bluuebunny/crossref_metadata_2025_split huggingface dataset:
Magnetotransport and Fermi surface segmentation in Pauli limited superconductors
Authors: Karmakar Madhuparna 
Published: January 2024

Abstract
We report the first theoretical investigation of the spectroscopic, electrical and optical transport signatures of d-wave Pauli limited superconductors, based on a non perturbative numerical approach. We demonstrate that the high magnetic field low temperature regime of these materials host a finite momentum paired superconducting phase. Multi-branched dispersion spectra with finite energy superconducting gaps, anisotropic segmentation of the Fermi surface and spatial modulations of the superconducting order characterizes this finite momentum paired phase and should be readily accessible through angle resolved photo emission spectroscopy, quasiparticle interference and differential conductance measurements. Based on the electrical and optical transport properties we capture the non Fermi liquid behavior of these systems at high temperatures, dominated by local superconducting correlations and characterized by resilient quasiparticles which survive the breakdown of the Fermi liquid description. We map out the generic thermal phase diagram of the d-wave Pauli limited superconductors and provide for the first time the accurate estimates of the thermal scales corresponding to the: (a) loss of (quasi) long range superconducting phase coherence (T
c), (b) loss of local pair correlations (T
pg), (c) breakdown of the Fermi liquid theory (T
max) and cross-over from the non Fermi liquid to the bad metallic phase (T
BR). Our thermal phase diagram mapped out on the basis of the spectroscopic and transport properties are found to be in qualitative agreement with the experimental observations on CeCoIn5 and κ-BEDT, in terms of the thermodynamic phases and the phase transitions. The results presented in this paper are expected to initiate important transport and spectroscopic experiments on the Pauli limited d-wave superconductors, providing sharp signatures of the finite momentum Cooper paired state in these materials.
Symmetry-enforced fourfold degenerate phonons in noncentrosymmetric space groups
Authors: Li Zehou , Pan Baoru , Zhou Pan , Kang Ruirong , He Shenda , Peng Xiangyang , Sun Lizhong 
Published: January 2024

Abstract
Multifold degenerate phonons have received much attention due to their nontrivial monopole topological charge and fascinating boundary states. Although Yu et al recently provides a comprehensive list of all potential nodal points for systems with specific space groups (SGs) (2022 Sci. Bull.
67 375). However, our understanding of the fundamental mechanisms that give rise to the formation of fourfold-degenerate (FD) phonons is still limited. In this paper, we have directed our research towards investigating the generation mechanism of these FD phonons in noncentrosymmetric SGs. Using symmetry arguments and

k
⋅

p

model analysis, we have classified them into two categories: the first origins from the commutation/anticommutation relation of the little cogroup operations, and the second associates to the combination of threefold rotation, mirror and time-reversal symmetries. Moreover, the band dispersions of the FD phonons in the first group are required to be linear, whereas the band dispersions of the FD phonons in the second category may be quadratic. On the basis of first-principles calculations, we propose that K

2

Mg2O3 and Na

4

SnSe4 are representative candidates for the two categories, respectively. Furthermore, for each SG with fourfold degenerate phonons, we propose corresponding materials that must host the FD points. Our work not only deepens our understanding of the mechanisms underlying the formation of these FD phonons, but it also proposes practical materials for observing FD phonons in crystalline systems without inversion symmetry.
Phase transitions, conductance fluctuations and distributions in disordered topological insulator stanene
Authors: Liu Wenchao , Luo Chaobo , Peng Xiangyang 
Published: January 2024

Abstract
It is essential to understand to what extent the protected edge states of topological insulators (TIs) can survive against the degradation of the ubiquitous disorders in realistic devices. From a different perspective, disorders can also help to enrich the applications by modulation of the phases in TIs. In this work, the phases and phase transitions in stanene, a two-dimensional TI, have been investigated via the statistical approach based on the random matrix theory. Using a tight binding model with Aderson disorder term and the Landauer–Büttiker formalism, we calculated the conductance of realistic stanene ribbons of tens of nanometers long with random disorders. The calculated phase diagram presents TI in the gap, metal in high energy and ordinary insulator in large disorder region. Increasing the width of the ribbon can significantly enhance the robustness of TI phase against disorders. Due to different underlying symmetries, the metallic phase can be further categorized into unitary and orthogonal classes according to the calculated universal conductance fluctuations. The local density of states is calculated, showing characteristic patterns, which can facilitate the experimental identification of the phases. It is found that different phases have distinguishing statistical distribution of conductance. Whereas at the phase boundary the distribution exhibits intermediate features to show where the phase transition occurs. To reveal the phase evolution process, we further studied the effects of the disorders on respective transmission channels. It is found that when phase transition takes place, the major transmission channels of the old phase are fading and the new channels of the new phase are emerging.
Adaptive rotating machinery fault diagnosis method using MKIST
Authors: Yi Jiliang , Tan Huabing , Yan Jun , Chen Xin 
Published: January 2024

Abstract
An adaptive fault diagnosis method for rotating machinery based on maximum kurtosis incomplete S-transform is proposed in this paper. Firstly, the incomplete S-transform is performed on the fault frequency band of the vibration signal, and the module vector group is obtained through module calculation. Subsequently, the kurtosis of all the modulus vectors are calculated and the vector corresponding to the maximum kurtosis is located to adaptively determine the envelope of the fault frequency component in the vibration signal. Then, fast Fourier transform is performed on the envelope to obtain its main frequency, which is matched with the fault mode frequency to achieve fault diagnosis of rotating machinery. Finally, the mean peak ratio (MPR) was used to evaluate the performance of different methods under various operating conditions. The results show that the maximum MPR is obtained by the proposed method, demonstrating its stronger noise resistance and demodulation ability.
Traceable frequency measurements with counters
Authors: Piester Dirk , Staliuniene Egle , Bauch Andreas 
Published: January 2024

Abstract
Received signals from Global Navigation Satellite Systems (GNSS) are nowadays widely used by industry laboratories for ensuring metrological traceability for their respective range of calibration services in the field of time and frequency. Usually, a local frequency standard is steered by continuous GNSS signal reception providing at its output stable and accurate reference signals for the laboratory measurement equipment, in general for synthesizers and counters. Reception of GNSS signals is surely an adequate and practical tool for the purpose, however further steps are needed to establish traceability in a strict metrological sense. Based on already available guidelines and publications, this paper is a contribution to the discussion how metrological traceability to internationally accepted standards can be established in a calibration laboratory. We restrict the discussion to equipment in common use which may not necessarily be of the highest sophistication. In this spirit, we develop a detailed scheme for an uncertainty budget comprising all links of the traceability chain from the device under test to the SI second, the scale-unit of Coordinated Universal Time. Then we go through and apply this scheme step by step to a demonstration setup for frequency measurements with a counter with varying operational parameters. In this framework, a novel approach to distinguish between components of statistical measurement uncertainty is introduced. Furthermore, the limiting uncertainty contributions are discussed and based on a suitable set of parameters an expression for the best measurement capability is given. With this scheme at hand a user may develop an uncertainty budget adapted to his own setup, especially if acceptance from a national accreditation body is sought.
A steel surface defect detection model based on graph neural networks
Authors: Pang Wenkai , Tan Zhi 
Published: January 2024

Abstract
Steel is an indispensable raw material in the construction industry. To avert catastrophic events such as building collapse, it is essential to detect minute defects on steel surfaces during production. However, this has been a persistent challenge due to the minuscule and dense nature of these defects. To this end, we propose an efficient defect detector called Vision Grapher with Hadamard, which employs a novel attention mechanism (HDmA) to establish local-to-local relationships within an image and integrates global relationships by graph convolution. With the HDmA module, we can not only fuse information under the same field of view, but also under different fields of view, which significantly enhances the richness of the acquired features. In addition, compared to convolutional neural networks, graph neural networks can utilize the contextual information in the image more effectively and resulting in better performance. We evaluate our model on the NEU-DET and GC-10 benchmark datasets, which encompass six and ten types of defects on the surfaces of hot-rolled and cold-rolled steel, and our model achieves a mean average precision of 79.04% and 66.93% on the two datasets, respectively. The results demonstrate that our model significantly improves the accuracy of defect detection compared to existing methods.
A novel deep learning algorithm applied to machine vision inspection for surface defects of injection moulded products
Authors: Fan Haipeng , Qiu Zhongjun 
Published: January 2024

Abstract
In modern industry, the surface defect inspection of injection moulded products is crucial for controlling product quality and optimising the manufacturing process. With the development of optical measurement and computer technology, machine vision inspection methods have been widely adopted instead of manual inspection. However, current machine vision inspection methods are difficult to simultaneously ensure the accuracy and efficiency of surface defect inspection of injection moulded products. Considering this problem, a novel deep learning algorithm applied to machine vision inspection for surface defects of injection moulded products is proposed. To train and evaluate the proposed deep learning algorithm, an image acquisition platform is established and the dataset of surface defects in moulded products is obtained. In the proposed deep learning algorithm, reparameterisation-based convolution modules are employed for feature extraction and feature fusion. A median iterative clustering algorithm based on hierarchical clustering initialisation is proposed to obtain prior anchors that are highly matched with the actual distribution of defect sizes. A novel focus-entire union over covering loss function is utilised for bounding box regression. On these bases, the proposed deep learning algorithm applied to machine vision inspection is evaluated on the dataset of surface defects in moulded products. The experimental results indicate that compared to the traditional inspection algorithms and other deep learning algorithms currently used in machine vision inspection, the proposed deep learning algorithm exhibits superior inspection accuracy and inspection efficiency on the acquired dataset. The inspection precision reaches 0.964, the inspection recall reaches 0.955, and the inference time for each subgraph is only 6.1 ms, confirming its effectiveness.
Streamer-induced kinetics of excited states in pure N2: II. Formation of N2(B 3Πg,v=0–21
) through analysis of emission produced by the first positive system
Authors: Bílek Petr , Dias Tiago Cunha , Prukner Václav , Guerra Vasco , Šimek Milan 
Published: January 2024

Abstract
Vibrational distributions of electronically excited states of N2 obtained through dipole-allowed radiative transitions provide an important tool to study the kinetics of non-equilibrium plasmas under various discharge conditions. In this work, we report, for the first time, streamer-induced visible/near-infra-red emission spectra developing during the first hundred nanoseconds after the initiation of the discharge. Emission through the first positive system of N2 was acquired in 500–1100 nm range, which allows a complete analysis of the N2(B

3

Π

g

,
v

= 0–21) vibrational manifold. The investigated evolution of the vibrational distribution of the N2(B

3

Π

g

, v = 0–21) state at the centre of the gap corresponds to the transition of the streamer head and the subsequent decay of the streamer channel. We show that the vibrational distribution characterising streamer head is determined by Franck–Condon factors, while during streamer relaxation, it is influenced by the complex interaction between triplet excited states of N2. Additionally, the observed N2(B

3

Π

g

, v = 13–21) vibrational levels are likely produced by the interaction of high vibrational levels of N2(W

3

Δ

u

, B’

3

Σ

u

−

, B

3

Π

g

)

with

N

2

(

C

3

Π

u

)

state. We also provide a detailed kinetic scheme for modelling vibrationally-resolved N2(B

3

Π

g

) state and compare model results with experimental outcomes.
Experimental tests and numerical simulations of miniature buckling-restrained braces using iron-shape memory alloy bar
Authors: Wang Yuanzuo , Jiang Tianyuan , Qiu Canxing , Zhang Aifang , Liu Jiawang , Du Xiuli 
Published: January 2024

Abstract
Miniature buckling-restrained braces (BRBs) have a concise configuration and clear working mechanism. Owing to stable and full hysteresis, miniature BRBs are emerging as favorable energy-dissipating fuse elements in seismic applications. This paper proposes using iron-shape memory alloy (FeSMA) in lieu of conventional steel as the yielding core and focuses on the cyclic behavior. Four specimens, corresponding to four loading protocols, were fabricated and tested. According to experimental data, the miniature FeSMA BRBs exhibited full hysteresis, which is characterized by large damping, noticeable isotropic and kinematic hardening behavior and appreciable post-yield stiffness ratio. The cumulative plastic deformations meet the requirement by ANSI/AISC 341-16. Further, high fidelity finite element models, which explicitly considered damage and fracture rules, were established for numerical simulations. Good agreement can be found between the experimental data and numerical simulations, in terms of failure modes, fracture locations and global hysteresis.
Investigation of healing electronic pressure-sensitive soft switch based on liquid metal microfiber
Authors: Ren Yijun , Wen Xiaolong , Bian Hairui 
Published: January 2024

Abstract
Flexible and wearable electronics have gained extensive attention in health monitoring, electronic skin, and sensors due to their flexibility, portability, sensitivity, and biocompatibility. Liquid metal (LM) is an optimum conductive material for soft electronic devices because of its high conductivity and fluidity at room temperature. Nevertheless, LM electronic devices with stable dimension is a formidable challenge due to its relatively high surface tension and mass density. In this study, we introduce a wet spinning approach that utilises sodium alginate as the exterior phase and LM as the interior phase. Calcium lactate is used to solidify the sodium alginate, thereby producing liquid metal microfibers (LMMs). The LMMs can be modified by adjusting the flow rate of the two-phase materials. The encapsulated LM microcapsule can serve as a healing electronic soft switch that is suitable for use in wearable and flexible electronic devices. Initially, the liquid metal soft switch (LMSS) has a high resistance value. Once a specific amount of pressure is applied, the resistance value drops considerably resulting in the switch’s activation. And LMMs coated by the sodium alginate can dissolve in a trisodium citrate solution, so that the LM can be reshaped under mixed each other. It achieves LMSS’s reusability and recycling.
Design and integration of textile-based temperature sensors for smart textile applications
Authors: Rasheed Abher , Imran Aqsa , Abrar Amna , Zaman Shahood uz 
Published: January 2024

Abstract
Wearable technology is now frequently utilized to check people’s health. Body temperature measurements needed for telemedicine and real-time health monitoring applications can be taken with wearable temperature sensors. The goal of this work was to create thermocouples made of textiles for use in smart textile applications, particularly temperature monitoring in outfield uniforms. The thermocouples were created using metal wire and conductive yarns; however, metal-based thermocouples were only created for reference. In these studies, three junction levels and three distinct materials were used, and the Seebeck coefficient for these samples was examined. A four-probe heating system coupled with a multimeter was used to calculate the Seebeck coef-ficient. Results show that the cotton-based conductive yarn thermo-couple with stainless steel yarn (C + SS2) junction performed well with the best Seebeck coefficient value. The thermocouple values with one, five, and ten junctions were sequentially 167.56 µv °C−1, 227.30 µv °C−1, and 267.54 µv °C−1. After the integration, ten junction thermocouples of C + SS2 showed the best Seebeck coefficient values.
Breaking reflection symmetry: evolving long dynamical cycles in Boolean systems
Authors: Ouellet Mathieu , Kim Jason Z , Guillaume Harmange , Shaffer Sydney M , Bassett Lee C , Bassett Dani S 
Published: January 2024

Abstract
In interacting dynamical systems, specific local interaction rules for system components give rise to diverse and complex global dynamics. Long dynamical cycles are a key feature of many natural interacting systems, especially in biology. Examples of dynamical cycles range from circadian rhythms regulating sleep to cell cycles regulating reproductive behavior. Despite the crucial role of cycles in nature, the properties of network structure that give rise to cycles still need to be better understood. Here, we use a Boolean interaction network model to study the relationships between network structure and cyclic dynamics. We identify particular structural motifs that support cycles, and other motifs that suppress them. More generally, we show that the presence of dynamical reflection symmetry in the interaction network enhances cyclic behavior. In simulating an artificial evolutionary process, we find that motifs that break reflection symmetry are discarded. We further show that dynamical reflection symmetries are over-represented in Boolean models of natural biological systems. Altogether, our results demonstrate a link between symmetry and functionality for interacting dynamical systems, and they provide evidence for symmetry’s causal role in evolving dynamical functionality.
Large-scale geometry of the Universe
Authors: Awwad Yassir , Prokopec Tomislav 
Published: January 2024

Abstract
The large scale geometry of the late Universe can be decomposed
as ℝ × Σ3, where ℝ
stands for cosmic time and Σ3 is the three dimensional
spatial manifold.
We conjecture that the geometry of the Universe's spatial
section Σ3
conforms with the Thurston-Perelman theorem,
according to which the geometry of Σ3 is either one of the
eight geometries from the Thurston geometrization conjecture,
or a combination of Thurston geometries smoothly sewn together.
We assume that topology of individual geometries plays
no observational role, i.e. the size of individual
geometries is much larger than the Hubble radius today.
We investigate the dynamics of each of the individual
geometries by making use of the simplifying assumption
that our local Hubble patch consists of only one such geometry,
which is approximately homogeneous on very large scales,
but spatial isotropy is generally violated.
Spatial anisotropies grow in time in decelerating universes, but they
decay in accelerating universes. The thus-created anisotropy problem can be solved
by a period of primordial inflation, akin to how the flatness problem is solved.
Therefore, as regards Universe's large scale geometry,
any of the Thurston's geometries should be considered on a par with
Friedmann's geometries.
We consider two observational methods that can be used to test our conjecture: one based on
luminosity distance and one on angular diameter
distance measurements,
but leave for the future their detailed forecasting implementations.
A new strategy for the determination of dinobuton fungicide by square wave stripping voltammetry on the multi-walled carbon nanotube electrode
Authors: Murathan Zeynep , İnam Recai , Demir Ersin 
Published: January 2024

Abstract
Dinobuton is a fungicide with a dinitrophenol group pesticide, and its electrochemical behavior was investigated by cyclic voltammetry (CV) and square wave stripping voltammetry (SWSV) on a multi-walled carbon nanotube paste electrode (MWCNTPE). First of all, optimum parameters such as pH, step potential, frequency, puls amplitude, deposition time and, deposition potential were specified by using SWSV on the MWCNTPE. In the negative potential scans, two cathodic peaks appeared at nearly −480 mV and –760 mV due to the nitro groups on the molecule and the second sharp one appeared at −760 mV (versus Ag/AgCl) was used for analytical purposes. The linear working range was found to be within 3.74–25.8 μM on the MWCNTPE by SWSV in pH 7.0 Britton Robinson (BR) buffer solution. The limit of detection (LOD) and limit of quantification (LOQ) values were found to be 0.73 μM and 2.43 μM, respectively. The interference study was conducted in the presence of some pesticides such as triasulfuron, azinphos-methyl, bromoxynil-octanoate, dialifos, fipronil, vinclozolin, iprodione, procymidone, and some selected metal ions withal. Furthermore, the proposed method was also applied to apple juice, tap water, and grape juice, and percent recoveries (%) were detected as 105.9 ± 4.3; 98.3 ± 0.9; 103.7 ± 2.5% with relative standard deviations of 4.0, 1.0, and 2.4%, respectively. On the other hand, percent relative errors were calculated as 5.90, 1.65, and 3.74%, respectively. High recoveries and low relative standard deviations indicate that the applicability of the proposed method in both matrix and real samples is satisfying.