bluuebunny/crossref_metadata_2025 huggingface dataset:
Sensitivity matrix update method for electrical resistance tomography based on error-constrained cross fusion residual attention network
Authors: Wang Chao , Zhu Shiyi , Zhao Linshuo , Pang Ran , Ye Jiamin , Yan Jingyi
Published: September 2024

Electrical resistance tomography (ERT) is an imaging technique of conductivity distribution. The image reconstruction algorithm based on the empty field sensitivity matrix is widely used because it provides an approximate solution to the complex ERT inverse problems. However, due to the soft field effect, the sensitivity matrix changes with the media distribution, leading to significant errors in image reconstruction. To address this issue, an error-constrained deep learning scheme for bubble flow, namely cross fusion residual attention network (CFRA-Net) is designed to update the sensitivity matrix during gas–liquid–solid fluidized bed operation. CFRA-Net employs a multi-head self-attention mechanism to enhance bubble features in boundary measurements, a multilevel cross fusion (CF) module to fuse empty field strength and boundary measurement information, and a novel serial-channel residual spatial attention block to boost the feature extraction capability of the model. A weighted loss function is designed to give more weight to the gas phase distribution region. Additionally, this paper establishes a dataset for gas–liquid–solid three-phase flow, considering background field conductivity variations. Validation and reliability of the proposed method are assessed through ablation, comparison, and noise experiments. The experimental results demonstrate that CFRA-Net achieves rapid updates of the sensitivity matrix, high imaging accuracy, and robust noise immunity.
A ship detection model with progressive feature fusion and cross-spatial learning attention mechanism for optical remote sensing images
Authors: Miao Ru , Wang Jiaqian , Zhou Ke , Meng Geng , Li Yi , Chang Ranran
Published: September 2024

Using remote sensing images to detect ships is vital for port management, maritime transportation, and security. Challenges such as false detection and omission arise in ship target detection in optical remote sensing images due to the complexity of the background and the diversity of target scales. To address these issues, this paper proposes a novel model called MBE-YOLO. Firstly, the multiscale input spatial pyramid pooling-fast structure is designed to effectively extract more feature information by efficiently integrating the features from different stages of the backbone network. Secondly, the backbone to neck structure is designed with a progressive architecture to mitigate semantic differences between non-adjacent layers in the feature delivery process, thereby significantly reducing the risk of information loss. Finally, we introduce the efficient multi-scale attention attention mechanism, which establishes short and long dependencies through multi-scale parallel subnetworks. This enhances the ability to detect targets in complex environments at various scales. MBE-YOLO is applied to the HRSC2016 and HiresShipDetection datasets. Comparison experiments with current mainstream and state-of-the-art models demonstrate its effectiveness in addressing errors and omissions due to scene complexity and scale variations in remote sensing ship detection, with a parameter size of only 3.24 M.
Facile synthesis of Bi2ZnB2O7-MoS2 nanocomposite for photodetector and photocatalytic Rhodamine B dye degradation application
Authors: Porwal Chirag , Thakur Deepa , Gaur Akshay , Chauhan Vishal Singh , Balakrishnan Viswanath , Vaish Rahul
Published: September 2024

In this research, the visible light active performance of Bi2ZnB2O7 (BBZO) was significantly enhanced through the formation of a composite with few layer MoS2. The resultant MoS2@BBZO catalyst was employed in both photocatalysis and photodetector applications. Comprehensive structural and morphological analyses of the MoS2@BBZO catalyst were conducted using x-ray diffraction, Raman spectroscopy, field-emission scanning electron microscopy (FE-SEM), and transmission electron microscopy. The estimated band gaps of BBZO and the composite were found to be 2.8 eV and 1.74 eV, respectively. Rhodamine B degradation studies demonstrated that the catalyst achieved 75% degradation within 30 min. Additionally, the photodetector application was investigated, revealing rapid photo-switching capabilities and an increased photocurrent.
Enhancement of photovoltaic parameters of thermally stable graphene/LaVO3 semitransparent solar cell by employing interfacial graphene quantum dots
Authors: Kim Hyo-Han , Kim Do Hoon , Choi Bo Gyu , Kim Da Hee , Oh Si Duck , Shin Dong Hee , Lee Hosun
Published: September 2024

Semitransparent solar cells are attracting attention not only for their visual effects but also for their ability to effectively utilize solar energy. Here, we demonstrate a translucent solar cell composed of bis(trifluoromethane sulfonyl)-amide (TFSA)-doped graphene (Gr), graphene quantum dots (GQDs), and LaVO3. By introducing a GQDs intermediate layer at the TFSA-Gr/LaVO3 interface, we can improve efficiency by preventing carrier recombination and promoting charge collection/separation in the device. As a result, the efficiency of the GQDs-based solar cell was 4.35%, which was higher than the 3.52% of the device without GQDs. Furthermore, the average visible transmittance of the device is 28%, making it suitable for translucent solar cells. The Al reflective mirror-based system improved the power conversion efficiency by approximately 7% compared to a device without a mirror. Additionally, the thermal stability of the device remains at 90% even after 2000 h under an environment with a temperature of 60 °C and 40% relative humidity. These results suggest that TFSA-Gr/GQDs/LaVO3-based cells have a high potential for practical use as a next-generation translucent solar energy power source.
Visible-light-driven selective cleavage of lignin C-C bonds on the TiO2@g-C3N4 heterostructured photocatalyst
Authors: Xiao Gang , Wang Zishuai , Jin Yu , Wang Fengping
Published: September 2024

The selective cleavage of lignin C–C bonds is a highly sought-after process with the goal of obtaining low-molecular-weight aromatic chemicals from renewable resources. However, it remains a challenging task to achieve under mild conditions. Photocatalysis is a potentially promising approach to address this issue, but the development of efficient photocatalysts is still in progress. In this study, we introduce the heterostructured TiO2@g-C3N4 photocatalyst for the development of a visible light photocatalytic procedure for the selective cleavage of lignin C–C bonds under mild conditions. The photocatalyst displays favourable visible light absorption, efficient charge separation efficiency, and promising reusability. A typical β–O–4 dimer model, 2-phenoxy-1-phenylethanol, was effectively (96.0% conversion) and selectively (95.0 selectivity) cleaved under visible light at ambient conditions. This photocatalytic procedure was also effective when subjected to solar irradiation or other lignin dimer models with β–O–4 or β-1 linkages. This reaction occurred through a C
β
-centred radical intermediate and a six-membered transition state with photogenerated holes as the primary active species. The C
α
–OH oxidative dehydrogenation of the substrate could also take place but was a relatively minor route. This study provides a new photocatalytic procedure for visible-light-driven lignin valorisation and sheds light on the design of high-performance nanocomposite photocatalysts for C–C bond cleavage.
Fabrication of a graphene@Ni foam-supported silver nanoplates-PANI 3D architecture electrode for enzyme-free glucose sensing
Authors: Wahid Ahtisham Abdul , Usman Muhammad , Haleem Yasir A , Ahmed Arsalan , Raza Kabeer , Munir Muhammad Usman , Pan Lujan , Khan Aslam
Published: September 2024

Reliable and cost-effective glucose sensors are in rising demand among diabetes patients. The combination of metals and conducting polymers creates a robust electrocatalyst for glucose oxidation, offering enzyme-free, high stability, and sensitivity with outstanding electrochemical results. Herein, graphene is grown on nickel foam by chemical vapor deposition to make a graphene@nickel foam scaffold (G@NF), on which silver nanoplates-polyaniline (Ag–PANI) 3D architecture is developed by sonication-assisted co-electrodeposition. The resulting binder-free 3D Ag–PANI/G@NF electrode was highly porous, as characterized by x-ray photoelectron spectroscopy, Field emission scanning electron microscope, x-ray diffractometer, FTIR, and Raman spectroscopy. The binder-free 3D Ag–PANI/G@NF electrode exhibits remarkable electrochemical efficiency with a superior electrochemical active surface area. The amperometric analysis provides excellent anti-interference performance, a low limit of deduction (0.1 nM), robust sensitivity (1.7 × 1013
µA mM−1cm−2), and a good response time. Moreover, the Ag–PANI/G@NF enzyme-free sensor is utilized to observe glucose levels in human blood serums and exhibits excellent potential to become a reliable clinical glucose sensor.
Elucidating the time-dependent charge neutrality point modulation of polymer-coated graphene field-effect transistors in an ambient environment
Authors: Norhakim Nadia , Gunasilan Thaachayinie , Kesuma Zayyan Rafi , Hawari Huzein Fahmi , Burhanudin Zainal Arif
Published: September 2024

The charge neutrality point (CNP) is one of the essential parameters in the development of graphene field-effect transistors (GFETs). For GFET with an intrinsic graphene channel layer, the CNP is typically near-zero-volt gate voltage, implying that a well-balanced density of electrons and holes exists in the graphene channel layer. Fabricated GFET, however, typically exhibits CNP that is either positively or negatively shifted from the near-zero-volt gate voltage, implying that the graphene channel layer is unintentionally doped, leading to a unipolar GFET transfer characteristic. Furthermore, the CNP is also modulated in time, indicating that charges are dynamically induced in the graphene channel layer. In this work, understanding and mitigating the CNP shift were attempted by introducing passivation layers made of polyvinyl alcohol and polydimethylsiloxane onto the graphene channel layer. The CNP was found to be negatively shifted, recovered back to near-zero-volt gate voltage, and then positively shifted in time. By analyzing the charge density, carrier mobility, and correlation between the CNP and the charge density, it can be concluded that positive CNP shifts can be attributed to the charge trapping at the graphene/SiO2 interface. The negative CNP shift, on the other hand, is caused by dipole coupling between dipoles in the polymer layer and carriers on the surface of the graphene layer. By gaining a deeper understanding of the intricate mechanisms governing the CNP shifts, an ambiently stable GFET suitable for next-generation electronics could be realized.
Examining transport and integrated modeling predictive capabilities for negative-triangularity scenarios
Authors: McClenaghan J , Marinoni A , Nelson A O , Neiser T , Lao L L , Staebler G M , Smith S P , Meneghini O M , Lyons B C , Snyder P B , Austin M
Published: September 2024

This paper investigates the predictive capabilities of TGYRO and TGLF models in assessing the performance of negative triangularity (NT) plasmas compared to positive triangularity (PT) plasmas in fusion devices. TGYRO predicts kinetic profiles, while TGLF analyzes turbulent transport. The study reveals that TGYRO reasonably predicts NT profiles similar to PT, although it overpredicts the high-power scenarios where there is increased experimental MHD activity. TGLF analysis finds reduced linear growth rates in NT and altered flux spectra relative to PT. Additionally, the TGLF SAT0 saturation model is observed to predict high-k transport and a reduction of particle transport with the electron temperature gradient. These findings are further corroborated by core-pedestal modeling using the Stability Transport Equilibrium Pedestal workflow, showing stronger confinement improvements in NT, particularly at higher power densities for the SAT0 saturation model. The study underscores the importance of accurately capturing turbulence saturation mechanisms for NT in order to project its performance accurately in fusion reactors.
Determinant- and derivative-free quantum Monte Carlo within the stochastic representation of wavefunctions
Authors: Bernheimer Liam , Atanasova Hristiana , Cohen Guy
Published: September 2024

Describing the ground states of continuous, real-space quantum many-body systems, like atoms and molecules, is a significant computational challenge with applications throughout the physical sciences. Recent progress was made by variational methods based on machine learning (ML) ansatzes. However, since these approaches are based on energy minimization, ansatzes must be twice differentiable. This (a) precludes the use of many powerful classes of ML models; and (b) makes the enforcement of bosonic, fermionic, and other symmetries costly. Furthermore, (c) the optimization procedure is often unstable unless it is done by imaginary time propagation, which is often impractically expensive in modern ML models with many parameters. The stochastic representation of wavefunctions (SRW), introduced in (Atanasova et al 2023 Nat. Commun.
14 3601), is a recent approach to overcoming (c). SRW enables imaginary time propagation at scale, and makes some headway towards the solution of problem (b), but remains limited by problem (a). Here, we argue that combining SRW with path integral techniques leads to a new formulation that overcomes all three problems simultaneously. As a demonstration, we apply the approach to generalized ‘Hooke’s atoms’: interacting particles in harmonic wells. We benchmark our results against state-of-the-art data where possible, and use it to investigate the crossover between the Fermi liquid and the Wigner molecule within closed-shell systems. Our results shed new light on the competition between interaction-driven symmetry breaking and kinetic-energy-driven delocalization.
Simulation of the functionality of ZnO, TiO2 and Ta2O5, and MoO2 carrier selective contacts of GaAs0.99Bi0.01 nanowire-based solar cells
Authors: Roy Debamita , Samajdar Dip Prakash , Biswas Abhijit
Published: September 2024

The photovoltaic performance of perpendicularly aligned GaAs0.99Bi0.01/CSC/ITO core–shell nanowire solar cells is thoroughly investigated in this simulation-based theoretical study for both electron-selective contact (ESC) and hole selective contact (HSC) as carrier selective contact (CSC) shell around GaAs0.99Bi0.01 core nanowire. The overall performance is compared with radial p-i-n-doped GaAs0.99Bi0.01 nanowire solar cell (NWSC) to mark the improvement caused by carrier selectivity. ZnO, TiO2 and Ta2O5 are chosen as ESC material and MoO2 is chosen as HSC material in order to carry out this comparative study. We have thoroughly performed geometric optimization tests over a wide range of periods in order to select the optimized ITO (indium tin oxide) thickness for obtaining maximum photocurrent generation. A maximum short-circuit photocurrent density (J
sc) of 38.76 mA cm−2 is obtained with a ZnO coated NWSC for a pitch (P) of 400 nm and ITO shell thickness of 90 nm. For this optimized geometry, TiO2, Ta2O5 and MoO2 coated structures offer J
sc of 35.82, 35.69 and 35.27 mA cm−2, respectively, and an uncoated NW exhibits J
sc of 31.15 mA cm−2. The planar structure without coating gives a J
sc of 24.86 mA cm−2, which is significantly lower than the nanostructured solar cells. Finally, a Lumerical 3D charge transport simulator is used to perform electrical stimulation of ZnO-coated structure, which offers maximum ideal J
sc. A detailed electrical performance analysis of GaAs0.99Bi0.01/CSC/ITO unit NW solar cell for ZnO, TiO2 and Ta2O5 as ESCs and MoO2 as HSC is also covered in this article. ZnO as an ESC offers the best photo-conversion efficiency (PCE) of ∼25% and open-circuit voltage (V
oc) of 0.95 V for a very small minority carrier lifetime (Ʈn) of 0.1 ns for GaAs0.99Bi0.01 and Ʈn of 1 ps for ZnO, with high surface recombination velocity of 105cm s−1 at the interfaces.
Structure, morphology and magnetic performance of (Fe65Co35)
x
@(Ni0.5Zn0.5Fe2O4)100–x
nanocomposite thin films
Authors: Wang Jun Bao , Xiao Wei Wei , Ma Dian Guo , Wang Lu , Liu Yun Yun , Tian Xiao Zhong , Liang Lan Ju , Gao Ju
Published: September 2024

A bi-magnetic phase (Fe65Co35)x@(Ni0.5Zn0.5Fe2O4)100–x nanocomposite thin film was created by combining Fe65Co35 alloy nanoclusters produced through plasma gas condensation with Ni0.5Zn0.5Fe2O4 thin film prepared via RF magnetron sputtering. The study revealed that the Fe65Co35 alloy nanoclusters, with an average particle size of approximately 6 nm, are surrounded by the amorphous ferrite phase, forming a granular ‘core–shell’ structure. As the proportion of Fe65Co35 alloy nanoclusters increased from 5.9 wt% to 35.4 wt%, the grain size of the nanocomposite thin films decreased from 24 nm to 10.4 nm. Magnetic analysis demonstrated that the nanocomposite thin films displayed soft magnetic properties at room temperature. With an increase in Fe65Co35 content, the saturated magnetization of the nanocomposite thin films escalated from 68 emu cm−3 to 214 emu/cm3, significantly surpassing that of the corresponding NiZn ferrite films (∼17 emu/cm3). The fluctuation of coercivity is intricately linked to the grain size of the nanocomposite thin films, and at 24.5 wt% of Fe65Co35 alloy nanoclusters, the coercivity is minimized to 14 Oe. The ferromagnetic resonance spectra of the nanocomposite films exhibited some asymmetric broadening and shift. As the Fe65Co35 content increased, the resonance field initially decreased and then rose, while the resonance linewidth gradually decreased.
Boosting efficiency in dual-absorber RbPbBr3 perovskite solar cell: the role of two-dimensional GeS and SnS2 as electron transport layers
Authors: Rafiee Rafat Shahram , Ahangari Zahra , Ahadian Mohammad Mahdi , Hosseini Seied Ali
Published: September 2024

This paper presents a comprehensive investigation into the electrical characteristics of a perovskite solar cell. The n-i-p cell is based on a low band gap rubidium–lead-bromide (RbPbBr3) perovskite with an energy level of 1.31 eV. The study also evaluates the impact of high mobility two-dimensional GeS and SnS2 as electron transport layers (ETLs) on the cell’s performance. These ETLs have a wide band gap and provide a hole blocking layer due to their high valence band-offset. Additionally, a thin film MoTe2 with a band gap of 1 eV is considered as a complementary absorber for capturing near-infrared solar spectrum. The investigation focuses on the influence of critical physical and structural design parameters on the electrical parameters of the cell. The optimized device with SnS2 as the ETL exhibits a power conversion efficiency (PCE) of 25.03%, an open circuit voltage of 0.95 V, a short circuit current density of 33 mA cm−2, and a fill factor of 80.31%. Similarly, the device with GeS as the ETL achieves a PCE of 25.14%, an open circuit voltage of 0.96 V, a short circuit current density of 33.01 mA cm−2, and a fill factor of 80.66%. Furthermore, a statistical analysis is conducted by calculating the coefficient of variation to assess the sensitivity of the cell’s electrical measures to the variation of design parameters and operating temperature. The results highlight that defects in the absorber layer, work function of the back contact, and ambient temperature are critical design parameters that can significantly impact the device performance. Overall, the utilization of high mobility wide band gap ETLs, in combination with the low band gap perovskite, offers a promising approach for the design of high-performance solar cells.
Leading two-point resistances from transfer matrices in cylindrical, spider web, axial and grid resistor networks
Authors: Perrier Frédéric , Girault Frédéric
Published: September 2024

Resistor networks are increasingly being considered in heuristic research as models for natural or artificial matter. The equivalent resistance between two nodes, the Two-Point Resistance (TPR), can be calculated using a variety of methods. The transfer matrix (TM) method was originally considered as a numerical tool for estimating percolation thresholds in random networks with a repeating pattern. The TM method is revisited here as an efficient tool to obtain, in a fast and elegant way, iteration relations and exact explicit expressions for leading TPRs that include a node in the last repeated pattern. Several rotationally invariant networks are studied, such as simple cylindrical networks, spider web networks and cylindrical networks with a central resistive axis, in which case the TM matrices are circulant matrices. Examples of explicit expressions are given for orders of rotation ≤4 or 5, depending on the case. The method can be applied in a similar way to networks with less symmetry, such as grids. The general expressions of TPRs obtained using the TM method can provide quantitative guidelines for resistor networks developed in materials science, environmental issues or industrial applications.
High performance NiCoSe2@NiFe-MOF@AC Nanocomposite electrode for energy storage and precise detection of mono-sodium glutamate
Authors: Safdar Samia , Mumtaz Muhammad Azhar , Afzal Amir Muhammad , Muzaffar Nimra , Waris Muhammad Hamza , Iqbal Muhammad Waqas , Mumtaz Sohail , Iqbal Muhammad Zahir , Zafar Muhammad , Alaraidh Ibrahim A , Okla Mohammad K
Published: September 2024

Hybrid supercapacitors, a fascinating appliances that combines the best of both batteries and supercapacitors, showcase remarkable improvements in power and energy densities. Here, a two-step technique was used to synthesis NiCoSe2@NiFe-MOF. In first step NiCoS was synthesis using electrodeposition approach and in second step the NiCoSe2@NiFe-MOF was synthesis using vacuum-assisted filtering. The specific capacitance of the NiCoSe2@NiFe-MOF composite used as the supercapacitor electrode in a three-electrode system was (2882.5 F g−1) and specific capacity is 1729.8 C g−1, much greater than that of the NiCoSe2 electrode material which was 967.4 C g−1 at current density of 1.5 Ag−1, In addition, a hybrid supercapacitor device (NiCoSe2@NiFe-MOF//AC) has been developed and successfully demonstrates a specific capacity of 205.45 C g−1 at 0.5 A g−1. The energy density is measured in units of WhKg−1 with a numeric values of 78.3, while at 2.9 KWKg−1 the power density is recorded. This device has been tested for up to five thousands cycles of discharging (87.8%) and charging (94.2%), achieving an impressive capacity retention rate of 96.8%.Additionally, an amperometric immunosensor was fabricated by employing the NiCoSe2@NiFe-MOF nanocomposite to detect Mono-Sodium Glutamate (MSG). A constant linear association was observed between the concentration of MSG and the variation in current, encompassing the entire detection range of 0.05–200 μM. The findings of our study offer an exciting starting point for the development of energy storage systems with greater capacity.
Static reconfiguration method of photovoltaic array based on improved competence square
Authors: Yi Lingzhi , Tan Jingxuan , Wang Yahui , Luo Bote , Fan Lü , Cheng Siyue
Published: September 2024

Partial shading can reduce the power output of a photovoltaic (PV) array due to mismatch losses. Therefore, various static and dynamic reconfiguration techniques have been proposed to address this problem. Although dynamic reconfiguration methods are fast and flexible, they face challenges such as complex hardware circuits and high costs. In contrast, static reconfiguration methods simplify control complexity, improve system stability, and significantly reduce costs. Among the existing static reconfiguration techniques, the competence square (CS) method, which changes the physical positions of PV panels without modifying the total cross tied (TCT) based electrical connections, has been introduced to enhance power generation. However, this arrangement faces drawbacks due to the lack of effective chromatic dispersion and insufficient power enhancement under shading conditions. This paper proposes an improved competence square (ICS) reconfiguration method to further improve the power output. The ICS method first reconfigures the PV array using the CS method, then applies the lo shu (LS) method for secondary reconfiguration to determine the optimal connections. This method is compared with TCT, CS and improved northern goshawk optimization (INGO) methods. Additionally, the performance of the proposed method is evaluated against various existing photovoltaic array configurations by comparing the global maximum power point (GMPP), fill factor (FF), mismatch loss (ML), and power enhancement (PE). The experiment shows that under shading conditions of square shading, rectangle shading, trapezoid shading, triangle shading, L-shaped shading, cross shading, discontinuous shading, and irregular shading, reconfiguring PV arrays using ICS consistently achieves the highest power improvement. Compared to TCT, the power output increases significantly by 16.6%, 2.1%, 18.0%, 16.0%, 19.1%, 5.0%, 4.0%, and 3.0%, respectively. Comparison results validate the proposed ICS method in enhancing the global maximum power under shaded conditions.
CMB-PAInT: An inpainting tool for the cosmic microwave background
Authors: Gimeno-Amo C. , Martínez-González E. , Barreiro R.B.
Published: September 2024

The presence of astrophysical emissions in microwave observations forces us to perform
component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the
most optimistic cases, there are still strongly contaminated regions, such as the Galactic plane
or those with emission from extragalactic point sources, which require the use of a mask. Since
many CMB analyses, especially the ones working in harmonic space, need the whole sky map, it is
crucial to develop a reliable inpainting algorithm that replaces the values of the excluded pixels
by others statistically compatible with the rest of the sky. This is especially important when
working with Q and U sky maps in order to obtain E- and B-mode maps which are free from
E-to-B leakage. In this work we study a method based on Gaussian Constrained Realizations
(GCR), that can deal with both intensity and polarization. Several tests have been performed to
asses the validation of the method, including the study of the one-dimensional probability
distribution function (1-PDF), E- and B-mode map reconstruction, and power spectra estimation. We
have considered two scenarios for the input simulation: one case with only CMB signal and a second
one including also Planck PR4 semi-realistic noise. Even if we are limited to low resolution maps,
Nside = 64 if T, Q and U are considered, we believe that this is a useful
approach to be applied to future missions such as LiteBIRD, where the target are the
largest scales.
Dark-bright solitons and the role of their interaction in breather generation
Authors: Li Le , Che Wen-Juan , Liu Xi-Zhe , Liu Chong , Akhmediev Nail
Published: September 2024

We study fundamental dark-bright solitons and the interaction of vector nonlinear Schrödinger equations in both focusing and defocusing regimes. Classification of possible types of soliton solutions is given. There are two types of solitons in the defocusing case and four types of solitons in the focusing case. The number of possible variations of two-soliton solutions depends on this classification. We demonstrate that only special types of two-soliton solutions in the focusing regime can generate breathers of the scalar nonlinear Schrödinger equation. The cases of solitons with equal and unequal velocities in the superposition are considered. Numerical simulations confirm the validity of our exact solutions.
Vectorial manipulation of twisted vector vortex optical fields in strongly nonlocal nonlinear media
Authors: Liu Cai-xia , Hu Xiao-bo , Wu Feng-min , Chen Rui-Pin
Published: September 2024

We theoretically investigate the propagation properties and vectorial manipulation of twisted vector vortex beams (TVVB) with a cross-phase in a strongly nonlocal nonlinear medium (SNNM). The root mean square beam-width (RMS-BW) and the critical power required to retain the invariant RMS-BM of the TVVB in an SNNM are derived using the coupled nonlocal nonlinear Schrödinger equation. Numerical calculations reveal novel characteristics of the evolution of the state of polarization (SoP) and the optical intensity distributions during the TVVB propagating in an SNNM. It is found that mode conversions between a Laguerre Gaussian and a Hermite Gaussian mode take place during propagation in an SNNM, and the topological charge of the TVVB can be accurately measured by observing the interference intensity structure in the cross-section. Manipulation of the beam shape, SoP, and rotation of the TVVB is achieved by controlling factors such as the initial power, twisting coefficient, initial beam-width, and topological charge. These findings hold promise for applications in optical micro-manipulation, optical communication, and material processing.
Carbon-based Wearable Pressure Sensor System for Real-time Step Frequency Monitoring
Authors: Zhao Weikai , Liu Haibo , He Pei , Yang Junliang
Published: September 2024

Wearable pressure sensors have attracted great attention in human motion and health monitoring due to their sensitivity, flexibility and portability that can provide continuous physiological information recording. However, current pressure sensors used for wearable motion monitoring suffer from low sensitivity, poor resistance to interference, and the inability to be mass-produced. In this study, we proposed the utilization of multi-walled carbon nanotubes (MWNTs) as sensing materials, fabric as substrates, and screen printing process for fabricating flexible pressure sensors. The fabricated sensors exhibited a high sensitivity at low pressure, and good stability of more than 3000 cycles. Moreover, we designed a wearable step frequency monitoring system for real-time recording of footstep frequency during human walking activities. The results demonstrated that the system accurately monitors frequency under different walking speeds and footstep activities during various movements, providing a promising strategy to develop wearable and wireless sensing system for real-time motion monitoring.
Rapid Label-free and Amplification-free Detection of SARS-CoV-2 Using Solution-Gated Graphene Transistor-Based Nucleic Acid Biosensors in a Portable Biosensing Microsystem
Authors: Yu Haiyang , Li Jun , Liu Zhe , Feng Linrun , Li Jinhua , Tang Wei
Published: September 2024

The COVID-19 pandemic has highlighted the significance of swift and efficient large-scale screening to prevent epidemic outbreaks. Solution-gated graphene transistors (SGGTs) have emerged as a valuable asset in creating point-of-care (POC) sensing platforms for detecting SARS-CoV-2, owing to their notable stability and sensitivity in solution environments. However, the poor interface engineering of sensing electrodes is of great concern for reliable functionalization, leading to poor sensitivity. In this study, we present an interface engineering strategy for realizing the functionalization of SGGT sensing electrodes with high stability and sensitivity to construct a SARS-CoV-2 nucleic acid biosensor. The developed biosensor exhibits the capability to detect ORF1ab gene fragments at a concentration as low as 10−16 M without requiring additional nucleic acid amplification. Furthermore, the entire detection process can be accomplished using a portable biosensing microsystem within 30 minutes. This research holds promise for advancing the study of FET-based biosensors and facilitating their practical application in clinical settings.
Design and Investigation of a 10 Gb/s Hybrid Spatial-time Diversity FSO-CDMA Communication System
Authors: Ji Jianhua , Zheng Zihua , Zhang Wanying , Cao Wenming , Wang Ke , Xu Ming
Published: September 2024

This paper presents a novel strategy for free space optical (FSO) communication system that combines hybrid spatial-time diversity and optical code division multiple access (OCDMA). The authors demonstrate a 10 Gb/s hybrid spatial-time diversity FSO-CDMA experimental system for the first time. They investigate the bit error rate (BER) and physical-layer security under weak and strong turbulence conditions. The experimental results demonstrate that the proposed scheme can improve the performance of the FSO-CDMA system. In the hybrid spatial-time diversity FSO-CDMA system, the BER of the eavesdropper (Eve) exceeds the hard-decision forward-error-correction threshold of 3.8E-3. It is also worth noting that Eve can intercept and recover data without a matched decoder in a spatial diversity FSO-CDMA system. As a result, the proposed scheme can simultaneously enhance reliability and physical-layer security compared to time or spatial diversity systems.
Physical Layer Security of Fiber-optic Wiretap Channel with Forward Error Correction Coding
Authors: Xu Rongwo , Ji Jianhua , Wang Zhenhong , Song Yufeng , Wang Ke , Xu Ming
Published: September 2024

In this paper, by using effective leakage value, we quantitatively assess the security performance of the fiber-optic wiretap channel with forward error correction coding. As the eavesdropper is far from the transmitter, effective leakage value initially decreases slowly and then will vary rapidly. As the eavesdropper is close to the transmitter, effective leakage value of (7,4) block code is larger than that of the (7,3) block code. However, when the eavesdropping distance is far, the system security performances of both are almost the same. Furthermore, effective leakage value using OTDR is analyzed and discussed.
Base Station Energy Saving based on Imitation Learning in 5G Network
Authors: Li Ziyi , Wang Yu , Fan Yanlin , Wang Zhaobo , Lin Shangjing , Sun Lei
Published: September 2024

With the rapid development of communication technology, the large-scale deployment of base stations (BSs) has led to an increase in power consumption. To reduce power consumption, energy saving technologies for BSs have emerged, which are in line with the concept of green communications and can save operators’ costs. In this paper, our goal is to minimize the total power consumption of the base station by dynamically controlling the switching status of the base station. This article first proposes a dynamic base station switching framework based on deep reinforcement learning (DRL), which optimizes the power consumption of switching BSs. Then, considering the dynamic nature of the environment, this article proposes a dynamic BS switching algorithm that introduces the idea of imitation learning (IL) to update the policy by learning the expert’s action. The simulation results show that this scheme can effectively reduce power consumption.
SSFPN: Selective Spatial Feature Pyramid Network for Remote Sensing Object Detection
Authors: Xu Ziming , Ren Bin , Zhang Kunhua
Published: September 2024

Object detection, particularly for oriented small objects, benefits greatly from the generation of multi-scale feature maps by the feature fusion module. Despite the success of series of Feature Pyramid Network models in general object detection, their application in remote sensing object detection has received limited attention. Small oriented objects require contextual information for detection, while various types of objects need different long-range context. In this paper, we propose an intuitive and simple fusion module to be added in Feature Pyramid Network called Selective Spatial Feature Pyramid Network (SSFPN) to address these challenges. SSFPN dynamically adjusts the spatial receptive field across multi-scale feature maps, enhancing the modeling of contextual variations among different objects in remote sensing scenarios. In extensive experiments, SSFPN has achieved competitive results, i.e., an improvement of 0.34% after adding SSFPN to the Oriented RCNN model. The codes are available at https://github.com/Atlantisming/SSFPN.
Self-supervised Entity Alignment Model Based on Joint Embedding
Authors: Mao Zhifang , Fan Chunxiao , Wu Yuexin
Published: September 2024

Entity alignment is an important problem for constructing Web-scale KGs. Self-supervised entity alignment models represented by SelfKG, proposed in 2022, have eliminated the essential requirement of accurate alignment: human labeling, which significantly saves resources. However, when SelfKG scales up to improve entity alignment accuracy, it introduces neighbor noise, leading to a decrease in alignment performance. This indicates that the ability of self-supervised models to aggregate and utilize knowledge graph information needs further exploration. To address this issue, we proposed the following approach: using a Graph Convolutional Network(GCN) to collect global entity and structural information, and a Graph Attention Network(GAT) to collect local neighborhood information from subgraphs. Subsequently, we introduced a novel fusion method to merge the two parts through weighted sum and residual connection, and completed self-supervised entity alignment using the Relative Similarity Metric(RSM) mechanism proposed by SelfKG. This model has both the ability to scale up and the flexibility to avoid neighbor noise, resulting in a significant improvement in performance.
Small Object Detection with lightweight PointNet Based on Attention Mechanisms
Authors: Peng Hao , Huang Duan
Published: September 2024

In response to the issue of subpar small object detection outcomes, the improved 3D object detection method for Point Net is proposed. First, multi-scale fusion method is added to the channel attention mechanism into the feature extraction stage of Point Net; then, the loss function is adjusted to optimize the backbone network and reduce the number of model parameters while improving the accuracy. The experimental results show that in the dataset, the proposed method has higher detection accuracy, the improved algorithm average accuracy improves 3.9%, the model size decreases 20%, effectively improves the detection effect of small objects, and realizes the lightweight of the network.
Focus-SLAM: A visual Monocular SLAM
Authors: Yin Haohui
Published: September 2024

This research presents a novel simultaneous localization and mapping algorithm, called Focus-SLAM, which simulates human navigation strategies by synthesizing a optical saliency model, SalNavNet, in a traditional single-shot SLAM paradigm. SalNavNet introduces an innovative design that incorporates a correlation module and an adaptive Exponential Moving Average (EMA) component, effectively addressing the prevalent center bias issue found in contemporary saliency models. As a result, the system enhances target fixation by accentuating salient features more effectively. Extensive experimental evaluations, conducted across a spectrum of indoor environments exhibiting diverse luminosity conditions. These findings attest to the efficacy of Focus-SLAM in enhancing both the accuracy and efficiency of SLAM operations under challenging real-world conditions.
Research on signal denoising algorithm based on ICEEMDAN eddy current detection
Authors: Liu Qi , Zhao Zhifan , Hou Huaishu , Li Jinhao , Xia Shuaijun
Published: September 2024

This study addresses the challenges of non-stationarity and
significant background noise interference in eddy current detection
signals by proposing a noise reduction method based on Improved
Complete Ensemble Empirical Mode Decomposition with Adapted Noise
(ICEEMDAN). The process commences with the signal being decomposed
using Improved Complete Ensemble Empirical Mode Decomposition with
Adapted Noise into a finite number of Intrinsic Mode Functions
(IMFs). Each Intrinsic Mode Function is then evaluated for the
presence of high-frequency noise using a Power Spectral Density
(PSD) analysis. The high-frequency noise present in the Intrinsic
Mode Functions is then reduced using Normalized Least Mean Squares
(NLMS) before being reconstructed with the remaining Intrinsic Mode
Functions. Subsequently, the reconstructed signals are subjected to
another round of decomposition using Improved Complete Ensemble
Empirical Mode Decomposition with Adapted Noise. The Pearson Product
Moment Correlation Coefficient (PPMCC) is utilised to calculate the
correlation between the Intrinsic Mode Functions within each layer,
retaining those with a strong correlation to further attenuate
noise. Ultimately, the local maxima judgement method selectively
amplifies defect signals by assessing changes in peak and valley
degrees, thereby improving the signal-to-noise ratio of the eddy
current detection signal. The experimental results demonstrate that,
in comparison to the use of only the conventional Improved Complete
Ensemble Empirical Mode Decomposition with Adapted Noise and
Normalized Least Mean Squares denoising methods, the proposed method
increases the Signal-to-Noise Ratio (SNR) by 1.08 dB and 2.31 dB,
respectively, and decreases the Mean Square Error (MSE) by 106.9 and
223.9, respectively. The false alarm rate for stainless steel welded
tubes with defects is 1.4%, while the false alarm rate for
stainless steel welded tubes without defects is 0.4%.
Assessment and pre-assessment of compound hot and drought events over Yangtze River Basin
Authors: Mei Mei , Zhang Ying-Xian , Wang Guo-Fu
Published: September 2024

The severe compound hot and drought event (CHDE) in 2022 had serious impacts on water resources, agriculture, power supply, and ecosystems in the Yangtze River Basin (YRB). In this paper, we asked, have similar spatiotemporally overlapping compound events, like the one observed in 2022, occurred historically in the basin? And, if so, how can we pre-assess the impacts of such potential events on subseasonal timescales? To address these questions, regional CHDEs in the YRB since 1961 were systematically identified and comprehensively assessed using a modified intensity–area–duration technique and hazard assessment methods. Additionally, the subseasonal pre-assessment capability for CHDEs in the YRB using the China Meteorological Administration’s third-generation climate model prediction system (CPSv3-S2S) was demonstrated. A total of 140 CHDEs occurred during 1961–2022, with the 21st century showing a remarkably high risk of such events. Among these, 2022 was the most intense year, with the event from July 26th to August 30th being unprecedented in severity. CPSv3-S2S effectively forecast this event’s occurrence within a 1–25 lead days, particularly in pre-assessing its extensively impacted area and high-hazard centers in the upper and middle reaches of the main river course. This pre-assessment method serves as a valuable reference in decision-making to anticipate and mitigate the risks of hydropower supply shortages and heightened electricity demand during extremely high temperatures in upstream areas.
Spatiotemporal distribution of global wind erosion over the past four decades
Authors: Chu Zhaohan , Liu Maodian , Zhang Qianru , Cai Xingrui , Zhang Yanping , Hu Tao , Qiu Xinran , Huang Zhe , Wang Xuejun
Published: September 2024

Wind erosion is a critical environmental issue that degrades land and air quality, affecting global ecosystems, agriculture, and human health. Yet, on the global scale, the long-term spatial variability and controlling factors of wind erosion remain highly uncertain. Here, we develop a high-resolution spatiotemporal dataset of global wind erosion from 1980 to 2020 using the Revised Wind Erosion Equation model, integrated with comprehensive meteorological, terrestrial ecology, and soil datasets. Our analysis indicates that wind erosion annually impacted 359 ± 25 petagrams of soils worldwide during this period. Approximately 70% of this erosion occurred in just ten countries, predominantly in Africa and the Middle East. Due to higher erosion intensities, pasturelands, accounting for 28% of all non-barren land use types, disproportionately contributed to 70% of the erosion in these areas. Furthermore, our analysis highlights an upward trend in global wind erosion over the past four decades, with affected areas expanding worldwide. Although our study reinforces that changing wind speeds and a drier climate are central factors impacting global wind erosion, we find that increasing erosion intensities in pasturelands may also exacerbate erosion in North Africa, South America, and East Asia. This has broad implications for soil erosion issues that impact food productivity, human health, and ecosystem stability. This research provides insights for developing wind erosion warnings and targeted mitigation strategies, supporting global efforts to combat environmental degradation and promote sustainable development.
Flow of temporal network properties under local aggregation and time shuffling: a tool for characterizing, comparing and classifying temporal networks
Authors: Le Bail Didier , Génois Mathieu , Barrat Alain
Published: September 2024

Although many tools have been developed and employed to characterize temporal networks (TNs), the issue of how to compare them remains largely open. It depends indeed on what features are considered as relevant, and on the way the differences in these features are quantified. In this paper, we propose to characterize TNs through their behavior under general transformations that are local in time: (i) a local time shuffling, which destroys correlations at time scales smaller than a given scale b, while preserving large time scales, and (ii) a local temporal aggregation on time windows of length n. By varying b and n, we obtain a flow of TNs, and flows of observable values, which encode the phenomenology of the TN on multiple time scales. We use a symbolic approach to summarize these flows into labels (strings of characters) describing their trends. These labels can then be used to compare TNs, validate models, or identify groups of networks with similar labels. Our procedure can be applied to any TN and with an arbitrary set of observables, and we illustrate it on an ensemble of data sets describing face-to-face interactions in various contexts, including both empirical and synthetic data.
Effect of Water Quality Parameters on Total Bacteria Vibrio sp. in The Coastal Waters of Banyuwangi Regency
Authors: Setyaningrum Ervina Wahyu , Yuniartik Mega , Yuniari Shinta Hiflina
Published: September 2024

Banyuwangi coastal is used for several fishery activities consisting of fishing, and aquaculture. Vibrio is a type of saprophytic bacteria that lives in freshwater, sea water and soil. Water quality conditions affect the presence of Vibrio sp. bacteria. In the previous study, if the temperature and salinity values in the waters are getting higher, then followed by the amount of Vibrio sp. This study aims to determine the total Vibrio sp. and their relationship with water quality parameters. The method used is the descriptive method. The data analysis used is multiple linear regression analysis. Water quality consisting of phosphate, dissolved oxygen (DO), nitrit (NO2
−) and total organic matter (TOM) together has significant effect on the total Vibrio sp (Sig. < 0.05). Partial test results of water quality on total Vibrio sp. has a P-value of phosphate value of (0.245 X1), DO (0.103 X2), Nitrite (0.029 X3), and TOM (0.218 X4). The results of this test are known to be the value of nitrite variable Sig.0.029 (Sig.<0.05) which means that it has a significant effect on the total value of Vibrio sp. Based on multiple linear regression analysis, the regression equation is obtained which is Y = −19.534 X1 − 169.86 X2 + 26.68 X2 + 14.28 X3.