellar mass (M), making it crucial for astrophysical applications. To assess the astrophysical viability of our model, we consider a massive star-$$\beta $$
β
Canis Majoris and throughout this study we have presented a detailed numerical and graphical analysis of our model. The analysis of singularities in the models is conducted through the examination of the apparent horizon. Our findings demonstrate that the star continues to collapse indefinitely in co-moving time, ultimately leading to a space-time singularity-this represents a case of continuous gravitational collapse. We propose that this scenario describes an “Eternal Collapsing Object,” which may be treated as a “mathematical black hole without any finite equilibrium state.” Our presented models undergo rigorous physical tests to ensure their regularity, causality, and stability, and to satisfy the necessary energy conditions.
Estimation of the Hubble constant using Gaussian process regression and viable alternatives
Authors: Zammit Samuel , Suda David , Sammut Fiona , Said Jackson Levi
Published: September 2024

A well-known problem in cosmology is the ‘Hubble tension’ problem, i.e. different estimates for the Hubble constant $$H_0$$

H
0

are not concordant with each other. This work investigates different statistical methods for estimating this value using cosmic chronometer, type Ia supernova and baryonic acoustic data. We start by making use of methods already established in the literature for this purpose, namely Gaussian process regression and Markov chain Monte Carlo (MCMC) methods based on the concordance $$\varLambda $$
Λ
CDM model. We also consider two novel approaches; the first makes use of non-parametric MCMC inference on the hyperparameters of a Gaussian process kernel, independently of any cosmological model. The second approach is Student’s t-process regression, which is a generalised version of Gaussian process regression that makes use of the multivariate Student’s t-distribution instead of the multivariate Gaussian distribution. We also consider variants of these two methods which account for heteroscedasticity within the data. A comparison of the different approaches is made. In particular, the model-independent techniques investigated mostly agree with predictions based on the $$\varLambda $$
Λ
CDM model. Moreover, Gaussian process regression is highly sensitive to the prior specification, while Student’s t-process regression and the heteroscedastic variants of both methods are more robust to this. Student’s t-process regression and both heteroscedastic models suggest a lower value of the Hubble constant. Across all the estimates obtained for the Hubble constant within this work, the median value is $$\hat{H}_0^{med} = 68.85 \pm 1.67$$

H
^

0

med

=
68.85
±
1.67

km s$$^{-1}$$

-
1

Mpc$$^{-1}$$

-
1

.
Exploring the molecular scenario of X(4160)
Authors: Li Ruitian , He Dazhuang , Luo Xuan , Sun Hao
Published: September 2024

In this work, we investigate the decays of meson X(4160) in the molecular frame. By using an effective lagrangian approach, we calculate the widths of $$X(4160)\rightarrow J/\psi \phi $$

X
(
4160
)
→
J
/
ψ
ϕ

, $$D^*\bar{D}^*$$

D
∗

D

¯

∗

, $$D^*\bar{D}$$

D
∗

D

¯

and $$D\bar{D}$$

D

D

¯

through the triangle loop mechanism in the molecular scenario. Based on the compositeness condition, the coupling between X(4160) and the $$D_s^*\bar{D}_s^*$$

D
s
∗

D

¯

s
∗

molecular state is determined. The other coupling constants used are determined phenomenologically. The calculation of the decay widths shows that the $$D^*\bar{D}^*$$

D
∗

D

¯

∗

decay mode has a larger branching ratio. These predictions can be seen as a test for the charmonium assignment of X(4160).
Circular motion and QPOs near black holes in Kalb–Ramond gravity
Authors: Jumaniyozov Shokhzod , Khan Saeed Ullah , Rayimbaev Javlon , Abdujabbarov Ahmadjon , Urinbaev Sharofiddin , Murodov Sardor
Published: September 2024

General relativity (GR) theory modifications include different scalar, vector, and tensor fields with non-minimal gravitational coupling. Kalb–Ramond (KR) gravity is a modified theory formulated based on the presence of the bosonic field. One astrophysical way to test gravity is by studying the motion of test particles in the spacetime of black holes (BHs) using observational data. In the present work, we aimed to test KR gravity through theoretical studies of epicyclic frequencies of particle oscillations using quasi-periodic oscillation (QPO) frequency data from microquasars. First, we derive equations of motion and analyze the effective potential for circular orbits. Also, we studied the energy and angular momentum of particles corresponding to circular orbits. In addition, we analyze the stability of circular orbits. It is shown that the radius of the innermost stable circular orbits is inversely proportional to the KR parameter. We are also interested in how the energy and angular momentum of test particles at ISCO behave around the KR BHs. We found that the Keplerian frequency for the test particles in KR gravity is the same as that in GR. Finally, we study the QPOs by applying epicyclic oscillations in the relativistic precession (RP), warped disc (WD), and epicyclic resonance (ER) models. We also analyze QPO orbits in the resonance cases of upper and lower frequencies 3:2, 4:3, and 5:4 in the QPO as mentioned above models. We obtain constraints on the KR gravity parameter and BH mass using a Monte Carlo Markov Chain simulation in the multidimensional parameter space for the microquasars GRO J1655-40 & XTE J1550-564, M82 X-1, and Sgr A*.
Classifier surrogates: sharing AI-based searches with the world
Authors: Bieringer Sebastian , Kasieczka Gregor , Kieseler Jan , Trabs Mathias
Published: September 2024

In recent years, neural network-based classification has been used to improve data analysis at collider experiments. While this strategy proves to be hugely successful, the underlying models are not commonly shared with the public and rely on experiment-internal data as well as full detector simulations. We show a concrete implementation of a newly proposed strategy, so-called Classifier Surrogates, to be trained inside the experiments, that only utilise publicly accessible features and truth information. These surrogates approximate the original classifier distribution, and can be shared with the public. Subsequently, such a model can be evaluated by sampling the classification output from high-level information without requiring a sophisticated detector simulation. Technically, we show that continuous normalizing flows are a suitable generative architecture that can be efficiently trained to sample classification results using conditional flow matching. We further demonstrate that these models can be easily extended by Bayesian uncertainties to indicate their degree of validity when confronted with unknown inputs by the user. For a concrete example of tagging jets from hadronically decaying top quarks, we demonstrate the application of flows in combination with uncertainty estimation through either inference of a mean-field Gaussian weight posterior, or Monte Carlo sampling network weights.
Reinforcement learning of biomimetic navigation: a model problem for sperm chemotaxis
Authors: Mohamed Omar , Tsang Alan C. H.
Published: September 2024

Motile biological cells can respond to local environmental cues and exhibit various navigation strategies to search for specific targets. These navigation strategies usually involve tuning of key biophysical parameters of the cells, such that the cells can modulate their trajectories to move in response to the detected signals. Here we introduce a reinforcement learning approach to modulate key biophysical parameters and realize navigation strategies reminiscent to those developed by biological cells. We present this approach using sperm chemotaxis toward an egg as a paradigm. By modulating the trajectory curvature of a sperm cell model, the navigation strategies informed by reinforcement learning are capable to resemble sperm chemotaxis observed in experiments. This approach provides an alternative method to capture biologically relevant navigation strategies, which may inform the necessary parameter modulations required for obtaining specific navigation strategies and guide the design of biomimetic micro-robotics.

Graphical abstract
Local charge radius relations based on neutron shell effects
Authors: Jiao Bao-Bao , Fan Ping-Ping , Ling Qiang , Li Tao , Liu Xiao-Liang , Meng Xiang-Ting , Zhang Yan , Liu Yi-Bao
Published: September 2024

In this paper, we obtained the mean mass density parameter (MMDP) [Formula: see text] based on the nuclear mass AME2020 and nuclear charge radius CR2013 databases. On this basis, we study the dependence relationship between neutron number N and the two neighboring isotopes MMDP difference [Formula: see text], and then obtained the empirical formula for [Formula: see text]. By combining this empirical formula with the AME2020 and CR2013 databases, the root-mean-square deviation (RMSD) for 606 nuclear charge radii with [Formula: see text] 21 between the calculated and experimental values is 0.0046[Formula: see text]fm. Considering the odd–even staggering and isospin term correction, the study found that the RMSD is reduced to 0.0040[Formula: see text]fm. This work also uses Levenberg–Marquart (L-M) neural network approach to study the nuclear charge radius. The RMSD of nuclear charge radius is only 0.0030 fm, where the accuracy is increased by about 25%. Furthermore, the predicted values of nuclear charge radius obtained using this modified empirical formula and Neural Network model are competitive with the results of other models. These results indicate that nuclear charge radius relation and Neural Network model based on [Formula: see text] proposed in this work have a certain accuracy, simplicity and reliability.
Constraining neutron star properties and dark matter admixture with the NITR-I equation of state: Insights from observations and universal relations
Authors: Routaray Pinku , Das H. C. , Pattnaik Jeet Amrit , Kumar Bharat
Published: September 2024

A recent observational study has set a constraint on the maximum mass of neutron stars (NSs), specifically focusing on PSR J0952-0607 and the compact star remnant HESS J1731-347, particularly within the low-mass regime. In our recent study, Ref. 1 , we developed an energy density functional named NITR, which successfully produced the mass limit of the aforementioned pulsar but did not fully meet other observational constraints, such as those from NICER+XMM and GW170817. In this study, we introduce a new EDF named “NITR-I”, which not only reproduces the mass limit of PSR J0952-0607 but also aligns its canonical radius with NICER+XMM data, and its canonical dimensionless tidal deformability is consistent with the GW170817 event, thereby demonstrating the robustness of our model. The low-mass constraint associated with HESS J1731-347 suggests various possible compositions for the NS. The NITR-I model alone does not satisfy the HESS J1731-347 constraint; thus, we explore the possibility of incorporating dark matter (DM) inside the NS to meet this constraint. This approach proves successful when a specific value of Fermi momentum is considered. We also examine the impact of DM with varying Fermi momentum on different NS properties, such as tidal deformability and nonradial f-mode oscillation, using various relativistic mean-field (RMF) models. For the NITR-I EOS, the f-mode frequency is about 2.15[Formula: see text]kHz at 1.4 [Formula: see text] when [Formula: see text][Formula: see text]GeV, and it slightly increases to around 2.32[Formula: see text]kHz with [Formula: see text][Formula: see text]GeV. This increase in frequency due to DM suggests a possible reduction in tidal deformability, indicating that neutron stars with higher DM content are less susceptible to deformation by tidal forces which could be detectable in gravitational wave signals from neutron star mergers. Finally, we explore various universal relations (URs) for DM-admixed NSs, such as the relation between compactness and tidal deformability, the f-mode frequency and tidal deformability, and estimate the canonical values corresponding to both compactness and f-mode frequency using the GW170817 data.
Universal properties of truth
Authors: Łełyk Mateusz , Wcisło Bartosz
Published: September 2024

In this paper, we investigate abstract model-theoretic properties which hold for models in which a truth or satisfaction predicate for a sublanguage of the signature is definable. We analyze in which cases those properties in fact ensure the definability of the respective truth predicate. In some cases, we formulate different axiomatic theories which are indispensable for such properties to hold and we analyze the mutual definability relations between those theories.
Performance Evaluation of Inerter and Negative Stiffness-Based Dampers for Seismic-Induced Vibration Response Control of a Cable-Stayed Bridge: A Comparative Study
Authors: Zhang Xi , Wang Xinwei , Wang Zhihao , Li Yang
Published: September 2024

The excessive main girder displacement responses of the large-span cable-stayed bridges during seismic events may precipitate collisions between the main girder and the approach bridge. The viscous dampers (VDs) have been extensively employed in the seismic response control of long-span bridges, yet their effectiveness is limited. To augment the seismic-induced vibration control performance of the VD, inerter element, negative stiffness (NS) element, and spring element have been incorporated into the VD to achieve energy dissipation capacity enhancement. The equations of motion for the simplified cable-stayed bridge-damper systems are established under stochastic seismic excitation, and the design parameters of inerter and NS-based damper are optimized by using the genetic algorithm. The seismic control performance of the VD and five types of dampers are systematically compared, demonstrating that these dampers can substantially enhance the main girder displacement mitigation performance in cable-stayed bridges. Owing to the NS characteristics attributes of the inerter element and NS element and the tuning effect of the spring element, the tuned viscous mass damper (TVMD) with NS achieves a 24.56% higher efficiency in control performance compared to the VD.
Understanding the Inherently Self-Adjusting Mechanism and Load Adaptability of the Mem-Damper
Authors: Zhang Xiao-Liang , Zhang Shu-Jia , Wang Feng-Li , Nie Jia-Mei
Published: September 2024

The tapered dashpot (damper) has been the earliest memristor found in the mechanical engineering domain, named mem-dashpot (mem-damper), since the missing memristor was postulated by Leon Chua. In this paper, a displacement-dependent viscous damper device with internal channels is investigated and recognized as a physical realization of the mem-damper by analyzing the mathematical and dynamic relationships of the device’s complementary port variables theoretically and experimentally. A vehicle suspension equipped with a mem-damper is taken as a carrier for presenting load adaptability of the mem-damper. An investigation reveals the inherently self-adjusting mechanism behind load adaptability from the viewpoint of energy storage, that is, a mem-damper with different initial displacement values can be equivalent to a semi-active damper performing an initial-position-dependent damping control strategy. Finally, the load adaptability of the mem-damper is demonstrated through both simulation and experiment of the suspension system with the mem-damper prototype. Due to such load adaptability, the suspension equipped with the mem-damper can offer more constant and smoother ride comfort than the one with the linear damper.
Semi-Active Vibration Control for Wind Turbines: A Variable Tuned Mass Damper Approach Utilizing 1st Modal and 3P Tuning
Authors: Bai Jiulin , Li Chenhui , Wang Qi , Huang Jiaxin , Wang Yu-Hang
Published: September 2024

Vibration in wind turbine towers poses a significant threat to the service life and structural integrity of wind turbines. Dampers have been identified as a pivotal strategy for alleviating such vibrations. Despite this, the dynamic behavior of large-scale offshore wind turbines is frequently swayed by wind shear, the tower shadow effect, and the Rotor-Nacelle Assembly (RNA) control system, typically manifesting as responses to the blade passing frequency (3P). To mitigate these vibrations, this study introduces a 3P tuning method for tuned mass dampers (TMDs), alongside a sophisticated design approach that targets optimal frequency and damping ratios. The integration of a semi-active variable-tuned mass damper (SA-V-TMD) offers a dual-mode control solution: The “3P tuning mode” adeptly manages vibrations across a spectrum of operating conditions, while the “1st modal frequency tuning mode” stabilizes the structure during parked states. Simulations substantiate the 3P tuning method’s enhanced efficacy over standard methods under operational conditions. Furthermore, the SA-V-TMD demonstrates superior effectiveness and stability in comparison to traditional TMDs, underscoring its potential as a preeminent solution in wind turbine vibration management.
EARLY DIAGNOSIS AND CLASSIFICATION OF LUNG CANCER DRIVEN BY MULTI-FEATURE DATA: A COMPARISON AND OPTIMIZATION OF THREE MACHINE LEARNING METHODS
Authors: LAN QI , WANG RENFENG , FAN HONG
Published: September 2024

The objective of this study was to construct a prediction model for early diagnosis and classification of lung cancer based on multi-dimensional clinical data. Three advanced machine learning models — Random Forest, Decision Tree, and Support Vector Machine (SVM) — were employed to predict lung cancer using features such as age, chronic disease history, and clinical symptoms. The models were optimized through various strategies to improve predictive performance. The results demonstrated that all three models achieved high accuracy and sensitivity in lung cancer prediction. Furthermore, a detailed analysis of feature importance identified key factors such as age and chronic disease history that significantly influenced prediction outcomes. Among the models, the SVM exhibited particularly strong performance, providing robust support for accurate lung cancer prediction. Future work will focus on integrating multimodal data and optimizing model architecture and hyperparameters to further enhance the predictive accuracy and clinical utility of the model, thereby contributing to the early diagnosis and treatment of lung cancer.
A Knowledge Graph Embedding-based Approach to Predict the Adverse Drug Reactions using a Convolutional Neural Network
Authors: Wu Juhua , Nie Ya , Liu Zheng Feng , Tao Lei , Zheng Wen
Published: September 2024

Our research is centred on drug knowledge discovery, involving the integration of drug knowledge graphs with machine learning techniques. To address the challenges of burdensome workload and inadequate classification accuracy associated with constructing individual models for each Adverse Drug Reaction (ADR), we developed and refined a Convolutional Neural Network (CNN) based on knowledge graph embedding (KGE) and deep learning methodologies. The outcomes of our study demonstrate that our proposed predictive model achieves remarkable precision and reliability, enabling comprehensive exploration of drug-reaction relationships. Our contributions introduce innovative models and techniques that drive the advancement of intelligent healthcare and demonstrate the scalability of data science applications in the medical domain.
Relation-theoretic-coupled fixed point theorems for rational-type contractions via C-class function with an application
Authors: Ali Shahbaz , Khan Qamrul Haque , Hossain Asik
Published: September 2024

In this paper, we discuss the relation theoretic fixed point results for rational type contractions by using [Formula: see text]-class functions. Also, we prove that the existence and uniqueness of coupled fixed point theorem under mixed monotone property and [Formula: see text]-class function. Moreover, we give some examples in support of our proved result. Finally, we give an application to find a solution to a nonlinear integral equation.
Optimal Path Planning Algorithm of Indoor AGV Enhanced with HHO and Sector-Wide Field DWA
Authors: Zhou Zhen , Song Yujie , Li Shuo
Published: September 2024

With an aim to solve the issue of dynamic obstacles and the global optimal path planning for indoor Automated Guided Vehicles (AGVs), this paper addressed an enhanced hybrid path planning method based on the improvement of Harris Hawk Optimization (HHO) and Dynamic Window Approach (DWA). The main contributions are given as follows. On the one hand, compared to the traditional HHO, the performances are improved in the following aspects. First, initializing the Harris Hawk population with a circle-tent chaotic map to enhance search capability. Second, balancing global and local searches with a segmented strategy to avoid local optima; Third, improving population survival with a hard-constraint mutation strategy. On the other hand, DWA is enhanced from the following three perspectives: a sector potential field is adopted for early obstacle avoidance and a smoother AGV trajectories; a dynamic weighting strategy is used to obtain a better escape local optima and enhance safety; a obstacle-free path attraction strategy is proposed to solve the problem of detours and accelerates the convergence speed. Finally, combined the enhanced HHO with DWA, Generalized Harris Hawks Optimization-Dynamic Window Approach (GHHO-DWA) algorithm addresses the issues of nonsmooth global paths and inadequate dynamic obstacle avoidance. Meanwhile, the effectiveness and practicality of GHHO-DWA algorithm are validated through MATLAB simulations and physical testing on the QBot2e platform.
Shared Ontologies: 4e Cognition and Montemayor’s Humanitarian AI
Authors: Zebrowski Robin L.
Published: September 2024

This short paper traces some convergences between the ontologies of mind and AI presented in Carlos Montemayor’s Precis for The Prospect of Humanitarian Artificial Intelligence and Enactivism, with a focus on autonomy, embeddedness, perspective, and social interaction. I argue that it is surprising that Montemayor does not engage with any of the traditional 4e ontologies here, especially enactivism, considering his strong reliance on biology and autonomy in carving up intelligence and consciousness.
Evasion Maneuver and Timing Strategy for UAVs Under Direct Force Control
Authors: Zhao Mengke , Shi Heng , Kuang Minchi , Zhu Jihong
Published: September 2024

Given the capabilities of modern high-performance missiles, efficient evasion maneuver strategies are crucial for enhancing UAV survivability. This paper addresses the integration of evasion strategies and maneuver timing for targeted UAVs. First, a three-dimensional engagement scenario is modeled using the relative motion mechanism. Subsequently, a fundamental evasion strategy focusing on large roll maneuvers and two-phase acceleration is developed. With the initiation timing of direct force control designated as the control variable, the formulation of a constrained optimization problem to maximize miss distance is fully articulated. While preserving the high fidelity of the established switching model, the feasible timing intervals and the optimal timing are determined through numerical optimization. Finally, simulation experiments are conducted focusing on omnidirectional attacks from the upper hemisphere. The results demonstrate that by implementing specific evasion maneuvers at optimal timing, the target successfully escapes the effective range of the proximity fuse, thus confirming the feasibility of the proposed evasion maneuver and timing strategy.
A new crinoid morphotaxon from the Silurian (Llandovery) of SW Scotland (Ayrshire)
Authors: Donovan Stephen K. , Hoare Gary , Clark Neil D. L. , Dixon Ben , Fearnhead Fiona E.
Published: September 2024

There is little known of the diversity of Silurian crinoids in Scotland. Rather than wait in hope for a new Lagerstätte, our knowledge of the fauna can be improved by recognizing imperfectly preserved specimens, such as disarticulated columnals.
Pentagonopentagonalis
(col.)
annulus
sp. nov. is here recorded from the Llandovery (Rhuddanian) Mulloch Hill Sandstone Formation of Ayrshire. It is known only from disarticulated columnals, most without counterpart, and rare pluricolumnals. The column is xenomorphic, and columnals can vary from pentagonal (probably proximal) to rounded or circular (more distal?), each with a moderately broad lumen that is similarly shaped. There is no areola and the articulation is radial symplectial. Pluricolumnals are heteromorphic, perhaps N3231323. This morphospecies is described to demonstrate something of the wealth of information and inference that may be gleaned from even the most unpromising material.
CoDe: Customizing Urban HD Map Deployment Strategy with Spatio-Temporal GPS Trace
Authors: Cao Xiaofeng , Guo Deke , Lyu Feng , Yang Peng , Zhang Weiming
Published: September 2024

In this article, we investigate the edge cache deployment for high definition (HD) urban map provisioning, which is an essential building block for future autonomous driving. Given a deployment budget, we first formulate a satisfied downloading request maximization (SDRM) problem to obtain the deployment locations and customized cache sizes. The SDRM problem is unsolvable directly as the urban transportation traffic is highly dynamic and future traffic conditions are unknown in advance. Based on data analytics of the vehicular GPS trace, we propose an architecture named
CoDe
, built on which we transform and address the SDRM problem. The reference implementation of
CoDe
is respectively developed based on the insights from two urban-scale carpool GPS traces. The novelty and contributions of
CoDe
lie in its three-layer design. Particularly, at data feeding layer, we make use of two urban 60-day GPS traces involving respectively 37,801 and 17,517 vehicles, to extract the analytics samples. At mobility characterization layer, we conduct extensive data analytics on traffic mobility in terms of their distribution, correlation, and variation, to mine the crucial traffic mobility patterns for strategy customization. At cache deployment layer, we propose the
K
-order subgraph for each block to record the moving statistics within its
K
-order neighborhood, and transform the SDRM problem accordingly. Then, the
R
oute we
I
ght ba
S
ed gr
E
edy (
RISE
) algorithm is devised for the problem, which can deliver the deployment decisions. Extensive data-driven experiments are carried out to demonstrate the superior performance of
CoDe
in terms of request hit ratio and caching resource utility.
PROV-IDEA: Supporting Interoperable Schema and Data Provenance within Database Evolution
Authors: Pérez Beatriz , Rubio Ángel Luis , Zapata María A.
Published: September 2024

Database evolution and data provenance are two closely related research fields. On the one hand, the registry (via provenance) of the schema evolution allows the maintenance of its version record. On the other hand, the origin of the data (i.e., its provenance) will always be affected by modifications (i.e., the evolution) in the schema on which they are based. Despite these interrelationships, there are few works in the literature that have proposed advances in that direction. In particular, to the best of our knowledge, there is no research that has resulted in a general and interoperable solution to the problem of managing database evolution using provenance. In this article, we present PROV-IDEA: a PROV-Interoperable Database Evolution Approach. This is a proposal that allows the simultaneous management of the provenance of schemas (of relational databases) and data, using the PROV standard as a way to guarantee interoperability. Furthermore, it is an adaptable and expandable approach (by using PROV templates), which allows a non-intrusive and seamless integration with existing applications, as well as different aspects of provenance information generation. These properties are demonstrated in the article by presenting a proof of concept built on top of a third-party relational database evolution tool.
Comparative Valuation Dynamics in Production Economies: Long-Run Uncertainty, Heterogeneity, and Market Frictions
Authors: Hansen Lars Peter , Khorrami Paymon , Tourre Fabrice
Published: September 2024

We compare and contrast production economies exposed to long-run uncertainty with investors that have possibly different preferences and/or access to financial markets. We study the macroeconomic and asset-pricing properties of these models, identify common features, and highlight areas where these models depart from each other. Our framework allows us to investigate more fully the impact of investor heterogeneity, capital heterogeneity, and fluctuations of the growth components to the capital evolution as they affect the dynamics of macroeconomic quantities and asset prices. In our comparisons, we employ an array of diagnostic tools to explore time variation and state dependencies in nonlinear environments.
200 mm Wafer Level Characterization at 2 K of Si/SiGe Field-Effect Transistors
Authors: Komericki Nikola David , Muster Pascal , Reichmann Felix , Huckemann Till , Kaufmann Daniel , Yamamoto Yuji , Lisker Marco , Langheinrich Wolfram , Schreiber Lars R , Bluhm Hendrik , Quay Ruediger
Published: September 2024

Si/SiGe has proven to be an excellent spin qubit platform, but industrial production of large-scale spin-qubit chips is missing. We use field effect transistors (FETs) to monitor and develop the quality of the fabrication process on 200 mm wafers at 2 K using a cryogenic wafer prober (CWP). This mass-characterization technique provides statistics on device performance. We observe variations in drain off current and gate threshold voltage of 213 FETs. These variations are related to bias voltage conditions during CWP cooldown, which differ from qubit chip cooldown. To address this, a new FET structure with an additional top gate is introduced, effectively suppressing unintentional charge accumulations. This eliminates drain off currents and improves homogeneity of FET characteristics at 2 K. Our results highlight significant impact of bias conditions during qubit chip cooldown, which, if not accounted for in the qubit chip design, can lead to incorrect conclusions when using CWP.
A platinum degradation reaction model for the high-speed computation in the integrated fuel cell system simulator and its validation by the accelerated stress test data of the commercial fuel cells
Authors: Hasegawa Shigeki , Kim Sanghong , Kageyama Miho , Kawase Motoaki
Published: September 2024

A model to estimate the Pt degradation rate and the numerical methods for high-speed computation were developed for the year-long and system-scale durability simulation in an acceptable accuracy and computational time. The parameters in the model were determined to reproduce the published accelerated stress test (AST) data with the 1 cm2 MEA of 2nd-generation MIRAI (MIRAI-2), state-of-the-art commercial fuel cell electric vehicle. Accuracy of the simulation results was validated by the published data of the ASTs with the FC stack having 13 cells of MIRAI-2, which consists of the 30000 startup-shutdown cycles in 0–0.88 V and 73000 acceleration-deceleration cycles in 0.6–0.9 V. The experimental and simulation results of the residual fractions of the electrochemical surface area in the cathode catalyst layer after the ASTs were 68 and 69 %, respectively, and they agreed in an acceptable accuracy. It was confirmed from the AST simulation with the different initial particle size distributions that even the small number of the coarse particles significantly accelerated the Pt degradation. The developed model was integrated to the FC system simulator the current authors had presented and a remarkable computational speed for the year-long and system-scale durability simulation was demonstrated with a normal laptop computer.
Diagnosis Method of Failure in PEMFC Using Magnetic Fields
Authors: Shibata Masumi , Akimoto Yutaro , Okajima Keiichi , Nishi Takahiro , Tanaka Shintaro
Published: September 2024

Proton exchange membrane fuel cells (PEMFCs) are currently used in various applications because they are compact, lightweight, and easy to start up. One of the challenges in PEMFCs is the improvement of gas diffusion. To overcome this challenge, appropriate water management in the gas diffusion layer and flow channels is necessary. Therefore, PEMFC diagnostic techniques are needed to detect flooding and plugging, which affect performance and efficiency. In this study, the magnetic field inside a PEMFC was analyzed to evaluate the changes caused by the internally generated water. Three cell types were used in the experiments: normal, channel-modified, and membrane–electrode assembly-modified cells. The results showed that the current was diverted because of the channel modification and water content, which resulted in a significant difference in the vertical magnetic field. This indicates that power generation inhibition due to flooding can be detected using vertical magnetic fields.
Effect of Non-ionic Surfactant on Fe-N-C Catalyst Layers under HT-PEMFC Conditions
Authors: Zierdt Tanja , Knake Jonas , Müller-Hülstede Julia , Schonvogel Dana , Wagner Peter , Wark Michael , Friedrich K. Andreas
Published: September 2024

The effect of different non-ionic surfactant contents on Fe-N-C gas diffusion electrode (GDE) coating and performance is investigated. GDEs are tested under high temperature polymer electrolyte membrane fuel cell (HT-PEMFC) conditions at 160 °C and concentrated phosphoric acid electrolyteFe-N-C-based GDEs are fabricated through ultrasonic spray coating with Tergitol contents of 0, 1, 20 and 50 wt% in the catalyst layer (CL). Thereby, the PTFE to catalyst ratio is kept constant at 1.0 in the CL. The H2O contact angle decreases with increasing Tergitol™ content in the CL, revealing an increased wettability. H3PO4 contact angles of Tergitol containing GDEs show a same wettability at room temperature as at 160 °C. GDE half-cell setup investigations show, that Tergitol leads to flooding of the electrode by the electrolyte and coverage of the active sites by the surfactant and thus a performance decay.
Spatially Resolved Analysis of the Influence of Three-Dimensional Flow Field Structures on Loss Processes in PEMFCs
Authors: Oppek Philipp , Raab Sebastian , Weber Andre
Published: September 2024

This study introduces a novel measurement device and technique to spatially resolve the influence of 3D flow field structures consisting of extended metal meshes on the performance distribution in PEMFCs. The newly designed segmented cell enables not only the measurement of the current distribution but also local electrochemical impedance spectra, subsequently analyzed by the distribution of relaxation times. The 3D flow field structures provide, despite of an increased HFR, an advantage at high current densities. The spatially resolved DRT analysis enabled the identification of polarization processes revealing that the gas diffusion process is greatly reduced compared to a conventional channel-rib design. In particular, the 3D coarse mesh shows promising advantages for application under high current densities. The findings from this study provide valuable insights into the local power and resistance distribution, enabling optimization of the flow field design and improvement of the performance of fuel cells with large active areas.
Deciphering Anion Exchange Membrane Water Electrolysis: A Distribution of Relaxation Times Approach
Authors: Ranz Matthias , Grabner Bianca , Schweighofer Bernhard , Wegleiter Hannes , Trattner Alexander
Published: September 2024

Anion exchange membrane water electrolysis (AEM-WE) is a promising method for hydrogen production, offering advantages over proton exchange membrane water electrolysis (PEM-WE), such as the use of nonprecious metal catalysts and perfluorosulfonic acid free membranes. Despite achieving impressive current densities, challenges in efficiency and stability remain. This study employs electrochemical impedance spectroscopy (EIS), the equivalent circuit model (ECM) and distribution of relaxation times (DRT) analysis to investigate AEM-WE cells. DRT analysis identifies and quantifies five loss mechanisms within the AEM-WE system, including hydrogen and oxygen evolution reactions and ionic transport losses. Long-term experiments reveal catalyst degradation and its impact on performance, providing insights for targeted optimisation. The findings enhance understanding of the electrochemical processes in AEM-WE, offering pathways to improve stability and efficiency.
Investigation of the Effect of Initial Anode Structures on the Durability of Water Electrolysis Cells
Authors: Hoshii Taisei , Hutapea Yasir Arafat , Ito Kohei , Hayashi Akari
Published: September 2024

Water electrolysis systems directly using renewable energy have been focused on this study. From our previous finding in the long-term accelerated voltage fluctuation test using actual wind power voltage fluctuations, increasing hydrophobicity and reducing gas stagnation within the anode catalyst layer were suggested. Then, controlling hydrophobic characters was considered in this study. Hydrophobic materials, such as polytetrafluoroethylene and polypyrrole, were chosen and added to the anode layers. As expected, the addition of 30% polytetrafluoroethylene improved hydrophobicity but also increased ohmic resistance, lowering IV performance. On the other hand, the use of polypyrrole was found to improve hydrophobicity while maintaining IV performance. However, the slight increase in activation and diffusion overvoltages was also observed, which was most likely owing to poor distribution of polypyrrole in the anode layer and possibly improved by adding a milling process.
Development of Mesoporous Carbon Fibers As Catalyst Supports for PEFC
Authors: Morinaka Yuma , Hutapea Yasir Arafat , Hayashi Akari
Published: September 2024

Mesoporous carbon fiber (MCF) sheet was developed for the purpose of controlling both the macroscopic fiber structure and the mesopore structure of the fibers. Two types of MCF sheet electrodes were fabricated by changing the conditions of the solution of electrospining. By depositing Pt on MCF sheet followed by introducing Nafion ionomer, MEAs with Pt/MCF sheet electrode as the cathode were prepared, and their IV performance was evaluated. As a result, Pt/MCF sheet electrodes successfully functioned as cathodes. On the other hand, IV performance was lower than that of a standard MEA, mainly due to the higher activation and concentration overvoltage. After evaluating different Pt/MCF sheet MEAs, increase in the Pt loading per sheet volume was found to be important to reduce the activation overvoltage, and optimizing the fiber density within the MCF sheet was found to be important to reduce the concentration overvoltage.
Nanostructured NiMoO4 as an Efficient Electrocatalyst for Oxygen Evolution Reaction
Authors: Rajangam Vinodh , Kalanur Shankara , Pollet Bruno Georges
Published: September 2024

Electrocatalysts derived from earth-abundant transition metals offer a viable alternative to noble metals for water electrolysis, yet they often suffer from poor catalytic behaviour and limited lifespan. In this study, nanostructured nickel molybdate on nickel foam (NiMoO4/NF) were synthesized via a straightforward hydrothermal process at three different durations (6, 12, and 24 h) to assess their oxygen evolution reaction (OER) performance. The electrodes, specifically NiMoO4-6h, NiMoO4-12h, and NiMoO4-24h, demonstrated significant OER activity in 1.0 M KOH solution, achieving overpotentials of 315 mV, 290 mV and 320 mV for respectively. Notably, the NiMoO4-12h electrode showed an exceptional stability, with only a 1.28% activity decrease after 200 hours at a current density of 10 mA cm-2. This study presents a novel approach to enhancing the electrocatalytic efficiency of these catalysts through optimizing their electrical conductivity, active surface sites, and surface reaction dynamics.
A Thermodynamic Analysis of a Proton Exchange Membrane Electrolyzer
Authors: Vlachaki Eirini , Lekatsas Konstantinos , Berning Torsten
Published: September 2024

A thermodynamic, first law analysis was conducted to understand the temperature of a proton exchange membrane electrolyzer when operated at a constant voltage and feed water flow rate. When using the electrolyzer voltage, current, liquid water feed rate and temperature, the electrolyzer operating temperature can be calculated. Heat losses can also be accounted for but are currently neglected. Carpet plots show the resulting electrolyzer temperature under varying conditions. The calculated temperatures are in very good agreement with measurements conducted in our laboratories.
Experimental Investigation on the Backpressure Effect on the Performance of a High Temperature Proton Exchange Membrane Fuel Cell Stack
Authors: Li Na , Zhou Mengfan , Sahlin Simon Lennart , Araya Samuel Simon , Liso Vincenzo
Published: September 2024

This study investigated the impact of backpressure of anode and cathode on the performance of a high-temperature proton exchange membrane fuel cell stack consisting of 30 cells, initially operating at a current density of 0.4 A/cm², temperature of 160 ℃, and 0 bar with pure H2. Subsequently, the backpressure on both sides was varied from 0 bar to 1.5 bar, and the changes in stack performance were recorded throughout the testing period. Additionally, the impact of backpressure was also investigated with reformates (H2/CO2/CO/N2 = 69.4%/22.3%/1.40%/6.9%) as anode feed for the stack. The results showed that increase in operating backpressure improves the fuel cell performance. A stack voltage increase of 20 mV per cell and 40 mV per cell were achieved for the pure hydrogen operation and reformate gas operation respectively when increasing backpressure from 0 bar to 0.5 bar. This signifies potential to improve the system’s overall efficiency with only minor penalty in terms of auxiliary power loss to increase the back pressure.
Assessing the Performance of a Proton Exchange Membrane Green Hydrogen Generation System through Stack and Balance of Plant Modeling
Authors: Almpantis Diamantis , Davidsson Henrik , Andersson Martin
Published: September 2024

The integration of Proton Exchange Membrane electrolyzers into hydrogen generation systems offers significant potential for sustainable energy solutions. Integrating hydrogen production with electricity, heat, and renewable energy sources enhances sustainability. PEM electrolyzers effectively address renewable energy intermittent by converting energy into hydrogen, leveraging their ramp rate and load-following capabilities. However, widespread commercialization hinges on cost reductions through new material development and a comprehensive understanding of the system's heat, mass, and electrochemical processes. This study presents a zero-dimension model developed using the Aspen Custom Modeler, detailing the electrochemical phenomena. A holistic PEM electrolysis model, including the stack and the Balance of Plant, is developed in Aspen Plus, demonstrating an overall system efficiency of 50%, with the BoP accounting for 8% of total electricity consumption. This research underscores the critical role of optimizing BoP subsystems and integrating grid-based backup solutions to enhance the economic viability and resilience of PEM electrolysis systems.
Study of Am electrodeposition from AmCl3-LiCl-KCl Molten Salt
Authors: Dean-Kersten Bethany , Hawthorne Krista , Williamson Mark , Akolkar Rohan , Duval Christine E.
Published: September 2024

In this work, the electrodeposition reaction of Am in AmCl3-LiCl-KCl molten salt was studied using voltammetry and chronoamperometry. Electrodeposition of Am was shown to proceed via a two

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step reaction scheme, involving the one-electron transfer reduction of Am3+ to Am2+, followed by the two-electron transfer reduction of intermediate Am2+ to Am0. A low Coulombic efficiency of Am deposition was measured despite the Am deposition occurring within the thermodynamic stability window of the supporting LiCl-KCl electrolyte. We hypothesize that the low efficiency is due to out-diffusion of the intermediate Am2+ species away from the electrode surface. Experimental observations provide evidence of a kinetically

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limited electrodeposition reaction, which allows for the loss of intermediate Am2+ via diffusion leading to Am deposition inefficiency.