bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating temperature-induced torque noise of a torsion pendulum based on temperature modulation at different frequencies
Authors: Long Teng-Yu , Lu Zhi-Jie , Wang Yu-Xiang , Qiao Min-Na , Liu Qi , Xue Chao , Tan Wen-Hai , Yang Shan-Qing
Published: November 2023

Torsion pendulums are widely used for the measurement of small forces. In this study, we investigated the impact of temperature fluctuations on a torsion pendulum using heating devices to modulate the environmental temperature at different specific frequencies. The response coefficient between the temperature variation and the torque of the torsion pendulum was found to vary at different frequencies, with values from 4 × 10−15 N mK−1 at 0.1 mHz to 3 × 10−13 N mK−1 at 10 mHz. A passive thermal-insulation system was used to reduce the torque response within this frequency band, which is dominated by temperature noise. The results demonstrate that this modulation method provides a useful way to independently investigate the noise in a torsion pendulum resulting from environmental temperature fluctuations over a wide frequency band.
Advances in polymerized small-molecule acceptors for improved performance in all-polymer solar cells
Authors: Khelifi Wissem , Luscombe Christine K.
Published: November 2023

This mini-review discusses the progress made in the development of polymerized small-molecule acceptors (PSMAs) for use in all-polymer solar cells (all-PSCs). These PSMAs combine the advantages of both small-molecule acceptors (SMAs) and polymers. Various studies have been conducted using different building blocks to synthesize these acceptors, including indacenodithiophene and indacenodithienothiophene. They exhibit many advantages such as strong absorption in the near infrared region, high electron mobility, and appropriate energy levels, making them good candidate for PSAMs. The improved efficiency of all-PSCs is attributed to several factors, including stronger absorption, improved blend morphology, and redistribution of composition in the film. Additionally, new materials have been incorporated as third components in ternary organic photovoltaics, with some achieving high power conversion efficiencies of up to 17.0%. The development of new acceptors with different building blocks has resulted in improved stability and reproducibility in all-PSCs, paving the way toward high-performance and stable devices. Overall, these developments demonstrate significant potential for further advancements in the field.
Study on impact of gap difference on plasma distribution of direct current vacuum circuit breaker with double-break
Authors: Huang Chongyang , Yin Yongshuai , Liu Shuxin , Du Hanwen , Shan Zengyu , Cao Yundong
Published: November 2023

During the fault current breaking process of a mechanical direct current vacuum circuit breaker (DC VCB) with double-break (DB), the mechanism’s dispersion can result in a gap difference between the two breaks. A DB DC VCB breaking experiment platform is constructed in order to investigate the impact of gap difference on plasma distribution during the DB DC VCB breaking process. During the experiment, a high-speed camera is used to capture the vacuum arcing process at the two breaks under varying gap difference conditions. Then, the arc feature parameters and their variations during the zero-zone process are extracted using image processing techniques, and the distribution patterns of plasma and arc energy at the two breaks are analyzed and compared. When there is no gap difference between the two breaks of the experimental DB DC VCB, there are no significant differences in arc energy and the sizes of high-, medium-, and low-temperature plasma zones between the two breaks. When there is a gap difference between two breaks, the break with the smaller gap has larger high and medium-temperature plasma zones, more concentrated arc energy, higher particle concentration, lower arc diffusion velocity and arc energy decay velocity, and a greater amount of residual plasma after the extinguishing of the arc. When the gap difference exceeds a certain threshold, energy spots appear on the contact surfaces, and a high concentration corridor of residual particles remains between the contacts after the current crosses zero, forming a breakdown weak point that eventually leads to arc re-ignition (hence interruption failure) under the action of transient recovery voltage.
Zombie cats on the quantum–classical frontier: Wigner–Moyal and semiclassical limit dynamics of quantum coherence in molecules
Authors: Green Austin T. , Martens Craig C.
Published: November 2023

In this paper, we investigate the time evolution of quantum coherence—the off-diagonal elements of the density matrix of a multistate quantum system—from the perspective of the Wigner–Moyal formalism. This approach provides an exact phase space representation of quantum mechanics. We consider the coherent evolution of nuclear wavepackets in a molecule with two electronic states. For harmonic potentials, the problem is analytically soluble for both a fully quantum mechanical description and a semiclassical description. We highlight the serious deficiencies of the semiclassical treatment of coherence for general systems and illustrate how even qualitative accuracy requires higher order terms in the Moyal expansion to be included. The model provides an experimentally relevant example of a molecular Schrödinger’s cat state. The alive and dead cats of the exact two-state quantum evolution collapse into a “zombie” cat in the semiclassical limit—an averaged behavior, neither alive nor dead, leading to significant errors. The inclusion of the Moyal correction restores a faithful simultaneously alive and dead representation of the cat that is experimentally observable.
Self-consistent study of tearing mode with finite current gradient in the resistive-inertial and viscous-resistive regimes
Authors: Huang Wenlong , Wang Zihan , Yang Mingwei
Published: November 2023

Via the two-field reduced magneto-hydrodynamics model, a self-consistent theory of tearing mode evolution is developed to study the stability of tearing mode in the resistive-inertial and viscous-resistive regimes. Based on the series expansion method, we obtain a closed system for tearing mode evolution with the finite current gradient (FCG) effect. Solving the closed system with correlated approximations, the dispersion relation of tearing mode with FCG in the resistive-inertial and resistive-viscous regimes is derived and discussed. Self-consistent calculations adopted in this work show that assumptions used in previous studies are not always appropriate. Furthermore, deviation from those assumptions provides a non-negligible effect to the stability of tearing mode.
A study on the extension of correlation functions obtained from molecular dynamics simulations by the Ornstein–Zernike theory for modeled molten salts
Authors: Miyata Tatsuhiko , Funahara Yu , Omori Seiya , Shinjo Taro
Published: November 2023

We extend the correlation functions obtained by molecular dynamics (MD) simulation for a molten salt modeled as a superposition of the Lennard-Jones (LJ) and Coulomb potentials using the hybrid closure method, which employs the Ornstein–Zernike (OZ) theory coupled with a closure relation. An appropriate distance for switching the short-range MD part and the long-range OZ part is determined by monitoring the isothermal compressibility, excess internal energy, and pressure. The Kobryn–Gusarov–Kovalenko (KGK) closure relation is mainly employed for the hybrid closure method (MD–KGK hybrid closure). The hybrid closure with either the hypernetted chain (HNC) or Kovalenko–Hirata (KH) closure was also tested to confirm that the performance was almost equivalent to one another among the MD–HNC, MD–KH, and MD–KGK methods. The bridge function for the model molten salt is extracted using the MD–KGK hybrid closure method. At a high-density state, the bridge function shows a steep increase in the repulsive core region, as is often observed for simple fluids, whereas when the density is relatively low, the bridge function for the cation–anion pair shows a downward-sloping behavior. Furthermore, the accuracies of excess internal energy, pressure, and isothermal compressibility were also examined for the HNC, KH, and KGK approximations. For molten salt systems, these approximations exhibited a similar behavior to those for monatomic LJ fluids, especially in the high-density state. The analysis of the integrand for excess internal energy and pressure is also discussed.
Characterising earth scent
Authors: Busby Ryan R. , Conrady Morgan W. , Jo Kyoo D. , Cropek Donald M.
Published: November 2023

Environmental context Everyone is familiar with the earth odour that comes from digging in the soil. We measured the chemicals comprising this odour and studied how the environment influences how much of these chemicals are released from disturbed soils. Understanding what conditions affect emission of these compounds from soils could provide new technologies for remotely assessing soil health and what people are doing to soils. Rationale Earth scent is the odour emitted from soils. This scent, primarily comprising the alcohols geosmin and 2-methylisoborneol (MIB), has not been fully characterised, but offers high potential for use as an environmental interrogation tool. Methodology We utilised our field-based, solid-phase microextraction fibre method to test the hypothesis that soil activity and soil property variation can be detected in situ by comparing biogenic volatile emissions. Results We eliminated sources of error utilising field-based sampling with these fibres, concluding that room temperature storage for up to 7 days is acceptable with minimal loss. Variation in individual fibre affinity for both compounds was higher than expected but no measured concentrations were observed to constitute outliers. Disturbance of minor soil volumes led to significantly higher emission of both compounds over background levels. Soil texture and soil cover had a significant effect on the emission of both compounds. Simulated rainfall, producing the characteristic odour known as petrichor, initiates elevated emission of geosmin. Background (undisturbed soil) concentrations of MIB were occasionally detectable during some sampling events, but geosmin concentrations in the air were always below detection limits without soil disturbance. Virtually all background and disturbed soil samples contained much higher concentrations of MIB compared to geosmin, but geosmin variation between replicates and experimental units was much lower. Discussion Soil disturbance and soil property variation can be remotely detected using emission of volatile compounds. Correlating emission from the soil with respect to disturbance events and environmental properties could yield a powerful new tool for acquiring soil information.
Laboratory benchmark of low-cost portable gas and particle analysers at the source of smouldering wildfires
Authors: Cui Wuquan , Dossi Simona , Rein Guillermo
Published: November 2023

Background Smouldering wildfires emit large amounts of carbon, toxic gases and particulate matter (PM), posing health and environmental hazards. It is challenging to conduct field measurements on wildfire emissions, and available instruments are limited by high cost and low mobility. Aim Here, we contribute to solving this challenge by studying three commercial low-cost and portable air quality analysers (KANE101, SDS011 and FLOW) and comparing them with research-grade instruments (FTIR, PM Cascade Impactor and DustTrak). Methods A series of laboratory experiments on peat smouldering were conducted including the stages of ignition, spread and burnout to provide conditions of emission measurements near the source. Key results The gas analyser KANE101 accurately measured CO2 and allowed calculation of modified combustion efficiency (MCE). The FLOW air pollution sensor was found unsuitable for PM measurements near fire sources because of its narrow range. FLOW captured the variation of volatile organic compounds (VOCs), but measurements did not correlate well with NO2 measurements. The SDS011 PM sensor responded well in measuring PM10 in this study. Conclusions KANE101 and SDS011 can be used in the field after calibration to measure CO2/CO and PM. Implications This work provides a better understanding of how low-cost and portable emission sensors can be of use for wildfire measurements in the field.
Enregistering Grammatical Gender: Indexing Brabantishness through Languagecultural Practices in Digital Tiles
Authors: Doreleijers Kristel
Published: November 2023

In the southern Dutch province of North Brabant, local dialect use is declining sharply. Dialect leveling and loss lead to convergence to standard Dutch, and simultaneously to divergence that is reflected in increasing variation, that is, hyperdialectisms. This can be clearly observed in morphosyntactic features such as the adnominal masculine gender suffix -e(n). The current study investigates the sociolinguistic enregisterment of this suffix in 336 multimodal “tiles” with Brabantish aphorisms and jokes on Instagram. Based on digital and interview data, it shows how linguistic structure, situated use, and metalinguistic awareness (i.e., Silverstein’s total linguistic fact) are constantly interrelated. It is argued that the gender suffix acquires indexical social meaning at the expense of grammatical function, as its (hyperdialectal) use becomes associated with and recognizable for a place-based identity (“Brabantishness”). This research offers insights into how this meaning-making process is enhanced by co-occurring linguistic and nonlinguistic resources in mediated “languagecultural” practices.
Instability enhanced thermalization of bi-Maxwellian EEDF in multi-dipole confined hot cathode discharge: an experimental observation
Authors: Jiang Di , Yip Chi-Shung , Jin Chen-Yao , Zhang Wei , Wang Liang , Xu Guo-Sheng
Published: November 2023

In multi-dipole confined hot cathode discharges, the presence of up to three distinct electron species has been observed by performing linear fitting of the Langmuir probe I–V traces. Nevertheless, the fundamental mechanism underlying the generation of hot electrons remains ambiguous. This work presents experimental observations to comprehensively investigate the impact of the instability-enhanced thermalization effect on the thermal equilibrium of both hot and cold electrons. Temperature composition of the electron energy distribution function (EEDF) was measured via a Langmuir probe, while instabilities was measured using a spectrum analyzer. The experimental results confirm the existence of a transition from a three-temperature Maxwellian EEDF composition to a two-temperature Maxwellian EEDF composition as the population of high-energy electrons increases. Furthermore, the process of thermalization between hot and cold electrons is found to be correlated to the effect of instability-enhanced collisions. The intensity of collisional instability also decreases with increased neutral collisionality.
Effect of ambient argon pressure on the structural, optical and electrical properties of non-crystalline Se85Te3Bi12 nano-thin films
Authors: Srivastava Aditya , Khan Zishan H , Khan Shamshad A
Published: November 2023

In this research work, we have synthesized non-crystalline Se85Te3Bi12 chalcogenide glasses by conventional melt quenching technique. The differential scanning calorimetry measurement of the synthesized specimen was done to confirm the glassy as well as non-crystalline nature of the bulk Se85Te3Bi12 alloy. The nano-thin films of thickness 30 nm of the synthesized sample at two different ambient argon pressures (1 Torr and 3 Torr) were made using the physical vapor condensation technique at a constant substrate temperature of 77 K using liquid nitrogen. The non-appearance of prominent peaks in the high-resolution x-ray diffractometer profile confirmed the non-crystalline nature of synthesized nano-thin films. The morphological analysis of the prepared nano-thin films using Field emission scanning electron microscopy confirmed the nanochalcogenide having particle size ranges from 30–90 nm. The Fourier transform infrared (FTIR) spectroscopy suggests the presence of moisture and carbon impurities in the prepared nano-thin films. The broad optical transmission shadow observed in the FTIR results is an essential requirement for new-generation IR systems. Based on UV-visible spectroscopy, optical parameters such as optical absorption coefficients, Urbach energy, optical band gaps, Tauc’s parameter and extinction coefficients were measured for synthesized Se85Te3Bi12 nano-thin films. The value of absorption coefficients, Tauc’s parameters, optical band gap and extinction coefficients increases with the increase of ambient argon pressure. The outcome of these studies recommends that these materials can be a preeminent candidate for photovoltaic applications. Photoluminescence spectroscopy results are accredited to the accumulation of non-crystalline nanochalcogenide particles on the substrates. DC conductivity measurements further confirm the semiconducting nature of the nanochalcogenide Se85Te3Bi12 thin films.
A dynamic semantic segmentation algorithm with encoder-crossor-decoder structure for pixel-level building cracks
Authors: Chen Yuliang , Dong Shaojiang , Hu Bo , Liu Qingyi , Qu Yinghao
Published: November 2023

A large number of newly built infrastructures as well as those constructed in the early stage are faced with the problems of detection and maintenance. However, it is difficult to detect building cracks because of its small size and complex background noise. In this study, a crack segmentation network based on Encoder-Crossor-Decoder structure is innovatively proposed to solve the problems of small cracks and easy to be disturbed by background. Then, a loss function is proposed to address the problem of large differences in the ratio of cracks to background pixels in architectural crack segmentation. The experiments show that the loss function can effectively improve the training effect of the model and make the model obtain better semantic segmentation ability. Finally, according to the requirements of building crack detection, a large dataset of concrete pavement cracks is produced, which fills the gap of large dataset of semantic segmentation of cracks. The excellent effect of the model and loss function is verified with three datasets containing most of the major material and structural scenes. In addition, we compare the model with other deep learning segmentation models to validate its effectiveness. The results show that the mIoU of the model of this study reaches 84.04%, 77.56% and 87.38% in the bridge non-steel crack dataset, steel surface crack dataset and our concrete crack dataset, respectively. The accuracy reaches 99.14%, 98.62% and 99.37%. F1 reaches 0.911, 0.873 and 0.963 respectively. It outperforms other deep learning based segmentation methods.
Green fabrication of ultrafine N-Mo
x
C/CoP hybrids for boosting electrocatalytic water reduction
Authors: Yu Xiaomei , Shi Wei , Wei Jiajiao , Liu Tiantian , Li Yuanyuan , He Mengyuan , Wei Zhengyu , Ping Dehai , Sun Panfei , Zheng Jin You , Li Songjie
Published: November 2023

Developing non-noble-metal electrocatalysts for hydrogen evolution reactions with high activity and stability is the key issue in green hydrogen generation based on electrolytic water splitting. It has been recognized that the stacking of large CoP particles limits the intrinsic activity of as-synthesized CoP catalyst for hydrogen evolution reaction. In the present study, N-Mo
x
C/CoP-0.5 with excellent electrocatalytic activity for hydrogen evolution reaction was prepared using N-Mo
x
C as decoration. A reasonable overpotential of 106 mV (at 10 mA cm−2) and a Tafel slope of 59 mV dec−1 in 1.0 M KOH solution was achieved with N-Mo
x
C/CoP-0.5 electrocatalyst, which exhibits superior activity even after working for 37 h. Uniformly distributed ultrafine nanoclusters of the N-Mo
x
C/CoP-0.5 hybrids could provide sufficient interfaces for enhanced charge transfer. The effective capacity of the hydrogen evolution reaction could be preserved in the complex, and the enlarged electrocatalytic surface area could be expected to offer more active sites for the reaction.
Ca-AlN MOFs-loaded chitosan/gelatin scaffolds; a dual-delivery system for bone tissue engineering applications
Authors: Dousti Mahdi , Golmohamadpour Azadeh , Hami Zahra , Jamalpoor Zahra
Published: November 2023

Creating a scaffold for bone tissue engineering that is bioactive and capable of acting as a local-dual delivery system, releasing bioactive molecules and regulating the bone remodeling process to achieve balanced bone resorption and formation, is a significant challenge. The objective of this research is to create a composite scaffold using chitosan/gelatin (CHS/Gel) and the calcium (Ca)-alendronate (ALN) metal–organic frameworks (MOFs). The scaffold will act as a dual-delivery system, releasing Ca ions and ALN to regulate bone formation. Ca-ALN MOF nanoparticles (NPs) were prepared in mild conditions and studied by FTIR, XRD, FESEM, and TGA. Ca-ALN NPs-loaded CHS/Gel scaffolds were opportunely fabricated through freeze-drying approach. Physicochemical features of the scaffolds after incorporating NPs equated by CHS/Gel scaffold changed, therefore, the attendance of NPs caused a decreasing porosity, decreased swelling, and low rate of degradation. The release profile results showed that the NPs-loaded CHS/Gel scaffolds were able to simultaneously release ALN and Ca ions due to the decomposition of NPs. Additionally, the loading of NPs in the CHS/Gel scaffold led to an increment in alkaline phosphatase (ALP) activity and the quantity of deposited Ca along with osteogenesis gene markers. These findings suggest that the NPs-loaded CHS/Gel scaffold has the potential to enhance the differentiation of human adipose tissue-derived mesenchymal stem cells, making it a promising approach for bone repair.
Coherence of turbulent structures with varying drive in stellarator edge plasmas
Authors: Huslage P , Birkenmeier G , Shanahan B , Killer C
Published: November 2023

This work investigates the parallel coherence of plasma filaments through numerical simulations using the hot-ion two-fluid hermes-2 model within the BOUT++ framework. Realistic field lines in the scrape-off layer (SOL) of magnetic fusion devices, especially in stellarator configurations possess a highly varying curvature along the magnetic field line. A varying curvature creates a parallel

E

×

B

velocity gradient which might tear the filament apart. The main parameters controlling this process are the collisionality and the electron plasma beta. Simulations of realistic curvature variations along field lines in a circular ASDEX Upgrade-like tokamak and Wendelstein 7-X stellarator (W7-X) show the parallel displacement between different filament sections to correlate with the curvature. The rapidly varying W7-X curvature and the low average curvature drive reduce the propagation of the filament to only a few hundred meters per second. The effect of a finite ion temperature on filament propagation in a W7-X field line geometry is found to be a higher diamagnetic current resulting in stronger charge separation. This work supports simulations and experimental findings that filaments in W7-X are comparably slow due to the large major radius of the device. They do not perform ballistic motion and hence do not drive significant turbulence spreading in the SOL.
Quantum Goos-Hänchen switch in graphene junctions
Authors: Zhang Z B , Wang Rui , Wang Baigeng , Xing D Y
Published: November 2023

Goos-Hänchen (GH) shift, an interference phenomenon describing the lateral shift of the reflected beam along the interface during total internal reflection, has attracted great interests in the field of quantum transport in two-dimensional materials. In particular, the GH effect generates a novel pseudospin-dependent scattering effect in graphene, which in turn results in an

8

e

2

/

h

conductance step in the bipolar junctions. Here, we reveal that a barrier region with effective barrier strength χ can greatly enrich the GH effect in graphene junctions. In contrast to the conventional case where the negative shift is allowed only in the p-n junction, the thin barrier enables both negative and positive spatial shifts in pIn and nIn junctions, where I represents the barrier region. More interestingly, the lowest channel degeneracy can be efficiently varied by tuning χ in both the symmetric pInIp and the asymmetric pnIp junctions, leading to a highly controllable switch that switches the conductance between

8

e

2

/

h

and

4

e

2

/

h

. These results advance the knowledge of GH effects in electronic materials and suggest experimental avenues for its observation and manipulation.
Formation and evolution of multiple-core structures in laser-sustained plasmas
Authors: Liu Jinbao , Zhang Dongheyu , Fu Yangyang
Published: November 2023

We report on the formation of multiple-core structures in laser-sustained plasmas (LSPs) through the utilization of an improved two-dimensional laser-thermal-hydrodynamically coupled fluid model. Our findings reveal that steady-state LSPs exhibit various temperature structures, including single, double, and triple cores, as the input laser power increases incrementally. The spatiotemporal distributions of these multiple-core structures are demonstrated, and the presence of an LSP core is identified when the rate of enthalpy change becomes positive. This behavior is predominantly influenced by factors such as laser power absorption, radiation, and diffusion along the laser path. The obtained results provide explicit insights into the temperature structures within LSPs, thereby potentially contributing to the advancement of LSP-based light sources for optical wafer defect inspection in the semiconductor industry.
The two-loop power spectrum in redshift space
Authors: Taule Petter , Garny Mathias
Published: November 2023

We present the matter power spectrum in redshift space including two-loop corrections. We
follow a strictly perturbative approach incorporating all non-linearities entering both via the
redshift-space mapping and within real space up to the required (fifth) order, complemented by
suitable effective field theory (EFT) corrections. This approach can a priori be viable up to
scales of order 0.2h Mpc-1 beyond which power suppression related to the finger-of-God effect
becomes non-perturbatively strong. We extend a simplified treatment of EFT corrections at
two-loop order from real to redshift space, making sure that the leading UV-sensitivity of both
the single-hard and double-hard limit of the two-loop contributions to the power spectrum is
accounted for, and featuring two free parameters for each multipole. Taking also
infrared-resummation into account, we calibrate with and compare to Quijote N-body simulations
for the monopole and quadrupole at redshifts z = 0 and z = 0.5. We find agreement within sample
variance (at percent-level) up to 0.18h Mpc-1 at two-loop order, compared to 0.1h Mpc-1 at
one-loop. We also investigate the role of higher-derivative corrections.
Diurnal modulation of electron recoils from DM-nucleon scattering through the Migdal effect
Authors: Qiao Mai , Xia Chen , Zhou Yu-Feng
Published: November 2023

Halo dark matter (DM) particles could lose energy due to the scattering off nuclei within the Earth before reaching the underground detectors of DM direct detection experiments.
This Earth shielding effect can result in diurnal modulation of the DM-induced recoil event rates observed underground due to the self-rotation of the Earth.
For electron recoil signals from DM-electron scatterings, the current experimental constraints are very stringent such that the diurnal modulation cannot be observed for halo DM.
We propose a novel type of diurnal modulation effect: diurnal modulation in electron recoil signals induced by DM-nucleon scattering via the Migdal effect.
We set so far the most stringent constraints on DM-nucleon scattering cross section via the Migdal effect for sub-GeV DM using the S2-only data of PandaX-II and PandaX-4T with improved simulations of the Earth shielding effect.
Based on the updated constraints, we show that the Migdal effect induced diurnal modulation of electron events can still be significant in the low energy region, and can be probed by experiments such as PandaX-4T in the near future.
Spin-2 dark matter from inflation
Authors: Gorji Mohammad Ali
Published: November 2023

The seed of dark matter can be generated from light spectator fields during inflation through a similar mechanism that the seed of observed large scale structures are produced from the inflaton field. The accumulated energy density of the corresponding excited modes, which is subdominant during inflation, dominates energy density of the universe later around the time of matter and radiation equality and plays the role of dark matter. For spin-2 spectator fields, Higuchi bound may seem to prevent excitation of such light modes since deviation of the inflationary background from the exact de Sitter spacetime is very small. However, sizable interactions with the inflaton field breaks (part of) isometries of the de Sitter space in the inflationary background and relaxes the Higuchi bound. Looking for this possibility in the context of effective field theory of inflation, we suggest a dark matter model consisting of spin-2 particles that produce during inflation.
A topologically charged four-dimensional wormhole and the energy conditions
Authors: Ahmed Faizuddin
Published: November 2023

In this research work, our primary focus revolves around the examination of a specific category of traversable wormholes known as topologically charged generalized Schwarzschild-Simpson-Visser-type wormhole, ds
2 = -(1-(2M/√(x
2+b
2))) dt
2+(1-(2M/√(x
2+b
2)))-1 ·(dx
2/α2)+(x
2+a
2) (dθ
2+sin2
θ
dϕ
2). This wormhole is uniquely defined by a pair of key parameters including global monopole charge. A noteworthy outcome of our investigation is the observation that the energy-momentum tensor associated with this wormhole complies with both the weak energy condition (WEC) and the null energy condition (NEC). Furthermore, incorporation of global monopole charge introduces a substantial influence on the curvature properties of wormhole space-time and various associated physical quantities derived from this geometry.
Observation of local density increase during pellet homogenization on EAST
Authors: Huang J. , Zhang T. , Zhang J. , Liang Y.F. , Wang Y.M. , Liao L. , Hou J.L. , Han X. , Ye K.X. , Geng K.N. , Xiang H.M. , Wen F. , Zhong F.B. , Li G.S. , Wu M.F. , Zhou Z. , Yang S.Q. , Zhou Z.Q. , Yu L. , Liu H.Q. , Krämer-Flecken A. , Gao X. , Zhuang G. ,   the EAST Team
Published: November 2023

By combining the X-mode polarized lower and upper cut-off reflections obtained from the density profile reflectometer, we have successfully attained a comprehensive density profile spanning from the edge to the core region in pellet injection (PI) experiments on EAST. During the homogenization process after PI on EAST, an innovative method was introduced to quantify the local density increase. This approach employed the distinctive ‘dual-reflection’ phenomenon observed in the EAST microwave reflectometer, encompassing measurements of both the X-mode lower and upper cut-off frequencies. Furthermore, experimental investigations were carried out on EAST to comprehensively explore the parallel and poloidal expansion of the high-density pellet cloud. Notably, this study marks the first instance of measuring expansion velocities of pellet materials in both parallel and poloidal directions on EAST. A comparative analysis was performed initially between these experimental measurements and simulation results obtained from the HPI2 code, marking a pivotal stride towards enhancing its applicability in EAST.
Intelligent Selection Method for Gravity-suitable Area Based on Improved Support Vector Machine by the Genetic Algorithm
Authors: He Chuangxin , Zhang Fengshuo , Yu Xiaoyou , Zheng Wei
Published: November 2023

The gravity-aided inertial navigation system (GAINS) can achieve precise positioning of underwater vehicles in a gravity-suitable area. However, there are generally shortcomings in the existing intelligent suitable area selection methods in terms of selecting gravity feature parameters and learning parameters. In this paper, an intelligent suitable area selection method is proposed based on an improved support vector machine by the genetic algorithm (GA-SVM) to address the aforementioned problems. Firstly, the genetic algorithm (GA) is utilized to independently pick out the optimal feature subset of 15 existing gravity feature parameters and obtain the optimal support vector machine (SVM) learning parameters while eliminating irrelevant redundant features, thus improving the classifier’s performance and generalization ability. Then, the SVM classifier is trained according to the optimal information output by GA, and the accuracy of the test set is 95.5%. Finally, the classifier is utilized to distinguish suitable and unsuitable areas in the application region to evaluate the proposed method’s performance. The TERCOM experiment in the suitable area resulted in an average positioning error of less than 170 m.
Robot path planning based on improved A* algorithm
Authors: Yu Jintao , Gao Zhenhua , Jiang Mingze , Hou Enqi
Published: November 2023

To address the issues of excessive polyline paths and the increased number of search nodes in the A* algorithm, a weighted WA* algorithm is proposed based on the A* algorithm. Firstly, a new distance function is introduced to reduce computational resource usage and improve search efficiency. Then, the heuristic function is improved by searching all feasible paths to find the shortest path. When the lengths of feasible paths are very similar, an additional value is added to the heuristic function along with weights to minimize frequent searches. Lastly, Bezier curves are introduced to enhance the smoothness of the global path. Simulation results show that the improved WA* algorithm reduces the number of turns, time consumption, search space, and turning angles by 25.0%, 65.4%, 53.5%, and 18.7%, respectively, compared to the A* algorithm. Compared to the bidirectional A* algorithm, these reductions are 7.6%, 34.4%, 43.5%, and 7.1%, respectively. In addition, the WA* algorithm uses Bezier curves to curve-fit the generated path points, making the path trajectory smoother.
Improved YOLOv7 Intelligent Environment Perception Algorithm Based on Loss Function
Authors: Ma Zingjing , Peng Tao
Published: November 2023

To address the difficulty of environment perception in unmanned driving technology, an improved intelligent environment perception model based on YOLOv7 loss function is proposed. Simultaneously, the algorithm of deep sort target tracking is added for the sake of perceiving the surrounding environment through the camera to ensure the safety of the driver. And by modifying the loss term of the aspect ratio to the distinction between the predicted width and the target width, the fitting speed of the model can be effectively improved. Focal Loss is introduced to optimize the problem with the sample imbalance inside the target bounding box regression and reduce the weight proportion of numerous anchor boxes with less overlap between the predicted target bounding box and the true target bounding one to the overall model, such that the model centers more upon overlapping targets. The data applied to this article is BDD100K. The map of this algorithm reaches 60.3 %, which reaches 2.2 percentage points exceeding the baseline. Tests indicate that the raised algorithm attains certain advancements in the intelligent perception model of unmanned driving.
Wildfire Smoke Detection Based on Swin Transformer
Authors: Wang Yue , Piao Yan
Published: November 2023

Wildfires have devastating consequences for ecosystems and human lives, and it is crucial to detect wildfires accurately for reducing losses. Most researchers detected wildfire smoke by traditional smoke detection algorithms, deep learning algorithms, or a combination of both, but this still has a high rate of false positive. To enhance the accuracy of wildfire smoke detection, we present an advanced algorithm based on the Swin Transformer architecture, which improves remote dependence of high-order feature maps in the convolutional neural network, thus reducing the false positive rate of smoke detection by introducing the STB module to the GoogLeNet. We approach the task of wildfire smoke detection as a classification problem, where we divide the dataset of 18, 000 real wildfire smoke images into two distinct sets: a training set and a testing set. The experimental results support the efficacy and practicality of the proposed algorithm, exhibiting a remarkable smoke detection accuracy rate of 95% while successfully reducing the false alarm rate to as low as 4%. These findings underscore the algorithm’s capability to accurately identify wildfire smoke instances while minimizing erroneous detections.
Design and Implementation of Environmental Monitoring System for Substation Based on Internet of Things
Authors: Li Songbai , Liu Yanlong , Chen Xiaoguang
Published: November 2023

At present, the environmental monitoring of the substation suffers from complex wiring, low intelligence, high staff work intensity, and a lack of information-based overall management. Moreover, the distribution of substations is relatively scattered, making it complex and costly to set up a dedicated communication network. In response to these problems, this paper combines modern communication technology, sensor technology, and mobile intelligent terminal development technology to study an overall information-based substation environmental monitoring system. The monitoring system proposed in this paper includes a main controller, a data collection terminal, and a mobile communication terminal. The environmental data collected by the main controller is sent to the server through the communication method of subscription and substation using wireless communication technology, and the interface of the mobile communication terminal can display indoor environmental monitoring data. When the environmental data of the Substation exceeds the set threshold value to issue an early warning alert, the user can control it remotely through the mobile communication terminal to improve the indoor environment of the Substation. The system has a simple operation interface, low power consumption, and strong expansion compatibility, which effectively realizes remote monitoring and control of the substation environment and has good engineering application value.
Fault detection of high-voltage insulator thermal images based on YOLOv5
Authors: Liu Xinyi , Miao Runzhong , Meng Yi , Sun Haonan , Wu Kaixin
Published: November 2023

In this paper, we propose a defect detection method based on YOLOv5 for thermal images of high-voltage insulators, in which a large number of insulator photographs are taken by a thermal imager, followed by a YOLOv5 model to detect the captured thermal images. The function Meta-ACON is proposed to replace the original activation function. Finally, the extracted features are used for insulator condition identification and defect detection. Experimental findings demonstrate the efficacy of the suggested approach in successfully accomplishing the feature extraction of insulator faults, thus improving the accuracy and efficiency of insulator fault diagnosis.
Self-supervised Learning for Expression Recognition on Small-scale Data Set
Authors: Li Songyang , Tsuchida Kensei , Goto Takaaki , Kirishima Tadaaki
Published: November 2023

In this paper, we propose a facial micro-expression recognition method utilizing self-supervised learning and Vision Transformer. We employ a contrast learning approach for self-supervision and extract image features using an attention mechanism. Various data augmentation techniques were utilized, and we specifically designed an enhancement method for facial recognition. By combining the strengths of the Vision Transformer and CNN models for feature extraction, our approach achieves improved recognition accuracy, even with limited labeled data. Experimental evaluation shows that our proposed method has good results in facial micro-expression recognition tasks.
Lightweight Human Motion Recognition Method with Multiscale Temporal Features
Authors: Liu Ying , Luan Tian
Published: November 2023

To address the problems of the large size of human motion recognition models based on deep learning and insufficient mining of data features and thus low recognition accuracy, a lightweight human motion recognition algorithm based on multi-scale temporal features is proposed, the algorithm automatically extracted features through a multiscale feature fusion model. After, the integrated features are modeled by an improved time convolution network (TCN). In the TCN network structure, In the TCN network structure, the depthwise separable convolution is used instead of the normal convolutional layer to reduce the computational complexity, and the Leaky ReLU activation function is used instead of the ReLU function to improve the training efficiency. The experiments are based on the WISDM public dataset. finally achieve fast real-time recognition of actions, and structural and parametric optimization is performed through experiments to effectively improve the accuracy of results, and the final accuracy rate reaches 99.06%. In comparison with other methods, this method can reduce the model volume while maintaining a high accuracy rate.
Cooperative Spectrum Sensing Algorithm Based on Eigenvalue Fusion
Authors: Guo Qianrui , Guo Bin , Li Xiangkun , Ma Weijiao
Published: November 2023

A novel algorithm is introduced to improve collaborative spectrum sensing under low cognitive capabilities and insufficient signal-to-noise ratio. The algorithm is based on the difference of random matrix eigenvalues and uses the theory of random eigenvalues and the extreme distribution of the minimum eigenvalue. It makes use of the average, both arithmetic and geometric, as well as the minimum and maximum values of eigenvalues as the detection metric. It calculates the fusion power parameter through local energy spectrum sensing. Simulation results demonstrate that the algorithm outperforms the DMM algorithm and the NMME algorithm under users with low cognitive capabilities and Insufficient signal-to-noise ratio, making it more suitable for low signal-to-noise ratio environments.
Ultrasound Image Classification of Thyroid Nodules Based on Attention Mechanism
Authors: Yu Lintao , Qu Shuoou , Cong Zhibin , An Xiaofeng
Published: November 2023

Ultrasound imaging of the thyroid gland is currently the most common diagnostic technique, used for pre diagnosis of benign and malignant thyroid nodules. During the clinical diagnosis, the condition judgment requires the high clinical experience of physicians. The low level of medical care in remote areas has led to an increased rate of misdiagnosis of benign and malignant nodules. To improve the accuracy of diagnosis and treatment effectiveness of doctors, this work proposes a benign and malignant thyroid classification model based on mechanisms of attention. First, this paper performs data cleaning on the collected data and performs pre-processing operations such as data enhancement to construct a new dataset. Then, a network model based on Lightweight Global Attention Module (LGAM) is constructed for the benign and malignant classification of nodules. Finally, it is shown by experimental analysis and comparison that the improved LGAM-based thyroid node classification model has achieved better experimental results on the dataset and can achieve the optimal classification accuracy of 95.16% for the network model proposed in this work.
Regional Link Routing Algorithm for Wireless Sensor Networks based on Improved Grey Wolf Optimization Algorithm
Authors: Ding Jiaqian , Jia Xinyong , Chen Jiaqi
Published: November 2023

In order to improve the survival time, connectivity and the active number of nodes in the wireless sensor network, this paper proposes a regional chain wireless sensor network routing algorithm (RWA) based on improved grey Wolf optimization algorithm. The algorithm uses the method of dividing regions into chains, and in each region, chains are formed to select cluster heads before communication. The simulation results show that RWA has an improvement in avoiding too long chain, balancing energy consumption and prolonging the network life cycle.
Gesture Recognition of sEMG Signals Based on CNN-GRU Network
Authors: Bai Duanyuan , Zhang Dong , Zhang Yongheng , Shi Yingjie , Wu Tingyi
Published: November 2023

To improve the accuracy of surface electromyogram signal (sEMG) gesture recognition algorithm and solve the problem of manually extracting many features, this paper proposes a deep neural network-based gesture recognition method. A neural network integrating CNN and GRU was designed. The 8-channel sEMG data collected by the MYO armband is input to the CNN for feature extraction, and then the obtained feature sequence is input to the GRU network for gesture classification, and finally the recognition result of the gesture category is output. The experimental findings that the proposed technology reaches 76.41% recognition accuracy on the MyoUP dataset. This demonstrates the practicality of the suggested plan.
Multi-level Salient Feature Mining Network for Person Re-identification
Authors: Wang Dingyi , Du Haishun
Published: November 2023

Person re-identification (Re-ID) algorithms can retrieve the same pedestrian’s images from an image gallery captured by multiple cameras when given a pedestrian image. Due to changes in pedestrian postures, illuminations, and perspectives, it remains a significant challenge to improve the accuracy of person re-identification. Although the attention mechanism can alleviate some of these issues, it causes attention-based methods to pay excessive attention to features in the most salient areas of images while ignoring discriminant features outside the most salient areas, resulting in the insufficient discriminability of features extracted by attention-based methods. For this purpose, we propose a Multi-level Salient Feature Mining Network (MSFM-Net). First, by embedding attention modules in ResNet50, the model extract the most salient pedestrian feature maps. Second, the model uses two sub-salient feature mining branches to extract the second-level and third-level salient feature maps (collectively referred to as sub-salient feature maps). Third, the model uses the feature maps fusion module to combine the most salient feature maps with sub-salient feature maps to obtain the fused salient feature maps. Finally, the model pools the fused salient feature maps to produce more discriminant pedestrian representations. The results of two benchmark datasets demonstrate that MSFM-Nets performance reaches the current advanced level.
Remote-sensing Small-target Detection Based on Feature-dense Connection
Authors: Bao Wenshu
Published: November 2023

To address the problem that a large number of small targets exist in remote-sensing images but are difficult to detect, in this paper, a DenseYOLOv5 detection model is proposed for practical applications. DenseYOLOv5 is based on YOLOv5s and the small target detection head P2 and its feature fusion part are added to improve the detection performance of small targets. To address the problem of semantic information loss of small targets due to continuous upsampling in YOLOv5s, DenseYOLOv5 reconstructs the feature fusion pyramid (FPN) structure and incorporates dense connections. In addition, DenseYOLOv5 also uses transposed convolution as the upsampling method to further improve the small target detection capability. DenseYOLOv5 can achieve better detection results with less memory and computational overhead and thus has better usability.