bluuebunny/crossref_metadata_2025 huggingface dataset:
A dual-biomimetic surface with leaf-skeleton-based hierarchical structures for efficient atmospheric water harvesting
Authors: Chen Qiyu , Medina Fabian Javier , Hao Qing
Published: January 2025

Atmospheric water harvesting (AWH) has been extensively researched as a sustainable solution to current freshwater scarcity. Various bioinspired AWH surfaces have been developed to enhance water-harvesting performance, yet challenges remain in optimizing their structures. In this work, we report a dual-biomimetic AWH surface that combines beetle-inspired heterogeneous wettability with leaf-skeleton-based hierarchical microstructures on a rigid substrate. An authentic leaf skeleton innovatively serves as the mask during photolithography complemented by O2-plasma treatment, enabling precise design of superhydrophilic SiO2 structures with a hierarchy of vein orders forming reticulate meshes on a hydrophobic Si substrate. This design facilitates enhanced water collection through intricate reticulate meshes and directional droplet transport along the abundant multi-order veins. Such AWH surface shows a water-harvesting efficiency of 172 mg cm−2 h−1, increasing up to 62% and 58% over the pristine SiO2/Si wafer and Si wafer, respectively. Additionally, the role of structure orientation in the open-surface droplet transport is explored while the AWH surface is vertically placed during the water-harvesting process. This work highlights the potential of using meticulous natural designs, like leaf skeletons, to improve AWH surfaces, with broad applications in compact devices, such as on-chip evaporative cooling and planar microfluidics manipulation.
Benchmark computations of nearly degenerate singlet and triplet states of N-heterocyclic chromophores. II. Density-based methods
Authors: Chanda Shamik , Saha Subhasish , Sen Sangita
Published: January 2025

In this paper, we demonstrate the performance of several density-based methods in predicting the inversion of S1 and T1 states of a few N-heterocyclic triangulene based fused ring molecules (popularly known as INVEST molecules) with an eye to identify a well performing but cost-effective preliminary screening method. Both conventional linear-response time-dependent density functional theory (LR-TDDFT) and ΔSCF methods (namely maximum overlap method, square-gradient minimization method, and restricted open-shell Kohn–Sham) are considered for excited state computations using exchange–correlation (XC) functionals from different rungs of Jacob’s ladder. A well-justified systematism is observed in the performance of the functionals when compared against fully internally contracted multireference configuration interaction singles and doubles and/or equation of motion coupled-cluster singles and doubles (EOM-CCSD), with the most important feature being the capture of spin-polarization in the presence of correlation. A set of functionals with the least mean absolute error is proposed for both the approaches, LR-TDDFT and ΔSCF, which can be more cost-effective alternatives for computations on synthesizable larger derivatives of the templates studied here. We have based our findings on extensive studies of three cyclazine-based molecular templates, with additional studies on a set of six related templates. Previous benchmark studies for subsets of the functionals were conducted against the domain-based local pair natural orbital-similarity transformed EOM-CCSD (STEOM-CCSD), which resulted in an inadequate evaluation due to deficiencies in the benchmark theory. The role of exact-exchange, spin-contamination, and spin-polarization in the context of DFT comes to the forefront in our studies and supports the numerical evaluation of XC functionals for these applications. Suitable connections are drawn to two and three state exciton models, which identify the minimal physics governing the interactions in these molecules.
Prediction of neuronal functionality of asymmetric ferroelectric tunneling junction with coupled polarization and thermal dynamics
Authors: Tang Zhenxun , Liu Linjie , Zhang Jianyuan , Chen Weijin , Zheng Yue
Published: January 2025

The performance of neuromorphic computing (NC) in executing data-intensive artificial intelligence tasks relies on hardware network structure and information processing behavior mimicking neural networks in the human brain. The functionalities of synapses and neurons, the key components in neural networks, have been widely pursued in memristor systems. Nevertheless, the realization of neuronal functionalities in a single memristor remains challenging. By theoretical modeling, here we propose asymmetric ferroelectric tunneling junction (AFTJ) as a potential platform to realize neuronal functionalities. The volatility, a necessary property for a memristor to implement a neuron device, is enhanced by the co-effect of polarization asymmetry and Joule heating. The simulated polarization reversal dynamics of the AFTJ memristor under trains of electric pulses reproduces the leaky integrate-and-fire functionality of spiking neurons. Interestingly, multiple spiking behaviors are found by modulating the pulse width and interval of trains of electric pulses, which has not yet been reported in ferroelectric neuron. The influences of several key factors on the neuronal functionalities of AFTJ are further discussed. Our study provides a novel design scheme for ferroelectric neuron devices and inspires further explorations of ferroelectric devices in neuromorphic computing.
Accuracy of approximate methods for the calculation of fluorescence-type linear spectra with a complex system–bath coupling
Authors: Nöthling J. A. , Mančal Tomáš , Krüger T. P. J.
Published: January 2025

Much can be learned about molecular aggregates by modeling their fluorescence-type spectra. In this study, we systematically describe the accuracy of various methods for simulating fluorescence-type linear spectra in a dimer system with a complex system–environment interaction, which serves as a model for various molecular aggregates, including most photosynthetic light-harvesting complexes (LHCs). We consider the approximate full cumulant expansion (FCE), complex time-dependent Redfield (ctR), time-independent Redfield, and modified Redfield methods and calculate their accuracy as a function of the site energy gap and coupling, excitonic energy gap, and dipole factor (i.e., type of spectrum). We find that the FCE method is the most accurate method for couplings smaller than 300 cm−1 at 300 K, but this method fails for very strong couplings or low temperatures due to inaccurate modeling of the equilibrium initial state. The ctR method performs well for the calculation of fluorescence and linear anisotropy spectra but poorer for circularly polarized fluorescence spectra or for all spectra when the coupling is strong (∼100cm−1). The Redfield and modified Redfield methods generally perform much more poorly than the ctR and FCE methods—especially for small excitonic energy gaps and strong couplings. We show that accurate modeling of the Stokes shift is crucial and present a version of the ctR method that treats both the Stokes shift and initial state correctly for the parameter ranges in plant LHCs. Apart from the application to LHCs, our results will be useful for the spectral characterization and design of organic molecular aggregates.
Electric dipole moment of excited octupolar molecules: Potential qubit implementation
Authors: Ivanov Anatoly I.
Published: January 2025

The first excited state of conjugated donor–acceptor molecules of C3 symmetry (octupolar molecules) is doubly degenerate. Such a doublet is known to be isomorphic to a spin 1/2. It is shown that a large electric dipole moment is associated with this spin. Since the mean value of the electric dipole moment of an octupolar molecule is a measure of the symmetry breaking charge transfer, a dimensionless dipole moment called the dissymmetry vector is introduced. The dissymmetry vector operator is constructed. A linear tensor connection between this operator and the Pauli matrices is found. The tensor character is due to the two-dimensionality of the dipole moment. The dipole moment can rotate freely in the plane of the molecule as long as the C3 symmetry is maintained. The rotation is associated only with the rearrangement of the electronic subsystem of the molecule and does not affect the spatial position of the nuclei. This opens up the possibility of changing the dipole moment state on a subpicosecond time scale. The Jahn–Teller effect on the dissymmetry vector is considered in detail. It is shown that the dissymmetry vector can be controlled using electric fields in the same way as three-dimensional spin if both static and alternating electric fields are in the plane of the molecule. The conducted studies indicate that the dipole moment of excited octupolar molecules is a promising candidate for the physical implementation of a qubit.
Restoring rotational symmetry of multicomponent wavefunctions with nuclear orbitals
Authors: Moncada Félix , Reyes Andrés , Pettersson Lars G. M.
Published: January 2025

In this work, we present a non-orthogonal configuration interaction (NOCI) approach to address the rotational corrections in multicomponent quantum chemistry calculations where hydrogen nuclei and electrons are described with orbitals under Hartree–Fock (HF) and density functional theory (DFT) frameworks. The rotational corrections are required in systems such as diatomic (HX) and nonlinear triatomic molecules (HXY), where localized broken-symmetry nuclear orbitals have a lower energy than delocalized orbitals with the correct symmetry. By restoring rotational symmetry with the proposed NOCI approach, we demonstrate significant improvements in proton binding energy predictions at the HF level, with average rotational corrections of 0.46 eV for HX and 0.23 eV for HXY molecules. For computing rotational excitation energies, our results indicate that HF kinetic energy corrections are consistently accurate, while discrepancies arise in total energy predictions, primarily from an incomplete treatment of dynamical correlation effects. Rotational energy corrections in multicomponent DFT calculations, using the epc17-2 proton–electron correlation functional, lead to an overestimation of proton binding energies. This is as a result of double-counting of proton–electron correlation effects in the off-diagonal NOCI terms. As a correction, we propose a scaling scheme that effectively adjusts the proton–electron correlation contributions, bringing our results into close agreement with reference CCSD(T) data. The scaled rotational corrections, on average, increase the epc17-2 proton binding energy predictions by 0.055 eV for HX and 0.025 eV for HXY and yield average deviations of 1.0 cm−1 for rotational transitions.
Biodegradable Tenebrio molitor antifreeze protein modified kinetic hydrate inhibitor: Insights into molecular interactions and structural flexibility
Authors: Zhang Nan , Huang Hui-Yi , Li Yan-Nan , Zhang Li-Rong , Liu Jun-Jie
Published: January 2025

The formation of natural gas hydrates presents significant economic and safety challenges to the petroleum and gas industry, necessitating the development of effective prevention strategies. This study investigates an environmentally sustainable Tenebrio molitor antifreeze protein (TmAFP) modified to be a potential kinetic hydrate inhibitor. The aim of this study was to enhance the inhibitory activity of TmAFP by systematically substituting threonine (Thr) residues with glycine (Gly), alanine (Ala), or serine (Ser) at positions 29, 39, and 53. The Ala mutant demonstrated superior inhibition of hydrate formation, attributed to its optimized spatial conformation and enhanced hydrophobic interactions, followed by the Gly and Ser mutants. The wild-type TmAFP showed limited efficacy. The radial distribution function (RDF) analysis indicated that the mutations facilitated a better accommodation of adjacent residues within the hydrate crystal structure by adjusting the distance between Thri and Thri+2 to closely match the second peak in the RDF of methane molecules at 6.4 Å. The potential of mean force (PMF) calculations revealed that the Ala and Ser mutants exhibited enhanced interactions with hydrate cages, with PMF values of −0.73 and −0.71 kJ/mol, respectively, compared to the Gly mutant, which had a PMF value of 1.46 kJ/mol. By identifying the optimal mutation combination (T29 39 53A) to significantly increase the potency of TmAFP, this study provides a fundamental basis for the further development of hydrate inhibition strategies.
Numerical study on the effect of rim seal slot filleting on turbine endwall cooling
Authors: Li Xinchun , Wei Na , Shi Liuliu , Chen Eryun
Published: January 2025

In this study, the effect of rim seal slot filleting on turbine endwall film cooling performance is numerically investigated. For comparison with the baseline case, five different fillet radius and width (R/W) ratios are adopted, i.e., R/W = 1.25, 2.5, 3.75, 5, and 6.25. The results indicate that an improvement up to 10% in overall film cooling effectiveness can be achieved with smaller fillet radii. However, this effect diminishes as the fillet radius increases and becomes negative at R/W = 6.25. By examining the contours of the film cooling effectiveness, a prominent inclined strip can be observed across the blade passage. The analysis indicates that the pressure-side leg horseshoe vortex is the primary factor contributing to the variation in the film cooling performance. Furthermore, the film cooling effectiveness can be slightly improved near the suction side of the blade leading edge as the result of the suppression of endwall separation in this region. The rim seal slot filleting eliminates the slot leakage separation, which, in turn, expedites the endwall cooling flow. Eventually, pressure-side leg horseshoe vortex is weakened and the performance of the film cooling is improved. As the fillet radius continues to increase, the through-flow area for the cooling flow enlarges, resulting in a gradual decrease in the film cooling performance.
Static deep stall analysis augmented by numerically constrained turbulent flows
Authors: D'Afiero Francesco Mario
Published: January 2025

As computational resources have advanced, scale-resolving methods like large eddy simulation (LES) have gained popularity in the aerodynamic design particularly in predicting massively separated flow regions. The limitations of traditional Reynolds-averaged Navier–Stokes (RANS) are evident in this regime, given the importance of the intrinsic unsteadiness and the strong three-dimensionality of the flow. This research focuses on wall-resolved implicit large eddy simulation (ILES) for airfoil flows in deep stall with a focus on its dynamics. Moreover, it is also of interest to understand how the spanwise extent of the computational domain affects the resolved aerodynamic forces and flow dynamics. The simulations in this study analyzed various spanwise extents (lz ranging from 0.10c to 2c) under specific conditions: a chord Reynolds number Re=105, an asymptotic Mach number M∞=0.15, and an angle of attack α = 20 degrees. Significant differences were found in aerodynamic coefficients and flow dynamics when the smallest spanwise extent was used. Specifically, spectral proper orthogonal decomposition showed that a small span failed to capture critical low-frequency dynamics necessary for predicting adequate stall behavior. Additionally, the turbulence field in the small span case remained largely rod-like, unlike the three-dimensional turbulence seen in larger spans. The current work propose the nondimensional spanwise integral length scale (SILS/lz) as a metric for determining the sufficiency of spanwise extent, using two-point correlations for the streamwise velocity. Findings suggest that a spanwise extent of lz=1c is sufficient, with minimal differences observed between lz=1c and lz=2c. The results emphasize the importance of adequate spanwise resolution to accurately capture deep-stall flow structures and their unsteady behavior.
Representing Ireland and the Irish in the 17th- and 18th-century English press
Authors: Claridge Claudia
Published: January 2025

The treatment of Ireland in the London press from 1640 to 1800 is investigated with the help of the
ZEN and Lampeter corpora, following up on De
Nie’s (2004) hypothesis that views of the Irish could have functioned as a foil for creating a British
identity. Mentions of the Irish and Irish affairs matters are not only very infrequent, but also are of a nature to
deny agency to the Irish. Within this picture of discursive neglect, apparently based on true English disinterest,
three aspects stand out, which partly contribute to (unsystematic) othering: (i) Irish Catholicism, styled as hostile
to Britain, (ii) a set of mocking stereotypes, and (iii) Ireland seen as subservient to the economic interests of
England.
Revolutionary news
Authors: Dooley Brendan , Boerio Davide
Published: January 2025

News travelled quickly during the troubled 1640s in Europe and had almost palpable effects. But how
did news travel, and who got it first? Weekly handwritten newsletters transmitted from sites of crisis to the Tuscan
Grand Ducal court and elsewhere, are a still under-used source. This chapter analyses the similarities and differences
between weekly handwritten news reporting about two places, London and
Naples, both of which experienced regime-changing commotions in the 1640s, among others similarly afflicted at the
time. More concretely, we will be comparing and contrasting these two cases of popular unrest resulting in the
creation of new forms of government, and the linguistic ramifications of this in the realms of diction, word usage,
sentiment and sense of belonging.
Revising the Algemene Nederlandse Spraakkunst
Authors: Dhondt Arne , Colleman Timothy , Caluwe Johan De
Published: January 2025

The third, fully revised version of the Algemene Nederlandse Spraakkunst (ANS), the main reference grammar of Dutch, aims to describe grammatical variation in the national standard varieties of Dutch. This paper investigates whether this pluricentric perspective is compatible with the geographical distribution patterns of Dutch grammatical variants. We provide an overview of the distribution patterns described in the second edition of the ANS and we check this description against frequency data from newspaper corpora for four selected variants which represent different distribution patterns. Although the observed distribution patterns do not always coincide with national borders, we argue that the pluricentric model does not (necessarily) conflict with linguistic reality and that it is the appropriate choice to meet the needs of Dutch language users.
Parametric level-sets enhanced to improve reconstruction (PaLEnTIR)
Authors: Ozsar Ege , Kilmer Misha , de Sturler Eric , Saibaba Arvind K , Miller Eric
Published: January 2025

We introduce parametric level-set enhanced to improve reconstruction (PaLEnTIR), a significantly enhanced parametric level-set (PaLS) method addressing the restoration and reconstruction of piecewise constant objects. Our key contribution involves a unique PaLS formulation utilizing a single level-set function to restore scenes containing multi-contrast piecewise constant objects without requiring knowledge of the number of objects or their contrasts. Unlike standard PaLS methods employing radial basis functions (RBFs), our model integrates anisotropic basis functions (ABFs), thereby expanding its capacity to represent a wider class of shapes. Furthermore, PaLEnTIR streamlines the model by reducing redundancy and indeterminacy in the parameterization, resulting in improved numerical performance. We compare PaLEnTIR’s performance to state-of-the art alternatives via a diverse collection of experiments encompassing denoising, deconvolution, sparse and limited angle of view x-ray computed tomography (2D and 3D), and nonlinear diffuse optical tomography tasks using both real and simulated data sets.
Computational prediction of novel two-dimensional tungsten nitride superconductors
Authors: Hernández-Tecorralco J , Ríos-Ramírez J J , Olea-Amezcua M A
Published: January 2025

Transition metal nitrides are well-known 3D superconductor materials. However, there is a lack of knowledge related to their two-dimensional (2D) counterparts, which have several potential technological applications. In this work, we predict, using an evolutionary algorithm coupled with a first-principles approach, a set of novel 2D superconductive structures based on tungsten nitride. Through a systematic process including energetic and dynamical analysis, three thermodynamically stable compositions along with metastable compounds were studied in the following stoichiometries: W4N2, W2N2, and W2N3. Their superconductive temperature (

T

c

) values, estimated by means of the Eliashberg superconductive theory and the McMillan equation, range from 2.3 to 21.6 K, where the highest

T

c

value corresponds to a W2N3 metastable hexagonal system. A systematic analysis of the structural, electronic, vibrational and electron–phonon (e–ph) properties, allowed us to recognize the variables that modulate the

T

c

in theses systems. The superconductive behavior is strongly affected by changes in the nitrogen density of states at Fermi level, the e–ph coupling constant and the lattice symmetry. The present results aim to encourage further theoretical and experimental efforts over non fully explored superconductors in two dimensions.
Lightweight multi-scale encoder– decoder network with locally enhanced attention mechanism for concrete crack segmentation
Authors: Dong Shuai , Cao Jin , Wang Yunlong , Ma Jia , Kuang Zhiwei , Zhang Zhenhao
Published: January 2025

Concrete surface crack detection and maintenance are crucial for ensuring structural safety. Deep learning-based techniques for detecting concrete cracks have become popular due to the quick advancement of artificial intelligence. However, the actual uses of these methods are limited due to issues like large model sizes and significant dependence on powerful computing hardware. To address these issues, this paper presents a lightweight multi-scale encoder–decoder network (LMED-Net) for crack detection of concrete structures. LMED-Net employs MobileNetV2 as the encoder for the initial feature extraction. A multi-scale feature extraction (MFE) module is developed and serially attached after the encoder for refining feature extraction. Finally, to strengthen the network’s perception of pixels surrounding the cracks, a novel enhanced attention mechanism (EAM) is deployed in the decoder. By improving the network’s attention to information within the crack regions, this mechanism keeps contextual information from being lost. Comparative experimental results show that the proposed network achieves an F1 score (F1) of 60.32% and a mean intersection over union (mIoU) of 71.04% on the crack forest dataset. On the DeepCrack dataset, the F1 and mIoU increase to 79.09% and 81.85% respectively. Notably, LMED-Net performs exceptionally well in crack segmentation since its model size and parameters count are much smaller than those of other image segmentation methods. Furthermore, ablation studies further validate the effectiveness of the proposed MFE module and EAM.
A precision method for measuring large-diameter, high-gradient surface profiles using a chromatic confocal sensor and mirror assembly
Authors: Yang Zhipeng , Wang Wei , Huang Daixin , Jiao Sicheng , Xu Min
Published: January 2025

High-gradient surfaces with large diameters are extensively utilized in various fields such as high-performance optical systems and aerospace engineering. Accurate measurement technologies are crucial to ensure that the machining precision of these surfaces meets application requirements. However, the need for sensor rotation axes and coupling devices imposes many limitations on current technologies and equipments when measuring these types of surfaces. To address this issue, this paper proposes an optical measurement method using a chromatic confocal sensor (CCS) and a mirror assembly that eliminates the need for rotation axes and coupling devices. This method deflects the optical path of the CCS by translating mirrors with different inclinations and achieves measurement of the entire surface using a four-axis system. This method lowers both the cost and complexity of the system, reduces potential error sources, and streamlines the measurement process. An experimental measurement of a hemispherical shell was conducted, resulting in a maximum deviation of 0.858 μm for the profiles reconstructed by the proposed system, compared to those obtained from the LUPHOScan260. The verification result demonstrates the feasibility and effectiveness of this method.
Hybrid contrastive representations and SBO-based samples generation for rotating machinery anomaly detection based on driven-end current signal
Authors: Lin Weiqi , Zhang Shaohui , Li Tao , Jiang Fei , Wu Zhaoqian , Zhong Zhi
Published: January 2025

While deep learning methods based on cross-entropy function have made great advancements in maintaining equipment reliability, their learning paradigm appears less suitable for anomaly detection tasks, which focus on extracting specific target features and ignore the discriminability between classes. Besides, incomplete dataset still hinders the robustness of intelligent detection models, especially when the training dataset only contains normal samples. Therefore, a hybrid contrastive representation and soft Brownian offset (SBO)-based samples generation (HCRS) method based on driven-end current signals is proposed to distinguish normal and abnormal samples in incomplete data scenarios where only normal signals are available. In the proposed HCRS detection framework, an autoencoder is initially trained using only normal current samples. It is then combined with the SBO method to generate abnormal samples, relieving the issues of incomplete dataset. Subsequently, a supervised contrastive learning-based deep feature extractor is trained using both the generated abnormal samples and the collected normal samples. This process aims to learn high-level fine-grained representations with discriminability. Finally, these learned representations are utilized to train a data-driven classifier, enabling effective anomaly detection in rotating machinery. In addition, experiments on two datasets suggest that the proposed HCRS can effectively achieve higher accuracy anomaly detection with only normal current signals and outperform existing detection approaches.
Spin-momentum locking as a source of spin-splitting anisotropy in inverted HgTe quantum wells
Authors: Kubisa Maciej , Ryczko Krzysztof
Published: January 2025

We show theoretically that Rashba spin–orbit coupling in gated heterostructures results in strong anisotropy of electron spin splitting. A simple analytical expression for the splitting energy is derived and shown to be in excellent agreement with multiband numerical calculations. Moreover, our theory successfully explains recent experimental results for inverted HgTe quantum wells.
Consequences of non-Markovian healing processes on epidemic models with recurrent infections on networks
Authors: Carlos M Silva José , Silva Diogo H , Rodrigues Francisco A , Ferreira Silvio C
Published: January 2025

Infectious diseases are marked by recovering time distributions which can be far from the exponential one associated with Markovian/Poisson processes, broadly applied in epidemic models. In the present work, we tackled this problem by investigating a susceptible-infected-recovered-susceptible model on networks with η independent infectious compartments (SI

η

RS), each one with a Markovian dynamics, that leads to a Gamma-distributed recovering time. We analytically develop a theory for the epidemic lifespan on star graphs with a center and K leaves, which mimic hubs on networks, showing that the epidemic lifespan scales with a non-universal power-law. Compared with standard susceptible-infected-recovered-susceptible dynamics, the epidemic lifespan on star graphs is severely reduced as the number of stages increases. In particular, the case

η
→
∞

leads to a finite lifespan. Numerical simulations support the approximated analytical calculations. We investigated the SI

η

RS dynamics on random power-law networks. When the epidemic processes are ruled by a maximum k-core activation, either the epidemic threshold or the epidemic localization pattern are unaltered. When hub mutual activation is at work, the localization is reduced but not sufficiently to alter the threshold scaling with the network size. Therefore, the activation mechanisms remain the same as in the case of Markovian healing.
Numerical simulation of type II primordial black hole formation
Authors: Uehara Koichiro , Escrivà Albert , Harada Tomohiro , Saito Daiki , Yoo Chul-Moon
Published: January 2025

This study investigates the formation of primordial black holes (PBHs) resulting from extremely large amplitudes of initial fluctuations in a radiation-dominated universe.
We find that, for a sufficiently large initial amplitude, the configuration of trapping horizons shows characteristic structure due to the existence of bifurcating trapping horizons.
We call this type of configuration of the trapping horizons type B PBH, while the structure without a bifurcating trapping horizon type A PBH.
As shown in ref. [1], in the matter-dominated universe, the type B PBH can be realized by the type II initial fluctuation, which is characterized by a non-monotonic areal radius as a function of the radial coordinate (throat structure) in contrast with the standard case, type A PBH with a monotonic areal radius (type I fluctuation).
Our research reveals that a type II fluctuation does not necessarily result in a type B PBH in the radiation-dominated case.
We also find that for an initial amplitude well above the threshold value, the resulting PBH mass may either increase or decrease with increasing the initial amplitude, depending on
its specific profile rather than its fluctuation type.
Auxiliary-field Monte Carlo method for frustrated spin systems
Authors: Cai 蔡 Ning 凝 , Gao 高 Yuan 源 , Li 李 Wei 伟 , Qi 戚 Yang 扬
Published: January 2025

We extend a semiclassical numerical method, bosonic auxiliary-field Monte Carlo, to quantum spin systems. This method breaks the lattice into clusters, solves each cluster precisely and couples them with classical auxiliary fields through classical Monte Carlo simulation. We test the method with antiferromagnetic spin models in one-dimensional chains, square lattices and triangular lattices, and obtain reasonable results at finite temperatures. This algorithm builds a bridge between classical Monte Carlo method and quantum methods. The algorithm can be improved with either progress in classical Monte Carlo sampling or the development of quantum solvers, and can also be further applied to systems with different lattices or interactions.
Atelocollagen-based hydrogel loaded with Cotinus coggygria extract for treatment of type 2 diabetic wounds
Authors: Yilmaz Ozdogan Candan , Kenar Halime , Uzuner Huseyin , Karadenizli Aynur
Published: January 2025

Diabetes, a chronic metabolic disease, causes complications such as chronic wounds, which are difficult to cure. New treatments have been investigated to accelerate wound healing. In this study, a novel wound dressing from fibroblast-laden atelocollagen-based hydrogel with Cotinus coggygria extract was developed for diabetic wound healing. The antimicrobial activity of C. coggygria hexane (H), dichloromethane (DCM), dichloromethane:methanol (DCM-M), methanol (M), distilled water (DW) and traditional (T) extracts against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Enterococcus faecalis and Candida albicans, as well as their cytotoxic effects on fibroblasts were determined. While fibroblast growth was significantly (p< 0.05) promoted with DCM (121.41 ± 1.04%), M (109.40 ± 5.89%) and DW (121.83 ± 6.37%) extracts at their lowest concentrations, 2000 μg ml−1 DCM and 7.8 μg ml−1 T extracts had both non-cytotoxic and antifungal effects. An atelocollagen-based hydrogel was produced by thermal crosslinking, and its pore size (38.75 ± 7.67 μm), water content (96.63 ± 0.24%) and swelling ratio (27.21 ± 4.08%) were found to be suitable for wound dressings. A significant increase in the deoxyribonucleic acid amount (28.27 ± 1.41%) was observed in the plain hydrogel loaded with fibroblasts after 9 d of incubation, and the hydrogel had an extensively interconnected cellular network. The hydrogels containing DW and T extracts were applied to wounds generated in an in vitro 3D type-2-diabetic human skin model. Although the incubation period was not sufficient for closure of the wounds in either of the treatments, the hydrogel with T extract stimulated more fibroblast migration. In the fibroblast-laden version of the hydrogel with T extract, no wound closure was observed but more keratinocytes migrated to the wound region. These positive outcomes underline the potential of the developed wound dressing as a powerful alternative to improve diabetic wound healing in clinical practice.
Non-Markovian reduced models to unravel transitions in non-equilibrium systems
Authors: Chekroun Mickaël D , Liu Honghu , McWilliams James C
Published: January 2025

This work proposes a general framework for analyzing noise-driven transitions in spatially extended non-equilibrium systems and explaining the emergence of coherent patterns beyond the instability onset. The framework relies on stochastic parameterization formulas to reduce the complexity of the original equations while preserving the essential dynamical effects of unresolved scales. The approach is flexible and operates for both Gaussian noise and non-Gaussian noise with jumps. Our stochastic parameterization formulas offer two key advantages. First, they can approximate stochastic invariant manifolds when these manifolds exist. Second, even when such manifolds break down, our formulas can be adapted through a simple optimization of its constitutive parameters. This allows us to handle scenarios with weak time-scale separation where the system has undergone multiple transitions, resulting in large-amplitude solutions not captured by invariant manifolds or other time-scale separation methods. The optimized stochastic parameterizations capture then how small-scale noise impacts larger scales through the system’s nonlinear interactions. This effect is achieved by the very fabric of our parameterizations incorporating non-Markovian (memory-dependent) coefficients into the reduced equation. These coefficients account for the noise’s past influence, not just its current value, using a finite memory length that is selected for optimal performance. The specific memory function, which determines how this past influence is weighted, depends on both the strength of the noise and how it interacts with the system’s nonlinearities. Remarkably, training our theory-guided reduced models on a single noise path effectively learns the optimal memory length for out-of-sample predictions. This approach retains indeed good accuracy in predicting noise-induced transitions, including rare events, when tested against a large ensemble of different noise paths. This success stems from our hybrid approach, which combines analytical understanding with data-driven learning. This combination avoids a key limitation of purely data-driven methods: their struggle to generalize to unseen scenarios, also known as the ‘extrapolation problem.’
Boundary Bethe ansatz in massless AdS3
Authors: Bielli Daniele , Moustakis Vasileios , Torrielli Alessandro
Published: January 2025

We construct the boundary algebraic Bethe ansatz for the

A
d

S
3

×

S
3

×

T
4

integrable reflection problem restricted to the massless sector. We derive the double-row monodromy and find the appropriate formulation of the dual equation of Sklyanin’s. We perform the algebraic Bethe ansatz and obtain the RTT (more properly RTRT) relations, from which the spectrum is obtained by repeated action of the B operator on the pseudovacuum. We obtain the Bethe equations by cancelling the unwanted terms, and prove the exact formulae for any number of quantum particles and magnonic excitations.
Learning to classify quantum phases of matter with a few measurements
Authors: Khosrojerdi Mehran , Pereira Jason L , Cuccoli Alessandro , Banchi Leonardo
Published: January 2025

We study the identification of quantum phases of matter, at zero temperature, when only part of the phase diagram is known in advance. Following a supervised learning approach, we show how to use our previous knowledge to construct an observable capable of classifying the phase even in the unknown region. By using a combination of classical and quantum techniques, such as tensor networks, kernel methods, generalization bounds, quantum algorithms, and shadow estimators, we show that, in some cases, the certification of new ground states can be obtained with a polynomial number of measurements. An important application of our findings is the classification of the phases of matter obtained in quantum simulators, e.g. cold atom experiments, capable of efficiently preparing ground states of complex many-particle systems and applying simple measurements, e.g. single qubit measurements, but unable to perform a universal set of gates.
Human motor performance assessment with lower limb exoskeletons as a potential strategy to support healthy aging—a perspective article
Authors: Moeller Tobias , Beyerlein Melina , Herzog Michael , Barisch-Fritz Bettina , Marquardt Charlotte , Dežman Miha , Mombaur Katja , Asfour Tamim , Woll Alexander , Stein Thorsten , Krell-Roesch Janina
Published: January 2025

With increasing age, motor performance declines. This decline is associated with less favorable health outcomes such as impaired activities of daily living, reduced quality of life, or increased mortality. Through regular assessment of motor performance, changes over time can be monitored, and targeted therapeutic programs and interventions may be informed. This can ensure better individualization of any intervention approach (e.g. by considering the current motor performance status of a person) and thus potentially increase its effectiveness with regard to maintaining current performance status or delaying further decline. However, in older adults, motor performance assessment is time consuming and requires experienced examiners and specific equipment, amongst others. This is particularly not feasible in care facility/nursing home settings. Wearable robotic devices, such as exoskeletons, have the potential of being used to assess motor performance and provide assistance during physical activities and exercise training for older adults or individuals with mobility impairments, thereby potentially enhancing motor performance. In this manuscript, we aim to (1) provide a brief overview of age-related changes of motor performance, (2) summarize established clinical and laboratory test procedures for the assessment of motor performance, (3) discuss the possibilities of translating established test procedures into exoskeleton-based procedures, and (4) highlight the feasibility, technological requirements and prerequisites for the assessment of human motor performance using lower limb exoskeletons.
Ultrafast laser welding of transparent materials: from principles to applications
Authors: Jia Xianshi , Luo Jinlin , Li Kai , Wang Cong , Li Zhou , Wang Mengmeng , Jiang Zhengyi , Veiko Vadim P , Duan Ji’an
Published: January 2025

The ultrafast laser-matter interaction is explored to induce new pioneering principles and technologies into the realms of fundamental science and industrial production. The local thermal melting and connection properties of the ultrafast laser welding technology offer a novel method for welding of diverse transparent materials, thus having wide range of potential applications in aerospace, opto-mechanical systems, sensors, microfluidic, optics, etc. In this comprehensive review, tuning the transient electron activation processes, high-rate laser energy deposition, and dynamic evolution of plasma morphology by the temporal/spatial shaping methods have been demonstrated to facilitate the transition from conventional homogeneous transparent material welding to the more intricate realm of transparent/metal heterogeneous material welding. The welding strength and stability are also improvable through the implementation of real-time, in-situ monitoring techniques and the prompt diagnosis of welding defects. The principles of ultrafast laser welding, bottleneck problems in the welding, novel welding methods, advances in welding performance, in-situ monitoring and diagnosis, and various applications are reviewed. Finally, we offer a forward-looking perspective on the fundamental challenges within the field of ultrafast laser welding and identify key areas for future research, underscoring the imperative need for ongoing innovation and exploration.
Biofabrication of brain-like living tissue: structure to intelligence
Authors: Wang Ling , Wang Sen , Liu Yingjie , Zhang Bowen , Pan Zhaoyu , Bai Luge , Yao Siqi , Zhang Chenrui , Xie Huangfan , He Jiankang , Li Dichen
Published: January 2025

Brain, the material foundation of human intelligence, is the most complex tissue in the human body. Brain diseases are among the leading threats to human life, yet our understanding of their pathogenic mechanisms and drug development remains limited, largely due to the lack of accurate brain-like tissue models that replicate its complex structure and functions. Therefore, constructing brain-like models—both in morphology and function—possesses significant scientific value for advancing brain science and pathological pharmacology research, representing the frontiers in the biomanufacturing field. This review outlines the primary requirements and challenges in biomanufacturing brain-like tissue, addressing its complex structures, functions, and environments. Also, the existing biomanufacturing technologies, strategies, and characteristics for brain-like models are depicted, and cutting-edge developments in biomanufacturing central neural repair prosthetics, brain development models, brain disease models, and brain-inspired biocomputing models are systematically reviewed. Finally, the paper concludes with future perspectives on the biomanufacturing of brain-like tissue transitioning from structural manufacturing to intelligent functioning.
Graphene quantum dots as hole transport material in lead free perovskite solar cell: a SCAPS-1D numerical study
Authors: Amanullah Saifee Md , Khan Fareha Feroz Alam , Ali Javid , Khan Mohammad Ajmal , Khan Mohd Shahid
Published: January 2025

The environment friendly, lead-free perovskite materials show significant promise for high-performance solar cells. We have conducted numerical simulations of the proposed solar cell structure using SCAPS-1D software. The analysed solar cell structure comprises of FTO/ZnO/MASnI3/GQD/C, where FTO serves as the transparent conducting oxide, ZnO as the electron transport layer (ETL), methylammonium tin iodide (MASnI3; MA = CH3NH3) as the absorbing material, graphene quantum dots (GQDs) as the hole transport layer (HTL), and carbon as the back contact. In this study, we examined various factors influencing solar cell performance, including thickness, Mott- Schottky and shallow acceptor density of the absorber layer. Additionally, we analysed the band energy, defect density at the GQD/MASnI3 and MASnI3/ZnO interfaces, carrier generation, recombination, and concentrations throughout the device layers. The optimized solar cell structure demonstrated an efficiency of 10.57%, a short-circuit current density of 34 mA cm−12, an open-circuit voltage of 0.9 V, and a fill factor of 88%. These simulation results could provide valuable guidelines for fabricating higher-efficiency, low-cost solar cells.
Land-use and land-cover changes and emerging non-tuberculous and tuberculous infectious diseases in humans and animals: a mixed-methods review of research findings from global and spatio-temporal perspectives
Authors: Guégan Jean-François , Vargas Campos Carlos A , Chevillon Christine , Sylla Ahmadou , Dogbe Magdalene , Fast Kayla M , Pechal Jennifer , Rakestraw Alex , Scott Matthew E , Sandel Michael W , Jordan Heather , Benbow M Eric
Published: January 2025

Despite recent interest in land-use and land-cover (LULC) change effects on emerging infectious diseases (EIDs), the debate on global potential health threats remains polarizing. These depend on diverse LULC changes, different types of infectious disease systems, and spatio-temporal scales of studies. Here, using both a bibliometric and scoping review method, we summarize the reliability and availability of published relevant studies on LULC effects on mycobacteria, an important group of infectious bacteria that affect humans and both wild and domestic animals. We make connections of LULC with environmental changes (e.g. soils) that likely lead to an increased risk of mycobacteria spillover to human and other animal populations. An important feature of our review is a focus on research from the richest countries of the world, though some studies have been done in Africa, Asia and South America. Geographically, regions experiencing important LULC transformations, such as many tropical regions of Meso- and South America and Southeast Asia, have been given little or no attention in this important topic. Research on Mycobacterium bovis, and to a larger extent on M. ulcerans, constitutes convincing illustrations of the importance of acknowledging shifts in spatio-temporal scales, from local to global and inter-annual to decadal ones, when evaluating responses of mycobacteria to LULC changes. However, studies on other pathogenic mycobacteria remain very much confined to local and dispersed scales. To date, the role of LULC change effects has not been adequately studied for many human and animal pathogens, and more research and attention to this issue is clearly needed. This review provides a comprehensive set of data on the updates of LULC change and their impact on animal and human mycobacterial infections. It also proposes several research recommendations, in particular to better understand the emergence of mycobacteria in context, by multiplying study sites in different regions of the world and in adopting an ecosystem-based perspective, in order to encourage interdisciplinary research better linking environmental microbiology, veterinary science and medical research.
Weather resilience of the future Swiss electricity system with very high shares of variable renewable energy sources
Authors: Killenberger Collin , Zielonka Nik , Sasse Jan-Phillipp , Trutnevyte Evelina
Published: January 2025

To design weather-resilient electricity systems that rely on variable renewable energy sources (VRES), spatially-explicit modeling with several decades of historical weather data is necessary to avoid over-optimization to a single weather year. Here, we apply the electricity system model EXPANSE for Switzerland to search for resilient cost-optimal and near-optimal system designs in 2035 under various policy scenarios, using data from 25 historical weather years (1995–2019) for electricity demand, solar photovoltaics (PV), wind power, hydropower dams and run-of-river hydropower. In particular, we demonstrate how modeling to generate alternatives (MGA) could be used to define a range of potential system designs for reaching different levels of weather resilience. We find that solar PV capacity of 35 GW in Switzerland in 2035 without any wind power would allow the country to reach its target of 35 TWh yr−1 on new renewable electricity in 95% of the 25 historical weather years. Further limiting winter electricity import to a maximum of 5 TWh yr−1 as currently envisioned by policy, would require additional 10 GW of wind power to have a comparable level of weather resilience. Within the range of alternative MGA scenarios, such 95% resilience level could also be achieved using 12 GW of solar PV and 18 GW of wind power, 20 GW of solar PV and 13.5 GW of wind power. This methodology could be transferred to other countries and continents that intend to reach high shares of VRES in their electricity systems.