bluuebunny/crossref_metadata_2025_split huggingface dataset:
An integrated coupled oscillator network to solve optimization problems
Authors: Graber Markus , Hofmann Klaus 
Published: August 2024

AbstractSolving combinatorial optimization problems is essential in scientific, technological, and engineering applications, but can be very time and energy-consuming using classical algorithms executed on digital processors. Oscillator-based Ising machines offer a promising alternative by exploiting the analog coupling between electrical oscillators to solve such optimization problems more efficiently. Here we present the design and the capabilities of our scalable approach to solve Ising and quadratic unconstrained binary optimization problems. This approach includes routable oscillator connections to simplify the time-consuming embedding of the problem into the oscillator network. Our manufactured silicon chip, featuring 1440 oscillators implemented in a 28 nm technology, demonstrates the ability to solve optimization problems in 950 ns while consuming typically 319 μW per node. A frequency, phase, and delay calibration ensures robustness against manufacturing variations. The system is evaluated with multiple sets of benchmark problems to analyze the sensitivity for parameters such as the coupling strength or frequency.
Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes
Authors: Ghiaci Payam , Jouhten Paula , Martyushenko Nikolay , Roca-Mesa Helena , Vázquez Jennifer , Konstantinidis Dimitrios , Stenberg Simon , Andrejev Sergej , Grkovska Kristina , Mas Albert , Beltran Gemma , Almaas Eivind , Patil Kiran R , Warringer Jonas 
Published: August 2024

AbstractAdaptive Laboratory Evolution (ALE) of microorganisms can improve the efficiency of sustainable industrial processes important to the global economy. However, stochasticity and genetic background effects often lead to suboptimal outcomes during laboratory evolution. Here we report an ALE platform to circumvent these shortcomings through parallelized clonal evolution at an unprecedented scale. Using this platform, we evolved 104 yeast populations in parallel from many strains for eight desired wine fermentation-related traits. Expansions of both ALE replicates and lineage numbers broadened the evolutionary search spectrum leading to improved wine yeasts unencumbered by unwanted side effects. At the genomic level, evolutionary gains in metabolic characteristics often coincided with distinct chromosome amplifications and the emergence of side-effect syndromes that were characteristic of each selection niche. Several high-performing ALE strains exhibited desired wine fermentation kinetics when tested in larger liquid cultures, supporting their suitability for application. More broadly, our high-throughput ALE platform opens opportunities for rapid optimization of microbes which otherwise could take many years to accomplish.
Enhancing network attack detection across infrastructures: An automatic labeling method and deep learning model with an attention mechanism
Authors: Vu Dinh‐Minh , La Thi Ha , Nguyen Gia Bach , Huh Eui‐Nam , Tran Hoang Hai 
Published: August 2024

AbstractIn the era of industry 4.0 and the widespread use of digital devices, the number of cyber attacks poses an escalating and diverse threat, jeopardizing users' online activities. Intrusion detection systems (IDS) emerge as pivotal solutions, playing a crucial role in detecting anomalous signals within network systems. To counter novel attack patterns, IDS systems require periodic rule updates for effective identification of unusual signals. Typically, these policies are updated based on rule‐based or deep learning algorithms to enhance detection performance. However, the insufficient number of labeled samples remains a challenge for real‐world deployment. In this article, an automated labeling method is presented that has shown high effectiveness, requiring minimal hardware resources, and applicable to IDS systems. Additionally, the approach utilizes transfer learning combined with attention mechanisms to boost the efficiency of abnormal signal detection. The results from the approach are compared with those of a reference model, illustrating an overall improvement of nearly 10% in our model's performance compared to the reference model. This underscores the effectiveness of automating rule adjustments for IDS, contributing significantly to reducing associated financial costs. The research addresses the challenges in deploying IDS in real‐world scenarios and provides a valuable contribution to enhancing cyber threat detection capabilities.A preprint has previously been published [11].
Two efficient three‐mode control strategies for four‐switch buck‐boost converters
Authors: Zhang Da , Gu Yu , Zhang Donglai , Zhang Xiaofeng , Li Haijin , Li Anshou 
Published: August 2024

AbstractThe bidirectional DC‐DC conversion, as an important application scenario, places certain requirements on the topology structure. The four‐switch buck‐boost (FSBB) converter has received widespread attention due to its simple structure, flexible control and state switchability. However, the traditional control strategy makes it difficult to meet the requirements of high performance, high stability and high security at the same time. Furthermore, the control methods commonly adopted in domestic and international practical applications rely heavily on analogue control, which cannot maintain efficiency over a wide stability range. The use of digital control methods allows for optimized control algorithms, maintaining stable system operation and improving efficiency. Therefore, it is very important to use the digital control method to further improve the smoothness and steady‐state efficiency of the system multi‐mode switching while maintaining a wide input and output range, based on this, this study proposes two new three‐mode control modes: interleaved bias control mode and dual‐edge bias control mode.
Dynamical accretion flows
Authors: Wells M. R. A. , Beuther H. , Molinari S. , Schilke P. , Battersby C. , Ho P. , Sánchez-Monge Á. , Jones B. , Scheuck M. B. , Syed J. , Gieser C. , Kuiper R. , Elia D. , Coletta A. , Traficante A. , Wallace J. , Rigby A. J. , Klessen R. S. , Zhang Q. , Walch S. , Beltrán M. T. , Tang Y. , Fuller G. A. , Lis D. C. , Möller T. , van der Tak F. , Klaassen P. D. , Clarke S. D. , Moscadelli L. , Mininni C. , Zinnecker H. , Maruccia Y. , Pezzuto S. , Benedettini M. , Soler J. D. , Brogan C. L. , Avison A. , Sanhueza P. , Schisano E. , Liu T. , Fontani F. , Rygl K. L. J. , Wyrowski F. , Bally J. , Walker D. L. , Ahmadi A. , Koch P. , Merello M. , Law C. Y. , Testi L. 
Published: August 2024

Context. Investigating the flow of material along filamentary structures towards the central core can help provide insights into high-mass star formation and evolution.
Aims. Our main motivation is to answer the question of what the properties of accretion flows are in star-forming clusters. We used data from the ALMA Evolutionary Study of High Mass Protocluster Formation in the Galaxy (ALMAGAL) survey to study 100 ALMAGAL regions at a ∼1″ resolution, located between ∼2 and 6 kpc.
Methods. Making use of the ALMAGAL ∼1.3 mm line and continuum data, we estimated flow rates onto individual cores. We focus specifically on flow rates along filamentary structures associated with these cores. Our primary analysis is centered around position velocity cuts in H2CO (30, 3–20, 2), which allow us to measure the velocity fields surrounding these cores. Combining this work with column density estimates, we were able to derive the flow rates along the extended filamentary structures associated with cores in these regions.
Results. We selected a sample of 100 ALMAGAL regions, covering four evolutionary stages from quiescent to protostellar, young stellar objects (YSOs), and HII regions (25 each). Using a dendrogram and line analysis, we identify a final sample of 182 cores in 87 regions. In this paper, we present 728 flow rates for our sample (4 per core), analysed in the context of evolutionary stage, distance from the core, and core mass. On average, for the whole sample, we derived flow rates on the order of ∼10−4 M⊙ yr−1 with estimated uncertainties of ±50%. We see increasing differences in the values among evolutionary stages, most notably between the less evolved (quiescent and protostellar) and more evolved (YSO and HII region) sources and we also see an increasing trend as we move further away from the centre of these cores. We also find a clear relationship between the calculated flow rates and core masses ∼M2/3, which is in line with the result expected from the tidal-lobe accretion mechanism. The significance of these relationships is tested with Kolmogorov–Smirnov and Mann-Whitney U tests.
Conclusions. Overall, we see an increasing trend in the relationships between the flow rate and the three investigated parameters, namely: evolutionary stage, distance from the core, and core mass.
Introduction: explaining the far-right over the longue durée through capital, race and space
Authors: Saull Richard 
Published: August 2024

AbstractIn this forum introduction I outline the core argument of my book, Capital, Race, and Space (CRS) and its main empirical substance, and then I address how and why I came to write it and how the argument is important for considering the state of the world today. The two volumes of CRS provide the first international historical sociology of Western far-right movements from their emergence in the second half of the nineteenth century up until the far-right upsurge after the 2007–8 North Atlantic financial crisis.
Multiple Soliton Asymptotics in a Spin-1 Bose–Einstein Condensate
Authors: Lan 兰 Zhong-Zhou 中周 
Published: August 2024

Abstract
Spinor Bose–Einstein condensates (BECs) are formed when atoms in the multi-component BECs possess single hyperfine spin states but retain internal spin degrees of freedom. This study concentrates on a (1+1)-dimensional three-couple Gross–Pitaevskii system to depict the macroscopic spinor BEC waves within the mean-field approximation. Regarding the distribution of the atoms corresponding to the three vertical spin projections, a known binary Darboux transformation is utilized to derive the N matter-wave soliton solutions and triple-pole matter-wave soliton solutions on the zero background, where N is a positive integer. For those multiple matter-wave solitons, the asymptotic analysis is performed to obtain the algebraic expressions of the soliton components in the N matter-wave solitons and triple-pole matter-wave solitons. The asymptotic results indicate that the matter-wave solitons in the spinor BECs possess the property of maintaining their energy content and coherence during the propagation and interactions. Particularly, in the N matter-wave solitons, each soliton component contributes to the phase shifts of the other soliton components; and in the triple-pole matter-wave solitons, stable attractive forces exist between the different matter-wave soliton components. Those multiple matter-wave solitons are graphically illustrated through three-dimensional plots, density plot and contour plot, which are consistent with the asymptotic analysis results. The present analysis may provide the explanations for the complex natural mechanisms of the matter waves in the spinor BECs, and may have potential applications in designs of atom lasers, atom interferometry and coherent atom transport.
Single-crystal silicon ablation with temporally delayed femtosecond laser double-pulse trains
Authors: Fan Zhengjie , Yi Liangtian , Lv Jing , Wang Wenjun , Li Guoji , Cui Jianlei 
Published: August 2024

Abstract
A double-pulse femtosecond laser is used to process single-crystal silicon. Modulating the delay time was discovered to increase the ablation depth and improve the morphology of the ablated surface. The hole fabricated by a dual-pulse with a 200 ps interval is 24.4% deeper than that created by a single pulse of the same energy. Moreover, utilizing a dual pulse with an interval ranging from 100 to 1000 ps produces a considerably smoother ablation area as compared to the single pulse. The effect of the sub-pulse energy ratio of the double-pulse femtosecond laser on the size and morphology of the ablated area was also investigated. As the sub-pulse energy ratio decreases from 3:1 to 1:3, the size of the ablation area initially decreases and then increases, while the size of the ablation area is minimized when the sub-pulse ratio is 1:1, enabling precise control over the machining size. As the energy of the second sub-pulse increases, the ablation area becomes smoother due to the plasma heating of the double-pulse femtosecond laser.
Developing a BIM based digital twin system for structural health monitoring of civil infrastructure
Authors: Li Xiao , Dong Yu-Xia , Xiang Wei 
Published: August 2024

Abstract
The utilization of building information modeling (BIM) within digital technology facilitates the creation of three-dimensional representations for monitoring data in large-scale civil infrastructure. In response to the need for intelligent structural management, this study establishes a structural health monitoring (SHM) system and foundational framework based on digital twins. This framework integrates information from various sources and facilitates collaborative efforts for structural operation and maintenance. Additionally, the SHM system integrates actual monitoring measurements and early warning mechanisms to consolidate multi-source monitoring data with BIM. Through real-time analysis, the system provides insights into the operational status of bridges, capturing geometric, physical, and performance evolution characteristics. To construct the system, engineering challenges are initially digitized, with appropriate sensors deployed on real bridge structures to monitor dynamic (acceleration) and static (strain, displacement) physical information during bridge operation. Subsequently, through wireless communication and data storage technologies, the monitored physical data serves as input for mode identification and early warning algorithms, facilitating the acquisition of structural performance information. Finally, three-dimensional display technology enables real-time calculation and rendering of BIM models, fostering the exchange and interaction of monitoring and BIM information, thus enhancing the intelligence of SHM system.
Time-domain velocimetry via femtosecond laser electronic excitation tagging
Authors: Carter Douglas W , Beresh Steven J 
Published: August 2024

Abstract
The application is explored of a linear photodiode array with femtosecond laser electronic excitation tagging (FLEET) to determine the streamwise velocity of flow at Mach 8 in the Sandia hypersonic wind tunnel. Incident light emitted by nitrogen gas upon FLEET excitation is collected by intensifying optics that amplify and transmit the light to the photodiode elements as the gas advects downstream. In contrast to previous studies that track FLEET lines utilizing image sensors to measure the line displacement in space, instead for the first time the time-delay between the initial excitation and convection to the measurement location is used to determine the velocity temporally.
The fabrication of a thin film CoO-poly(1H-pyrrole)/poly(1H-pyrrole) p-type photocathode with intercalated chloride ions inside the polymer chains for the green hydrogen generation without sacrificing agent
Authors: Rabia Mohamed , Aldosari Eman , Fernández S , Moussa Mahmoud 
Published: August 2024

Abstract
This study proposes an innovative solution to the challenges associated with hydrogen (H2) gas generation by introducing a novel composite material composed of CoO-Co2O3-P1HP/P1HP. This composite is synthesized in a single step through the direct reaction of Co(NO3)2 with pyrrole. The resulting composite exhibits promising morphological characteristics, featuring small particle sizes of approximately 150 nm and notable porosity. This intricate porosity has a great role in facilitating the penetration of photons, enabling effective light absorption throughout the material. Moreover, the composite demonstrates exceptional optical properties, displaying high absorbance across the optical spectrum up to 830 nm, coupled with an optimal bandgap of 1.35 eV. Utilizing this composite as a photocathode in a fabricated three-electrode cell, the study explores the conversion of natural Red Sea water into H2 gas. The selection of this water as the electrolyte offers several advantages, including its cost-effectiveness, ready availability, and natural self-sacrificing properties. Experimental testing of the photocathode involves subjecting it to various optical conditions, including varying single photon energies and frequencies. Under white light, the photocathode exhibits a promising Jph value of −0.17 mA.cm−2, surpassing the Jo value of −0.03 mA.cm−2. This comprehensive evaluation provides insights into the performance of the photocathode under different illumination conditions. Furthermore, the study holds promise for commercial applications, as it presents a pathway for the large-scale conversion of Red Sea water into H2 gas, with a production rate of 10 μmole h−1.10 cm2. The availability of H2 gas as a clean and sustainable energy source holds significant potential for addressing energy needs in residential and remote areas, offering a viable alternative to conventional energy sources.
Sensitivity and reliability assessment of pocket doped NCFET based dielectrically modulated biosensor considering steric hindrance effects
Authors: Malvika  , Talukdar Jagritee , Choudhuri Bijit , Mummaneni Kavicharan 
Published: August 2024

Abstract
The paper explores the biosensing investigation of Highly Doped Double Pocket Double Gate Negative Capacitance Field Effect Transistor (HDDP-DG-NCFET) for the potent and label free detection of bio-molecules. The biosensing figure of merits (FoMs) such as threshold voltage sensitivity (∆Vth), ON–OFF current ratio sensitivity (∆ION/IOFF), intrinsic gain, drain current sensitivity (SId) and transconductance (gm) are computed for HDDP-DG-NCFET based biosensor. The study considers neutral, negatively (–NBio) and positively (+NBio) charged biomolecules at different dielectric materials such as air (ε
k = 1), 3-aminopropyl-triethoxysilane (APTES) (ε
k = 3.57), zein (ε
k = 5), keratin (ε
k = 8) and gelatin (ε
k = 12) at the immobilization layer. Additionally, an extensive analysis of a partially filled nanocavity triggered by steric hindrance has been presented to encompass the real-world situation and to comprehend the non-ideal behavior of biosensor. Various scenarios of partly occupied nano-cavities as well as asymmetric probe insertion have been accounted. The significant biosensing metrics such as ∆Vth, ∆ION/IOFF and SId are calculated and have ensuing values as 188 mV, 3 × 104 and 138, respectively. In addition, the maximum SID for fully filled nano-cavities (FF = 100%) in the existence of +NBio and -NBio (±5 × 1012) are 194 and 170, respectively for HDDP-DG-NCFET based biosensor. Finally, to illustrate the outstanding sensitivity of the proposed biosensor, various sensitivity metrics of the HDDP-DG-NCFET are compared to the sensitivities of cutting-edge biosensors which demonstrate HDDP-DG-NCFET as a potential contender for label free biosensor applications.
Design and implement a nested coexisting multi-vortex hyperchaotic system with multiple stability memristors
Authors: Zhang Jie , Wang Xinghao 
Published: August 2024

Abstract
This paper proposes a nested coexisting multi-vortex hyperchaotic system based on memristors. Analysis of the system’s equilibrium points, Lyapunov exponents and bifurcations, coexisting attractors, complexity, etc. The system has infinitely many equilibrium points, and the number of system vortices can be expanded with parameters. The most significant feature of this system is the existence of nested coexisting attractors and mega-stability phenomena. Additionally, it exhibits phenomena of homogeneous multi-stability, heterogeneous multi-stability, and extreme multi-stability. Further analysis was conducted on the relationship between these phenomena and the basins of attraction. Under certain parameters, the system (6) exhibits burst oscillations, transient chaos, and intermittent chaos, demonstrating diverse dynamic characteristics. To verify the feasibility of the system theory, design and build a simulation circuit using Multisim, and implement digital circuit simulation on FPGA. By realizing analog and digital circuits, further broaden its application value. Finally, the system is applied to adaptive synchronization and anti-synchronization. Simulation results indicate that the time required for achieving complete synchronization or complete anti-synchronization is shorter. This significant reduction in synchronization and anti-synchronization time not only enhances the system’s operational efficiency and performance but also strengthens its adaptability, thus carrying important theoretical and practical value for system applications.
BBN catalysis by doubly charged particles
Authors: Akhmedov Evgeny , Pospelov Maxim 
Published: August 2024

Abstract
We consider primordial nucleosynthesis in the presence of hypothetical
quasi-stable doubly charged particles. Existence of X
–– with
macroscopic lifetimes will lead to the formation of its bound states with
4He and other
light elements, significantly facilitating the subsequent
formation of lithium nuclei. From observational constraints on maximum
allowable amount of lithium, that we update in this work, we derive
strong constraints on the abundance and lifetime of X
––. In a
likely cosmological freeze-out scenario with temperatures initially
exceeding the mass of X
––, the BBN constrains the lifetime of these
particles to be less than about 100 seconds. For parametrically long
lifetimes, lithium abundance data constrain X
–– abundance to be less
than 10-9
relative to protons, regardless of whether these particles
decay or remain stable. Stable particles could saturate the dark matter
density only if their mass is comparable to or in excess of
1010 GeV, and most of X
–– will be found in bound states with
beryllium nuclei, so that chemically they would appear as abnormally
heavy helium isotopes.
Preheating with deep learning
Authors: Yoon Jong-Hyun , Cléry Simon , Gross Mathieu , Mambrini Yann 
Published: August 2024

Abstract
We apply deep learning techniques to the late-time turbulent regime in a post-inflationary model where a real scalar inflaton field and the standard model Higgs doublet interact with renormalizable couplings between them. After inflation, the inflaton decays into the Higgs through a trilinear coupling and the Higgs field subsequently thermalizes with gauge bosons via its SU(2)×U(1) gauge interaction. Depending on the strength of the trilinear interaction and the Higgs self-coupling, the effective mass squared of Higgs can become negative, leading to the tachyonic production of Higgs particles. These produced Higgs particles would then share their energy with gauge bosons, potentially indicating thermalization. Since the model entails different non-perturbative effects, it is necessary to resort to numerical and semi-classical techniques. However, simulations require significant costs in terms of time and computational resources depending on the model used. Particularly, when SU(2) gauge interactions are introduced, this becomes evident as the gauge field redistributes particle energies through rescattering processes, leading to an abundance of UV modes that disrupt simulation stability. This necessitates very small lattice spacings, resulting in exceedingly long simulation runtimes. Furthermore, the late-time behavior of preheating dynamics exhibits a universal form by wave kinetic theory. Therefore, we analyze patterns in the flow of particle numbers and predict future behavior using CNN-LSTM (Convolutional Neural Network combined with Long Short-Term Memory) time series analysis. In this way, we can reduce our dependence on simulations by orders of magnitude in terms of time and computational resources.