bluuebunny/crossref_metadata_2025 huggingface dataset:
Collider constraints on electroweakinos in the presence of a light gravitino
Authors: Ananyev Viktor , Balázs Csaba , Beniwal Ankit , Braseth Lasse Lorentz , Buckley Andy , Butterworth Jonathan , Chang Christopher , Danninger Matthias , Fowlie Andrew , Gonzalo Tomás E. , Kvellestad Anders , Mahmoudi Farvah , Martinez Gregory D. , Prim Markus T. , Procter Tomasz , Raklev Are , Scott Pat , Stöcker Patrick , Van den Abeele Jeriek , White Martin , Zhang Yang ,   GAMBIT Collaboration
Published: June 2023

Using the global fitting framework, we constrain the MSSM with an eV-scale gravitino as the lightest supersymmetric particle, and the six electroweakinos (neutralinos and charginos) as the only other light new states. We combine 15 ATLAS and 12 CMS searches at 13 TeV, along with a large collection of ATLAS and CMS measurements of Standard Model signatures. This model, which we refer to as the $${{\tilde{G}}}$$

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-EWMSSM, exhibits quite varied collider phenomenology due to its many permitted electroweakino production processes and decay modes. Characteristic $${{\tilde{G}}}$$

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-EWMSSM signal events have two or more Standard Model bosons and missing energy due to the escaping gravitinos. While much of the $${{\tilde{G}}}$$

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-EWMSSM parameter space is excluded, we find several viable parameter regions that predict phenomenologically rich scenarios with multiple neutralinos and charginos within the kinematic reach of the LHC during Run 3, or the High Luminosity LHC. In particular, we identify scenarios with Higgsino-dominated electroweakinos as light as 140 GeV that are consistent with our combined set of collider searches and measurements. The full set of $${{\tilde{G}}}$$

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-EWMSSM parameter samples and input files generated for this work is available via .
Early evolution of fully convective stars in scalar–tensor gravity
Authors: Gomes Débora Aguiar , Wojnar Aneta
Published: June 2023

In this work, the early evolution of low-mass fully convective stars is studied in the context of DHOST (degenerate higher order scalar-tensor) theories of gravity. Although it is known that the hydrostatic equilibrium equation is modified for scalar-tensor gravity, the consequent modifications to the early evolution phases of a star were not explored in this framework. With this in mind, we consider three evolutionary phases—contraction to the main sequence, lithium burning and entrance to the main sequence—and investigate how each of these phases is affected by the theory’s parameter. Taking these effects into account, we are able to show, among other things, that the Hayashi tracks are shifted and the star’s age is considerably modified.
A Simple and Efficient Method for Accelerating Construction of the Gap-Greedy Spanner
Authors: Salami Hosein , Nouri-Baygi Mostafa
Published: June 2023

Let [Formula: see text] be the complete Euclidean graph on a set of points embedded in the plane. Given a constant [Formula: see text], a spanning subgraph [Formula: see text] of [Formula: see text] is said to be a [Formula: see text]-spanner, or simply a spanner, if for any pair of nodes [Formula: see text], [Formula: see text] in [Formula: see text] there exists a [Formula: see text]-path in [Formula: see text], i.e., a path between [Formula: see text] and [Formula: see text] whose length is at most [Formula: see text] times their distance in [Formula: see text].

Gap-greedy spanner, proposed by Arya and Smid, is a light weight and bounded degree spanner in which a pair of points [Formula: see text] is guaranteed to have a [Formula: see text]-path, if there exists at least one edge with some special criteria in the spanner. Existing algorithms for computing the gap-greedy spanner determine the existence of such an edge for each pair of points by examining the edges of the spanner, which takes [Formula: see text] time, however in this paper, we have presented a method by which this task can be done in [Formula: see text] time. Using the proposed method and well-separated pair decomposition, we have proposed a linear-space algorithm that can compute the gap-greedy spanner in [Formula: see text] time. How to use the well-separated pair decomposition to compute this spanner was proposed by Bakhshesh and Farshi, however using an example, we have shown that one of the algorithms they have proposed for this purpose is incorrect. We have performed various experiments to measure the duration and amount of memory used by the algorithms for computing this spanner. The results of these experiments showed that the proposed method, without a significant effect on the amount of memory consumed compared to previous algorithms, leads to a significant acceleration in the construction time of this spanner.
Entropy of the ensemble of acyclic graphs
Authors: Soares Edson A. , Moreira André A.
Published: June 2023

The structural phase transition in complex network models is known to yield knowledge relevant for several problems of practical application. Examples include resilience of artificial networks, dynamics of epidemic spreading, among others. The model of random graphs is probably the simplest model of complex networks, and the solution of this model falls into the universality class mean field percolation. In this work, we concentrate on a similar problem, namely, the structural phase transition in the ensemble of random acyclic graphs. It should be noted that several approaches to the problem of random graphs, such as generating functions or the Molloy–Reed criterion, rely on the fact that before the critical point, cycles should not be present in random graphs. In this way, up to the critical point our solution should produce results that are equivalent to these other methods. Our approach takes advantage of the fact that acyclic graphs allow for an exact combinatorial enumeration of the whole ensemble, what leads to an exact expression for the entropy of this system. With this definition of entropy we can determine the onset of the critical transition as well as the critical exponents associated with the transition. Our results are illustrated with Monte-Carlo results and are discussed within the context of general random graphs, as well as in comparison with another model of acyclic graphs.
Streaming Algorithms for Non-Submodular Functions Maximization with d-Knapsack Constraint on the Integer Lattice
Authors: Tan Jingjing , Yang Ruiqi , Zhang Yapu , Zhu Mingyue
Published: June 2023

We study the problem of maximizing a monotone non-submodular function under a [Formula: see text]-knapsack constraint on the integer lattice. We propose three streaming algorithms to approach this problem. We first design a two-pass [Formula: see text]-approximate algorithm with total memory complexity [Formula: see text], and total query complexity for each element [Formula: see text]. The algorithm relies on a binary search technique to determine the amount of the current elements to be added into the output solution. It also requires to have a good estimate of the optimal value, we use the maximum value of the unit standard vector which can be obtained by reading a round of data to construct a guess set of the optimal value. Then, we modify our algorithm to avoid a repetitive reading of data by dynamically update the maximum value of the unit vector along with the coming elements, and obtain a one-pass streaming algorithm with same approximate ratio. Moreover, we design an improved StreamingKnapsack algorithm to reduce the memory complexity to [Formula: see text].
Three-Stage Assembly Flow Shop Scheduling Problem with a Fixed Maintenance Period
Authors: Yuan Yuan , Han Xin , Zhou Yong , Liu Xingwu
Published: June 2023

This paper investigates the three-stage assembly flow shop scheduling problem, provided that there is a fixed maintenance period (MP) imposed on one of the machines in the first stage, the objective is to minimize the makespan. The starting time and duration of MP are known in advance, during MP no job can be processed on the corresponding machine. Only the non-resumable scenario is considered, i.e., if a job fails to finish before MP, it must restart from the beginning after the machine becomes available again, rather than continuing its processing. The problem generalizes the three-stage assembly flow shop scheduling problem without MPs and is therefore strongly NP-hard. To the best of our knowledge, the problem has not been explored so far. We propose three approximation algorithms for the problem.
An unsteady bioconvective non-Newtonian nanofluid model with variable thermal properties and modified heat flux framework
Authors: Ghachem Kaouther , Al-Khaled Kamel , Khan Sami Ullah , Alwadai Norah , Alshammari Badr M. , Kolsi Lioua , Chammam Wathek , Almuqrin Muqrin
Published: June 2023

The suspension nanoparticles in non-Newtonian materials convey different applications in the thermal systems, engineering processes, industrial energy developments, extrusion systems, solar system, etc. It is commonly observed that the thermal properties in the various base materials fluctuated and cannot be assumed to be constants. A decomposition of nanofluids is fluctuated and cannot considered as a constant. The objective of this communication is to inspect the thermal mechanism of non-Newtonian nanofluids due to accelerated frame in view of variable thermal conductivity. The modified mathematical relations for Fourier and Fick theories are utilized to model the problem. The nanofluids contain the microorganisms to ensure the thermal stability. The problem is modeled in nonlinear partial differential system which is further communicated via HAM. The convergent analysis is ensured and later on physical illustrations to problem in view of parameters are discussed. It is observed that thermal phenomenon controls due to mixed convection parameter while increasing impact for Williamson fluid parameter is observed. The magnitude of oscillation of Nusselt number due to Prandtl number is enhanced without any phase difference. The obtained results may convey different engineering applications like extrusion systems, chemical processes, thermal management systems, heating and cooling application, plasma, manufacturing processes.
Physical treatment of PCM in existence of nanoparticles during discharging
Authors: Rothan Yahya Ali
Published: June 2023

This work includes the finite element modeling of solidification process within the container with curved top wall. The container has three insulated wall and one cold wall which is situated on top wall and it has sinusoidal configuration. Nanoparticles with low fraction were loaded inside the water to improve the thermal features. In deriving the mathematical model, two main assumptions were incorporated: (1) neglecting the impact of velocity; (2) considering homogeneous mixture for NEPCM. To improve the accuracy of numerical approach, the variable style of grid with time has been employed and also, implicit method was considered for time-dependent two terms. Increasing fraction of nano-powders has its maximum effect when the second level of dp has been selected in which required time reduces around 41.33%. Also, in existence of maximum size of particles, changing [Formula: see text] causes reduction of time around 12.41%. With altering dp from 30 to 40[Formula: see text]nm, the freezing period reduces around 19.99% while augmenting up to 50[Formula: see text]nm can lead to reduction of time around 49.29%.
Dynamics of Soret–Dufour effects and thermal aspects of Joule heating in multiple slips Casson–Williamson nanofluid
Authors: Ali Usman , Irfan Muhammad , Akbar Noreen Sher , Rehman Khalil Ur , Shatanawi Wasfi
Published: June 2023

Recently, the thought of nanotechnology has endowed mankind to create materials of nanometer magnitudes. Nanoparticles or nanomaterials have diverse optical, chemical, thermal and physical possessions from their pre-supremacy corresponding item. Hence, this paper comprises the features of a Casson–Williamson flow field with nanoparticles. Here, we explored the impact of rate slip precondition on the mechanics of heat and mass transport over a stretched sheet with viscous dissipation, and heat generation in an exceedingly porous medium. The influence of Soret–Dufour, magneto-hydrodynamics (MHD) and thermal radiation is presumed. All chemical science specifications of nanofluid are measured as constant. As a result of motion of nanofluid particles, the fluid concentration is inspected underneath chemical implications. A collection of coupled partial differential frameworks is accustomed mathematically to formulate the physical model. The scheme for numerical study named Runge–Kutta approach along with shooting technique is implied to solve the obtained equations. The numerical procedure is then displayed pictorially, where fluid velocity, temperature and concentration against various pertinent parameters are examined. The velocity of the nanofluid encompasses a quicker rate within the deficiency of a magnetic factor; however, the velocity field possesses a reverse trend for Casson factor. The higher Eckert number intensifies the temperature of Casson fluid. Furthermore, the Casson parameter and the velocity slip parameter reduce the drag force and local Nusselt number.
Nanosensors sensitivity based on localized surface plasmons created in bimetallic nanoshells
Authors: Firoozi A. , Khordad R. , Sedehi H. R. Rastegar
Published: June 2023

Due to the increasing importance of nanosensors in the early diagnosis of diseases, the need for high-performance nanosensors is one of the goals of researchers. In this paper, a structure consisting of plasmonic nanoshells with spherical and ellipsoidal geometry has been proposed to calculate the refractive index (RI) changes in the range of 1–3. The sensitivity of the proposed nanosensor has been computed, and the effective factors on the performance of the nanosensor, including geometry, material, core dimensions, shell thickness, and RI of the surrounding environment are studied. To this end, various nanostructures have been modeled using the boundary element method. It has been shown that ellipsoidal nanoshells are more sensitive to RI changes than spherical nanoshells. Also, the results show that nanoshells with a core and shell made of plasmonic metals (bimetallic nanoshell) can exponentially increase the sensitivity of the nanosensor.
Hybrid COOT-Reverse Cognitive Fruit Fly Optimization-Based Big Data Services and Virtual Machine Allocation for Cloud Storage System
Authors: Kalai Arasan K. , Anandhakumar P.
Published: June 2023

In recent years, cloud computing technologies have been developed rapidly in this computing world to provide suitable on-demand network access all over the world. A cloud service provider offers numerous types of cloud services to the user. But the most significant issue is how to attain optimal virtual machine (VM) allocation for the user and design an efficient big data storage platform thereby satisfying the requirement of both the cloud service provider and the user. Therefore, this paper presents two novel strategies for optimizing VM resource allocation and cloud storage. An optimized cloud cluster storage service is introduced in this paper using a binarization based on modified fuzzy c-means clustering (BMFCM) algorithm to overcome the negative issues caused by the repetitive nature of the big data traffic. The BMFCM algorithm utilized can be implemented transparently and can also address problems associated with massive data storage. The VM selection is optimized in the proposed work using a hybrid COOT-reverse cognitive fruit fly (RCFF) optimization algorithm. The main aim of this algorithm is to improve the massive big data traffic and storage locality. The CPU utilization, VM power, memory dimension and network bandwidth are taken as the fitness function of the hybrid COOT-RCFF algorithm. When implemented in CloudSim and Hadoop, the proposed methodology offers improvements in terms of completion time, overall energy consumption, makespan, user provider satisfaction and load ratio. The results show that the proposed methodology improves the execution time and data retrieval efficiency by up to 32% and 6.3% more than the existing techniques.
A Personalized POI Recommendation Algorithm Using BERT-ACNN-GRU
Authors: Xia Dongliang , Liu Jianfang , He Weina , Gao Jingli
Published: June 2023

This paper proposes a point-of-interest (POI) sequence recommendation algorithm based on BERT-ACNN-GRU to address the issues faced by the existing POI recommendation model in social network large data, such as the difficulty in extracting deep feature information and the low recommendation performance. Firstly, the semantic relationship between a word and its context in the text is combined using the bidirectional encoder representation from transformers (BERT) model to effectively eliminate the influence of word distance and obtain the contextualized word vector. Secondly, a convolutional neural network (CNN) utilizing a gated recurrent unit (GRU) is employed to capture the feature information of the text. Lastly, the attention method is utilized to assign weight scores to various terms in order to provide more attention to particular words and boost the precision of recommendations. The experiments demonstrate that the precision, recall rate, F1 score and mean average precision (mAP) of the proposed method are 0.097, 0.26, 0.103, and 0.085 on the Gowalla dataset when the recommendation list has a length of 10, respectively. On the Yelp dataset, the precision is 0.093, the recall rate is 0.26, F1 is 0.099, and MAP is 0.089. Hence, the proposed method can effectively enhance the performance of the POI recommendation system.
A Multitask Attention Network for Food Delivery Time Prediction
Authors: Huang Feihong , Jiang Wei , Chen Shujie
Published: June 2023

Given the recent increase in the prevalence of online food ordering apps, food delivery has become an emerging service. Intelligent dispatch systems have been widely deployed by many on-demand logistics companies to maximize delivery efficiency. Predicting the food delivery time is a key module that provides critical information at the decision-making stage of order dispatch to ensure the punctual delivery service for each customer. In this study, we propose a multitask attention network for food delivery time prediction, mimicking the driver’s decision-making process during delivery. First, an attention mechanism is employed to capture mutual influences among orders and evaluate the importance of each order. Then, a multitask learning method is used to simultaneously train delivery time prediction and delivery priority prediction. Finally, a specific loss function is designed to further improve the accuracy of prediction. Extensive modeling demonstrates that our model greatly outperforms other state-of-the-art methods.
An Adaptive Semantic Annotation Tool for Teachers Based on Context-Aware and Internet of Things
Authors: Bensattalah Aissa , Chalal Rachid , Nader Fahima
Published: June 2023

Annotation has demonstrated its importance in several areas, notably in the modeling of annotation activity in the automation and adaptation phase. However, the context sensor is commonly manual or semi-automatic. The use of the Internet of Things with annotation gives a qualitative leap in the field of higher education and universities. In this field, teachers, during their pedagogical activities, require more information found in different textual documents, tools, and databases. In addition, they organized several meetings and took considerable time to make appropriate and right decisions during the deliberation process. In this paper, we propose an adaptive annotation tool based on the Internet of Things addressed for teachers during their educational tasks. The presented tool automatically adapts according to the context of the teacher’s tasks and it enables the annotation of all documents written in different languages. To consider all the parameters of the teaching activities when interfacing with the annotation and to give the useful information for teachers during decision-making, we have adopted an architecture based on the ontology of context and the multilingual ontology of deliberation and redemption. To implement this tool, we used Semantic Web and Internet of Things technology to achieve the desired architecture. Likewise, the usability of the proposed annotation tool has been tested with a real case in coordination with teachers and administrators during the deliberation operation to decide to rescue and redeem students at the university.
Necessary and sufficient criteria for existence, regularity, and asymptotic stability of enhanced pullback attractors with applications to 3D primitive equations
Authors: Wang Renhai , Guo Boling , Huang Daiwen
Published: June 2023

We introduce several new concepts called enhanced pullback attractors for nonautonomous dynamical systems by improving the compactness and attraction of the usual pullback attractors in strong topology spaces uniformly over some infinite time intervals. Then we establish several necessary and sufficient criteria for the existence, regularity and asymptotic stability of these enhanced pullback attractors under general theoretical frameworks which are expected to be applied to many kinds of nonautonomous PDEs. These abstract results are applied to the famous 3D primitive equations modeling the large-scale ocean and atmosphere dynamics. We establish the existence, regularity and asymptotic stability of the enhanced pullback attractors for the nonautonomous primitive equations in [Formula: see text] and [Formula: see text] when the forces satisfy some mild conditions. The uniform pullback asymptotic compactness of the solution operators in [Formula: see text] and [Formula: see text] are established by deriving the uniform “flattening effects” of the solutions in [Formula: see text] and the uniform [Formula: see text]-Hölder continuity of the solutions from [Formula: see text] to [Formula: see text] with respect to the initial data, respectively. Our approaches are applicable to prove the existence of global attractors for the autonomous primitive equations in [Formula: see text] provided [Formula: see text].
Three-species drift-diffusion models for memristors
Authors: Jourdana Clément , Jüngel Ansgar , Zamponi Nicola
Published: June 2023

A system of drift-diffusion equations for the electron, hole, and oxygen vacancy densities in a semiconductor, coupled to the Poisson equation for the electric potential, is analyzed in a bounded domain with mixed Dirichlet–Neumann boundary conditions. This system describes the dynamics of charge carriers in a memristor device. Memristors can be seen as nonlinear resistors with memory, mimicking the conductance response of biological synapses. In the fast-relaxation limit, the system reduces to a drift-diffusion system for the oxygen vacancy density and electric potential, which is often used in neuromorphic applications. The following results are proved: the global existence of weak solutions to the full system in any space dimension; the uniform-in-time boundedness of the solutions to the full system and the fast-relaxation limit in two space dimensions; the global existence and weak–strong uniqueness analysis of the reduced system. Numerical experiments in one space dimension illustrate the behavior of the solutions and reproduce hysteresis effects in the current–voltage characteristics.
Compressible Euler–Maxwell limit for global smooth solutions to the Vlasov–Maxwell–Boltzmann system
Authors: Duan Renjun , Yang Dongcheng , Yu Hongjun
Published: June 2023

Two fundamental models in plasma physics are given by the Vlasov–Maxwell–Boltzmann system and the compressible Euler–Maxwell system which both capture the complex dynamics of plasmas under the self-consistent electromagnetic interactions at the kinetic and fluid levels, respectively. It has remained a long-standing open problem to rigorously justify the hydrodynamic limit from the former to the latter as the Knudsen number [Formula: see text] tends to zero. In this paper, we give an affirmative answer to the problem for smooth solutions to both systems near constant equilibrium in the whole space in case when only the dynamics of electrons is taken into account. The explicit rate of convergence in [Formula: see text] over an almost global time interval is also obtained for well-prepared data. For the proof, one of main difficulties occurs to the cubic growth of large velocities due to the action of the classical transport operator on local Maxwellians and we develop new [Formula: see text]-dependent energy estimates basing on the macro–micro decomposition to characterize the asymptotic limit in the compressible setting.
Emergence of quantum-field theory in causal diamonds
Authors: Banks Tom
Published: June 2023

The experimental successes of quantum-field theory do not justify using it to describe even a finite fraction of the entanglement entropy of a causal diamond with its exterior, in the limit of large diamonds. Susskind and Uglum and Jacobson conjectured that this divergent entropy could be thought of as a renormalization of Newton’s constant in the Bekenstein–Hawking formula, if we applied that formula to arbitrary causal diamonds. Jacobson showed that this leads to a derivation of the null projection of Einstein’s equations as the hydrodynamic equations of the area law for arbitrary diamonds, a derivation which has the added virtue of demonstrating that the cosmological constant is not an energy density. Using a gauge choice adapted to causal diamond boundaries, we revisit arguments of Carlip and Solodukhin that the proper theory of near horizon states is a (cut-off) (1 + 1)-dimensional conformal field theory, with central charge proportional to the transverse area. This leads to a universal formula for fluctuations of the modular Hamiltonian of a diamond, which we argue is compatible with the explanation of the temperature of de Sitter space in terms of an identification between localized energy and the number of constrained q-bits of the holographic degrees of freedom.
SHORT- TO MIDTERM RADIOGRAPHIC AND CLINICAL OUTCOMES OF ANTERIOR OPENING OSTEOTOMY WITH LAMINA SPARING IN POST-TRAUMATIC KYPHOSIS: A CASE SERIES
Authors: Chang Chih-Mai , Chen Kun-Hui , Pan Chien-Chou , Lu Wen-Hsien , Su Kuo-Chih , Lee Cheng-Hung
Published: June 2023

Purpose: Most spinal osteotomy procedures applied for spinal deformity and concomitant malalignment cases are associated with varied complications. This study evaluates the short- to midterm clinical and radiographic efficacy of the transpedicular anterior opening osteotomy technique.

Methods: We retrospectively enrolled six patients who underwent transpedicular anterior opening osteotomy due to symptomatic rigid kyphotic deformity from May 2005 to 2016. During surgery, we created a new fracture line at the collapsed anterior vertebral body through bilateral pedicles, filled spaces with compacted bone grafts while preserving posterior elements, including lamina, and secured structure using posterior instrumentation. The kyphotic Cobb angle, Visual Analog Scale (VAS), and Oswestry Disability Index (ODI) before and after surgery were measured and analyzed.

Results: The mean preoperative kyphotic Cobb angle was [Formula: see text] while the postoperative value was [Formula: see text]. The mean correction angle was [Formula: see text]. The mean follow-up duration was [Formula: see text] months. During the final follow-up, the mean kyphotic angle was not statistically different from the postoperative values. All patients with documented VAS Back and ODI had improved values postoperatively.

Conclusions: Transpedicular anterior opening osteotomy with posterior element preservation improves clinical outcomes and is safe and effective in correcting regional, fixed kyphotic deformities.
Recurrence and transience of quantum Markov semigroups constructed form quantum Bernoulli noises
Authors: Chen Jinshu , Hai Shexiang
Published: June 2023

Quantum exclusion semigroup constructed form quantum Bernoulli noises can be written on diagonal and off-diagonal operators space, respectively. The diagonal parts describe a classical Markov process. In this paper, we first produce a decomposition into the sum of irreducible components determined by the class states of the associated classical Markov process and prove that each irreducible component is recurrent or transient if and only if its diagonal restriction is recurrent or transient. We then give conditions for existence of invariant states and study properties of invariant states such as detailed balance, uniqueness and convergence towards as time approaches infinity.
Averaging for the 2d dispersion-managed NLS
Authors: Campos Luccas , Murphy Jason , Van Hoose Tim
Published: June 2023

We establish global-in-time averaging for the [Formula: see text]-critical dispersion-managed nonlinear Schrödinger equation in the fast dispersion management regime. In particular, in the case of nonzero average dispersion, we establish averaging with any subcritical data, while in the case of a strictly positive dispersion map, we obtain averaging for data in [Formula: see text].
Non-vanishing higher derived limits
Authors: Veličković Boban , Vignati Alessandro
Published: June 2023

In the study of strong homology Mardešić and Prasolov isolated a certain inverse system of abelian groups [Formula: see text] indexed by elements of [Formula: see text]. They showed that if strong homology is additive on a class of spaces containing closed subsets of Euclidean spaces then the higher derived limits [Formula: see text] must vanish, for [Formula: see text]. They also proved that under the Continuum Hypothesis [Formula: see text]. The question whether [Formula: see text] vanishes, for all [Formula: see text], has attracted considerable interest from set theorists. Dow, Simon and Vaughan showed that under the Proper Forcing Axiom (PFA) [Formula: see text]. Bergfalk showed that it is consistent that [Formula: see text] does not vanish. Later Bergfalk and Lambie-Hanson showed that, modulo a weakly compact cardinal, it is relatively consistent with ZFC that [Formula: see text], for all [Formula: see text]. The large cardinal assumption was recently removed by Bergfalk, Hrušak and Lambie-Hanson. We complete the picture by showing that, for any [Formula: see text], it is relatively consistent with ZFC that [Formula: see text].
Prescribed blow-up sets for sequences of solutions to a non-local Q-curvature equation in ℝ3
Authors: Wang Yamin
Published: June 2023

Let [Formula: see text] be an open connected domain and [Formula: see text] stand for the Laplacian in [Formula: see text]. For a uniformly bounded sequence [Formula: see text] having a fixed sign and non-positive bi-harmonic functions [Formula: see text], we prove that there exists a sequence of solutions [Formula: see text] to [Formula: see text] with a total curvature [Formula: see text] such that [Formula: see text] for [Formula: see text] and [Formula: see text] for [Formula: see text], where [Formula: see text] is the zero set given by [Formula: see text] In particular, when [Formula: see text] is smoothly bounded and [Formula: see text], we obtain that [Formula: see text] blows up on [Formula: see text] for any [Formula: see text]. This extends the work of Hyder et al. who treated the analogue in even dimensions and complements a previous result in dimension three. We also consider a radial case with no blowing up phenomena and large total curvature.
A Comparative Study of Dynamic Responses of Coastal Long-Span Bridge Under Typhoon with Different Crossing Paths
Authors: Guo Jian , Zhong Chengjie , Ma Kaijiang , Shen Yufeng
Published: June 2023

Coastal long-span bridges are intensively constructed along the western Pacific coast. While the coast is frequently disturbed by typhoons. Given that a coastal long-span bridge will experience a number of typhoons during its service life, it is important to have an understanding of the wind fields formed by typhoons with different crossing paths and corresponding structural dynamic responses. Wind and acceleration data of the Xihoumen Bridge under the influence of onshore, offshore, and landfalling typhoons were acquired by the structural health monitoring system (SHMS). Wind field features of typhoons with three types of paths were compared. The landfalling Typhoon In-fa was used to investigate the differences of wind-induced structural dynamic responses under the influence of each typhoon structural region. The covariance-driven stochastic subspace identification (SSI-COV) was used to identify the modal parameters of the bridge. The results revealed that wind field features at bridge site varied with typhoon crossing paths. The SSI-COV accurately identified the structural frequencies of first 15 vertical modes using the acceleration data under the influence of spiral rainband. The first eyewall has the most detrimental wind conditions to the bridge because the stiffening girder vibrated violently in this region.
An Eigensystem Realization Algorithm for Identification of Modal Parameters of Nonviscous Damping Structure System
Authors: Shen Renjie , Qian Xiangdong , Zhou Jianfang , Lee Chin-Long
Published: June 2023

In this paper, a modified eigensystem realization algorithm for modal parameter identification and relaxation parameter is extended from a viscous damping system to a nonviscous damping system. The equation of motion with nonviscous damping in second-order form is expressed in the state space formulation. The eigenvalues of the second-order form equation are proved equal to the state space formulation. The extended method is based on the proposed nonlinear relationship between the eigenvalues and the damping parameters of a nonviscous damping system. The identified procedure of the proposed method is given in detail. Finally, the method is validated using three numerical examples for assessing its accuracy.
Structural Modal Parameters Identification Under Ambient Excitation Using Optimized Symplectic Geometry Mode Decomposition
Authors: Hu Feng , Zhi Lunhai , Zhou Kang , Li Shouji , Hu Zhixiang
Published: June 2023

In the process of structural modal parameters identification under environmental excitation, the employed measured dynamic response signal is usually non-stationary and contains noise. As a novel signal analyzed method, symplectic geometry mode decomposition (SGMD) has been proven to be effective for dealing with non-stationary and noisy signals. However, the traditional SGMD may treat noise as modal information, which inevitably undermines the accuracy of modal identification. To overcome this problem, this paper proposes an optimized SGMD algorithm for structural modal parameter identification. First, the SGMD algorithm is refined with the Hankel matrix, Kurtosis theory, Pearson correlation coefficient, and energy entropy theory. Then, the natural frequencies and damping ratios are identified using the proposed method, which consists of the optimized SGMD algorithm, natural excitation technique (NExT), direct interpolating method, and curve-fitting function. Finally, the applicability of the proposed method under environmental excitation is investigated by two examples: a two-story frame structure and an 88-story office tower. The results demonstrate that the proposed method is effective for identifying the civil structural modal parameters from non-stationary dynamic responses.
Rapid Assessment of Seismic Risk for Railway Bridges Based on Machine Learning
Authors: Huang Yong , He Jing , Zhu Zhihui
Published: June 2023

When an earthquake occurs, railway bridges will suffer from different degrees of seismic damage, and it is necessary to assess the seismic risk of bridges. Unfortunately, the majority of studies were done on highway bridges without taking into account railway bridge characteristics; hence they are not applicable to railway bridges. Furthermore, current research methods for risk assessment cannot be performed quickly, and suffer from the problems of subjective personal experience, complicated calculations, and time-consuming. This paper we use machine learning for earthquake damage prediction and empirical vulnerability curves to represent risk assessment results, creating a rapid risk assessment procedure. We gathered and tallied seismic damage data from 335 railway bridges that were damaged in the Tangshan and Menyuan earthquakes, found six variables that had a substantial impact on seismic risk outcomes, and categorized the damage levels into five categories. It is essentially a multi-classification and prediction problem. In order to solve this problem, four algorithms were tested: Random Forest (RF) Back Propagation Artiifcial Neural Network (BP-ANN), PSO-Support Vector Machine (PSO-SVM), and K Nearest Neighbor (KNN). It was found that RF is the most effective method, with an accuracy rate of up to 93.31% for the training set and 89.39% for the test set. Then this study describes the new procedure in detail for rapidly assessing seismic risk to 269 bridges chosen at random from the sample pool. Firstly, the seismic damage data of bridges are collated, then the seismic damage rating is predicted using RF, and finally the empirical vulnerability curve is drawn using a two-parameter normal distribution function for the purpose of seismic damage risk assessment. The study’s findings can be used as a guide for choosing a machine learning approach and its inputs to build a rapid assessment model for railway bridges.
Vibration and Stability Analysis of a Spinning Hollow Functionally Graded Beam with Exponentially Varying Cross-Section
Authors: Wang Guangding , Zhao Qing , Chen Liqing , Yuan Huiqun
Published: June 2023

This paper presents an analytical investigation of the whirl characteristics and flexural instability of a spinning functionally graded (FG) hollow beam with exponentially varying cross-section. Applying Rayleigh beam theory, the governing equation of motion of the spinning beam with eccentricity is formulated via the Hamilton principle. The dimensionless whirl frequency equation is obtained for the FG beam with pinned–pinned end supports. On the basis of the obtained model, the whirl frequency, critical spinning speed, and stability conditions of the system are studied. Also, the effects of the main parameters on the whirl characteristics and stability of the system are evaluated. Results show that the unbalanced mass is the main source of system instability. It is also shown that the whirl frequency, critical spinning speed, and stability boundaries of the system are strongly dependent on the slenderness ratio, taper parameter, gradient index, hollow ratio, and eccentricity effects.
Existence and nonexistence criteria for a system of biharmonic wave inequalities in an exterior domain of ℝN
Authors: Jleli Mohamed , Samet Bessem
Published: June 2023

We consider a system of nonlinear biharmonic wave inequalities posed in an exterior domain of [Formula: see text]. Three types of boundary conditions are investigated. For each case, the existence and nonexistence of weak solutions are studied. Our study yields naturally existence and nonexistence results for the corresponding stationary system and equation. Many new results are provided and some open questions are proposed.
ERP System Evaluation in the Defense Industry: A Hybridized Spherical Fuzzy AHP-Codas Approach
Authors: Nebati Emine Elif , Ayvaz Berk , Kusakci Ali Osman
Published: June 2023

Design/methodology/approach: Converting data into information and its diffusion along all organization units has become a vital survival skill. At this point, an ERP system provides an invisible network among a company’s internal and external stakeholders and plays a strategic role. Moreover, ERP systems offer some advantages. For example, integrating financial, customer, and order information, speeding up production processes, and reducing stock level and order lead time. Therefore, we propose an integrated spherical fuzzy-analytical hierarchy process (SF-AHP) and spherical fuzzy-combinative distance-based assessment (SF-CODAS) framework to prioritize the best ERP software provider for the defense industry.

Purpose: Despite having the advantages mentioned above, some crucial aspects must be considered while selecting an ERP package. Factors such as high cost, difficulty in installation, and security threats can be very challenging. The latter issue needs special care in the defense industry. This study aims to design an evaluation framework for the ERP selection problem in the sector.

Findings: One of the pivoting defense companies in Turkey is chosen as a case study. Seven ERP systems are evaluated with the proposed model. The results show that the proposed model can be successfully implemented in a defense company context. Furthermore, a sensitivity analysis proves the robustness of the approach to varying threshold parameters in CODAS and different fuzzy weighting approaches.

Originality/value: The defense professionals prioritize a different set of selection criteria than conventional manufacturing firms. The study provides a rare holistic framework for the defense industry using a hybridized SF-AHP-CODAS technique. Thus, the study may serve as reference work for the researchers and decision-makers during the digitalization journey of defense firms.
Detailed asymptotic expansions for partitions into powers
Authors: O’Sullivan Cormac
Published: June 2023

In this paper, we examine the number of ways to partition an integer [Formula: see text] into [Formula: see text]th powers when [Formula: see text] is large. Simplified proofs of some asymptotic results of Wright are given using the saddle-point method, including exact formulas for the expansion coefficients. The convexity and log-concavity of these partitions is shown for large [Formula: see text], and the stronger conjectures of Ulas are proved. The asymptotics of Wright’s generalized Bessel functions are also treated.
Object Detection Enhanced by Hybrid Overlay for Augmented Reality
Authors: Maidi Madjid , Otmane Samir , Lehiani Yassine , Preda Marius
Published: June 2023

In this work, we proposed and developed an approach for markerless object detection and registration in augmented reality. Our system enables the superimposition of videos or 3D graphics on natural objects in a real-time tracking process. The object of interest is detected within a sequence of images using the feature points and their invariant descriptors. The matching process between the test image and the training images is calculated using a 2D homography to generate the projective transformation for the video registration part. Further, the 3D graphic is overlaid into the scene by estimating the real camera pose and solving transformations relating the virtual and the real reference frames. The conducted experiments provided accurate and time effective results. Our approach detects and tracks markerless objects in real-time and enables video and 3D models registration for augmented reality experiences.
Named Entities as Key Features for Detecting Semantically Similar News Articles
Authors: Stockem Novo Anne , Gedikli Fatih
Published: June 2023

The focus of this work is detecting semantically similar news articles for search engines and recommender systems which is an important step towards processing and understanding natural language. Search engines and recommender systems typically filter out near-duplicate articles which are often just a paraphrasing of a previous article and therefore irrelevant for the users. Articles with a high level of overlapping content are not interesting to the reader and should be avoided. Here, we focus on named entities, such as people, organizations and places, and their role as a key feature for identifying near-duplicate articles. Since our dataset from the energy business contains a significant amount of paraphrased articles, standard techniques, e.g. based on the Jaccard coefficient, already serve quite well. A fine-tuned BERT model evaluated on named entities achieves best model results with more than 97% accuracy and highest True Positive Rates. The importance of individual words for the model decisions is evaluated by computing their Shapley values. It was found that the explanations are in overall good agreement with the human intuitive interpretation.
Learning Causal Graphs in Manufacturing Domains Using Structural Equation Models
Authors: Kertel Maximilian , Harmeling Stefan , Pauly Markus , Klein Nadja
Published: June 2023

Many production processes are characterized by numerous and complex cause-and-effect relationships. Since they are only partially known, they pose a challenge to effective process control. In this work we present how Structural Equation Models can be used for deriving cause-and-effect relationships from the combination of prior knowledge and process data in the manufacturing domain. Compared to earlier applications, we do not assume linear relationships leading to more informative results. Furthermore, our results indicate that including expert knowledge seems to be able to reduce the difference between the learned cause-effect relationships and the expert assessment, thus opening a promising direction for future research on manufacturing processes.
Mobile Gait Analysis
Authors: Agius Owen , Dingli Alexiei
Published: June 2023

This project aims to develop an extension to automated gait analysis that makes gait analysis available on smart devices. The alternative may serve as a baseline for future implementations that are cheaper, user-friendly and accessible to an ordinary smartphone or web browser. Accessibility of gait analysis on an application encourages people to check their walking patterns more regularly, and if the issue is very severe, they can take the next step of contacting a specialist. By collaborating with the Podiatry Department of the University of Malta and the Chinese Academy of Sciences Institute of Automation (CASIA), a considerable amount of gait data was acquired. The data consists of videos of people walking regularly or irregularly. But videos are not enough for the development of our system. The videos were inputted into a pose estimator whose goal was to outline the skeleton of the person throughout the video. Additionally, the pose estimator was modified to record the coordinates of the main joints concerning a gait cycle (hip, knee and ankle). These coordinates were then plotted as a scatter plot where the gait cycle is generated. With the coordinates extracted, kinematics were also extracted to create another model which detects different features for gait analysis. After the gait cycle of each video was extracted, the next step was to classify whether that gait cycle was either regular or irregular. This goal is achieved by passing the extracted data through the VGG16 architecture. The application was tested out on people which have either bad, good or slightly bad gaits to investigate the rigidity of the system. After a series of experiments, it can be concluded that the system performs with 94% accuracy just by using a mobile phone.
An Assessment of Resilience Capacities in Local Disaster Management: A Case Study of Tabriz, Iran
Authors: ASADI Ahmad
Published: June 2023

Regarding the approach of reducing risks of settlements, a system is considered to be resilient if it can address temporary and permanent risks and adapt itself to rapidly changing conditions without losing its functionality. To this end, a dynamic management approach on a local scale is needed for realizing resilience. Due to the importance of local management in improving resilience in cities, this study aims to assess the resilience capacity of the local risk management in terms of exposure to various crises in Tabriz, Iran. The findings in this study show that integrity and coordination in decision- or policy-making, enhancement of organizational and local capacities, and confrontation or rehabilitation approaches in critical conditions and after that are not desirable in Tabriz. Also, the centralized and top-down approaches lead to no proper local planning and management that can facilitate the resilience measures. In light of no spatial equilibrium in Tabriz and the inefficiency of conventional planning and management systems, technocrat-oriented and top-down, changing the management practices and emphasizing the local and bottom-up approach are necessary for the thorough understanding of facilities and limitations and implementation of realistic planning.