bluuebunny/crossref_metadata_2025 huggingface dataset:
Duality between the quantum inverted harmonic oscillator and inverse square potentials
Authors: Sundaram Sriram , Burgess C P , O’Dell D H J
Published: May 2024

In this paper we show how the quantum mechanics of the inverted harmonic oscillator (IHO) can be mapped to the quantum mechanics of a particle in a super-critical inverse square potential (ISP). We demonstrate this by relating both of these systems to the Berry–Keating system with Hamiltonian

H
=
(
x
p
+
p
x
)

/

2

. It has long been appreciated that the quantum mechanics of the ISP has an ambiguity in choosing a boundary condition near the origin and we show how this ambiguity is mapped to the IHO system. Imposing a boundary condition requires specifying a distance scale where it is applied and changes to this scale come with a renormalisation group (RG) evolution of the boundary condition that ensures observables do not directly depend on the scale (which is arbitrary). Physical scales instead emerge as RG invariants of this evolution. The RG flow for the ISP is known to follow limit cycles describing the discrete breaking of classical scale invariance in a simple example of a quantum anomaly, and we find that limit cycles also occur for the IHO. However, unlike the ISP where the continuous scaling symmetry is explicit, in the case of the IHO it is hidden and occurs because the Hamiltonian is part of a larger su(1,1) spectrum generating algebra. Our map does not require the boundary condition to be self-adjoint, as can be appropriate for systems that involve the absorption or emission of particles.
Electronic states in quantum wires on a Möbius strip
Authors: Pinto J J L R , Silva J E G , Almeida C A S
Published: May 2024

We study the properties of a two dimensional non-relativistic electron gas (TDEG) constrained on wires along a Möbius strip. We considered wires around the strip and along the transverse direction, across the width of the strip. For each direction, we investigate how the curvature modifies the electronic states and their corresponding energy spectrum. At the center of the strip, the wires around the surface form quantum rings whose spectrum depends on the strip radius a. For wires at the edge of the strip, the inner edge turns into the outer edge. Accordingly, the curvature yields localized states in the middle of the wire. Along the strip width, the effective potential exhibits a parity symmetry breaking leading to the localization of the bound state on one side of the strip.
Gas concentration and refractive index sensor based on plasmonic induced absorption in metal-insulator-metal waveguide coupled with arc resonators structure
Authors: Tang Xueyun , Li Yuchang , Chen Fang , Yang Wenxing
Published: May 2024

In this paper, the plasmonic induced absorption (PIA) effect is numerically studied in a plasmonic metal-insulator-metal (MIM) waveguide coupled with disk and arc-shaped resonators. The PIA spectrum characteristics and magnetic field distributions are investigated by the Finite difference-time domain method (FDTD) method, the PIA effect originated from the coupling of two resonance modes excited by the disk resonator and the arc-shaped resonator. The coupling mode theory (CMT) is used to fit the PIA transmission spectrum, and the calculated result fits well with the simulated spectrum. A double PIA spectrum can be observed by introducing another arc-shaped resonator both on the same or the opposite side. Three different structures are designed to achieve the PIA effect, and we found the PIA response can be easily tuned by altering the structure’s parameters. Three structures are designed and compared, the PIA spectra exhibit high refractive index (RI) sensing with maximum sensitivity of

867.2

nm

RIU

−
1

.

Besides, the proposed structure can also be used as a gas concentration (GC) sensor when the polyhexamethylene biguanide (PHMB) is introduced, a maximum sensitivity of 142.1 pm/ppm is achieved for the proposed structure II, the maximum figure of merit (FOM) and Q value are 57.8 and 65.9, respectively. Therefore, the results represented in this paper will be beneficial in the fields of high-performance refractive index and gas sensors.
Light fields during inflation from BOSS and future galaxy surveys
Authors: Green Daniel , Guo Yi , Han Jiashu , Wallisch Benjamin
Published: May 2024

Primordial non-Gaussianity generated by additional fields present during inflation offers a compelling observational target for galaxy surveys. These fields are of significant theoretical interest since they offer a window into particle physics in the inflaton sector. They also violate the single-field consistency conditions and induce a scale-dependent bias in the galaxy power spectrum. In this paper, we explore this particular signal for light scalar fields and study the prospects for measuring it with galaxy surveys. We find that the sensitivities of current and future surveys are remarkably stable for different configurations, including between spectroscopic and photometric redshift measurements. This is even the case at non-zero masses where the signal is not obviously localized on large scales. For realistic galaxy number densities, we demonstrate that the redshift range and galaxy bias of the sample have the largest impact on the sensitivity in the power spectrum. These results additionally motivated us to explore the potentially enhanced sensitivity of Vera Rubin Observatory's LSST through multi-tracer analyses. Finally, we apply this understanding to current data from the last data release of the Baryon Oscillation Spectroscopic Survey (BOSS DR12) and place new constraints on light fields coupled to the inflaton.
Decoupling of peeling and ballooning thresholds for pedestal stability and reduction in ELM frequency via enhanced turbulence with edge electron cyclotron heating in DIII-D
Authors: Banerjee Santanu , Barada K. , Chrystal C. , Groebner R. , Mordijck S. , Odstrčil T. , Osborne T. , Rhodes T.L. , Scotti F. , Yan Z. , Zeng L. , Damba J. , Laggner F. , Haskey S. , Grierson B. , Chen J. , Saarelma S. , Pankin A.
Published: May 2024

The edge localized mode (ELM) frequency (f
ELM) decreased by 63% when electron cyclotron heating (ECH) deposition location is shifted from ρ = 0.4 to ρ = 0.8 in DIII-D discharges where the power ratio between neutral beam injection (NBI) and ECH (P
NBI/P
ECH) is kept at ∼1. The performance of the pedestal in the ECH heated case is compared with a pure NBI reference discharge while keeping the total input power constant. All these discharges are performed at balanced input torque conditions. Furthermore, in the pure NBI discharge a strong decoupling of the peeling–ballooning (PB) thresholds is observed. The PB decoupling is preserved when the ECH is deposited at ρ = 0.8 and P
NBI/P
ECH ∼ 1, while the thresholds manifest a closed stability boundary when the ECH is deposited at ρ = 0.4. The inter-ELM pedestal recovery time is considerably larger for the ECH at ρ = 0.8 case. Increased pedestal turbulence is observed in beam emission spectroscopy (BES), Doppler backscattering and magnetic diagnostics for the ECH at the ρ = 0.8 case. Strong growth of a TEM-like mode is observed in BES and the mode growth is correlated with the decrease in f
ELM. In view of these observations, the increased pedestal turbulence seems to be the plausible reason behind the delayed pedestal recovery following an ELM event in the ECH at ρ = 0.8 case, and the preservation of PB decoupling through temperature pedestal profile widening. TRANSP interpretative simulations show that the ECH at the ρ = 0.8 case is more susceptible to ITG/TEM turbulence.
Active control of Alfvén eigenmodes by external magnetic perturbations with different spatial spectra
Authors: Gonzalez-Martin J. , Garcia-Munoz M. , Galdon-Quiroga J. , Todo Y. , Dominguez-Palacios J. , Dunne M. , Jansen Van Vuuren A. , Liu Y.Q. , Sanchis-Sanchez L. , Spong D. , Suttrop W. , Wang X. , Willensdorfer M. ,   the ASDEX Upgrade Team,   the MST1 Teams
Published: May 2024

Alfvén eigenmodes have been suppressed and excited in tokamak plasmas by (just) modifying the poloidal spectra of externally applied static magnetic perturbations. This effect is observed experimentally when toroidal spectra of n = 2, n = 4 as well as a mixed spectrum of n = 2 and n = 4 is applied. Under the n = 2 magnetic perturbations, the modes are excited or suppressed by modifying the coil phasing between the upper and the lower set of coils. Regardless of the absolute rotation, an even parity for the n = 4 perturbation is observed to reduce the amplitude of the Alfvénic instabilities, while an odd parity amplifies it. To combine the stabilizing (and destabilizing) effect of n = 2 and n = 4, a mixed spectrum is applied, finding similar reduction (and amplification) trends. However, the impact on the mode amplitude is more subtle, due to the reduced coil current required for a mixed spectrum. The signal level on the fast-ion loss detector is sensitive to the applied poloidal spectrum, which is consistent with Hamiltonian full-orbit modelling of an edge resonant transport layer activated by the 3D perturbative fields. An internal redistribution of the fast-ion population is induced, modifying the phase-space gradients driving the Alfvénic instabilities, and ultimately determining their existence. The calculated edge resonant layers for both n = 2 and n = 4 toroidal spectra are consistent with the observed suppressed and excited phases. Moreover, hybrid kinetic-magnetohydrodynamic (MHD) simulations reveal that this edge resonant transport layer overlaps in phase-space with the population responsible for the fast-ion drive. The results presented here may help to control fast-ion driven Alfvénic instabilities in future burning plasmas with a significant fusion born alpha particle population.
SAR Image Fusion Classification Based on Improved D-S Evidence Theory
Authors: Liang Jialu , Fang Hui , Zhang Xinggan
Published: May 2024

Applications for classifying Synthetic Aperture Radar (SAR) images are critical to environmental monitoring, urban planning, and land resource surveying. Fusion approaches work well for increasing SAR image categorization accuracy. However, effective processing of uncertainty information is frequently overlooked by conventional fusion classification systems. This paper presented a fusion classification approach for SAR images based on improved Dempster-Shafer (D-S) evidence theory, taking into account the uncertainty and possible conflicts in the classifiers’ output. First, after adaptively identifying the optimal hyperparameters of models, the SAR data is identified using Gradient Boosting Machine (GBM), Multilayer Perceptron (MLP), and Random Forest (RF). Different weights are then allocated in accordance with the variations in classifier performance. Ultimately, enhanced D-S evidence theory is used to integrate the output of these classifiers. In addition, uncertainty in classification results is also modeled and visualized. Experiments with Flevoland and Oberpfaffenhofen datasets show that the accuracy of this method is 85.21% and 91.88% respectively, outperforming both the soft voting ensemble classifier (SVE) and D-S evidence theory fusion method. This approach enhances the comprehension and capacity to manage uncertainty in the model output in addition to increasing the accuracy and reliability of the classification of SAR data.
A Digital Animation Generation Model Based on Cycle Adversarial Neural Network
Authors: Xu Juan , Xu Lijun , Zhang Kai , Yang Qing
Published: May 2024

This paper proposes a digital animation generation model based on Cycle Adversarial Neural Network (CycleGAN). Compared with the classical CycleGAN, this research presents a multi-attention approach to enhance the network’s generalization. Specifically, a style enhancement module and a style cross-attention mechanism are introduced into the generator network structure, which enables the model to better parse the structural information of the content image and realize the accurate matching of content features and style features. Furthermore, the introduction of a multi-scale discriminator with a fused attention mechanism enhances the preservation of content information from the source image in the output animated image. The experiments conducted in this study demonstrate that the model proposed in this paper exhibits superior performance in generating digital animation. This model not only enhances the realism and variety of the generated effects, but also achieves significant improvements in the coherence and stability of long time-series animation. The contribution of this paper lies in the introduction of the multi-attention mechanism, which enhances the generalization of the network and is of great theoretical and practical significance for the development of the field of digital animation generation.
Boosting Performance on 3D Object Detection with a Plug-in Discrimination Module
Authors: Yang Yi , Zhang Zhang
Published: May 2024

Around-view multi-camera 3D object detection in BEV (Bird’s-Eye-View) space has been a research focus over the past few years. As a typical supervised training task, many researchers promote this area with different task-specific key designs, such as exploiting temporal information and correspondence of perspective image plane and BEV space. Most of these works follow the DETR detection framework, yet the nature of learnable queries in DETR, the encodings of objects’ center and bounding box information, have not been discussed in previous studies. In this paper, we take advantage of this prior and further extend it to 3D detection tasks. In 3D object detection, the ground-truth bounding boxes are hardly overlapping. Therefore, the queries should be more diverse under this hypothesis. To achieve this goal, we propose a Plug-in Discrimination Module (PDM) to discriminate learnable queries from all the other queries with a discrimination loss to ensure the diversity of queries. The PDM is a simple train-time-only module. It contains a query projection head to project all the object queries into a common latent space. In the latent space, the discrimination loss is conducted on all the queries. Experimental results show that this design can directly improve the 3D detector’s performance without modifying the detector’s architecture and adding extra inference costs. The NDS improvement on the nuScenes dataset is up to a maximum of 1.62% in the 8th training epoch and remains an average 0.64% improvement in the following epochs, compared with the baseline model.
Improved DSFD Algorithm for Balancing Speed and Accuracy
Authors: Wang Lihui , Hu Xichuan
Published: May 2024

Aiming at the mismatch between speed and accuracy of DSFD face detection algorithm, a lightweight network method based on improved DSFD is proposed. First, the backbone of the algorithm is replaced with EfficientNet B1, which greatly reduces parameters and computation. Then the feature pyramid network in feature enhance module is changed to BiFPN to further enhance the feature fusion. Finally, to improve the efficiency, dilated convolution layers in feature enhancement module are removed, and the convolution layers of BiFPN is replaced by ACBlock. The improved algorithm was evaluated on WIDER FACE and the effectiveness of the proposed methods are evaluated through ablation experiments. The detection speed of the improved algorithm is increased by twice. Compared with two popular algorithms, the improved algorithm achieves higher accuracy.
Building Edge Detection Technology From Remote Sensing Image Based On NSCT And Tensor Voting
Authors: Wu Yingbin , Zhao Peng , Zhou Mingquan , Geng Shengling , Zhang Dan
Published: May 2024

An edge detection technology based on the combination of non-downsampling contour wave transform (NSCT) and tensor voting is proposed, which aims to obtain more accurate and detailed edge information of buildings in remote sensing images. Firstly, NSCT is used for image decomposition to obtain the subband frequency information of different scales and angles. Then, position encoding is performed on these subband coefficients to obtain second-order symmetric tensors at the corresponding positions. Tensors of different scales and angles at the same position are weighted and summed to complete feature fusion. Finally, the edge features of the image are obtained based on tensor voting theory. The experimental results show that compared to common edge detection technologies, such as Canny, Fast Edge (Fast edge detection using structured forests) and HED (Holistically-Nested Edge Detection), our method can more accurately and intensively reflect the boundaries of buildings and the edge information of roofs, providing better support for the analysis of building types and architectural styles. Compared to the HED method, which is based on deep learning, our method improves PSNR and SSIM metrics by 0.98 and 0.03, respectively.
An illumination-robust edge detection method for nuclear fuel assembly deformation measurement
Authors: Chen Rui , Cheng Yuqi , Yang Wentao , Yang Bin , Li Wenlong
Published: May 2024

Fuel assemblies (FAs) are critical components of nuclear reactor cores. The excessive deformation of FAs can pose a serious risk of safety accidents in nuclear power plants. Hence, regular monitoring of the deformation of the FAs is necessary. To accomplish this task, the most critical challenge lies in accurately extracting the edges of FAs in the nuclear underwater environment with spatial variations in illumination. In this paper, a novel illumination-robust edge detection method is proposed. Firstly, tilt correction is applied to arrange the fuel rods vertically in the image. Then, the center of each fuel rod is located through grayscale projection and filtered by rod center spacing variance minimization. Subsequently, adaptive thresholding is employed to obtain a binary image. Finally, the edges are identified by searching in the vicinity of rod centers in the binary image. The effectiveness and robustness of the proposed method have been validated in experiments, and the approach has been successfully applied to the FA deformation measurement in nuclear power plants.
Distributed drive electric vehicle differential assistance particle swarm optimization PID control
Authors: Huang Zihao , Huang Kaiqi , Lan Haoqiang
Published: May 2024

To improve the vehicle’s handling stability and enhance the steering assist effect of distributed drive electric vehicles, a differential assist steering control strategy is proposed based on the Particle Swarm Optimization (PSO) algorithm to optimize PID control parameters. A dynamic model of steering torque considering the influence of tire force is established, based on the reference steering torque to calculate the required torque. The PSO algorithm with the Integral of Time-weighted Absolute Error (ITAE) is used to optimize the parameters in the PID steering control, and wheel torque allocation is performed by using the objective function constraint. Simulation results show that the differential assistance can meet the driving requirements of drivers at both high and low speeds, and the proposed control strategy is effective.
Finite element analysis of self-tensioning and bursting of 210 L carbon fiber fully wound hydrogen storage cylinders
Authors: Pan Yingbo , Xiao Jieli , Shen Wei , Wang Hehui
Published: May 2024

This paper focuses on a 210 L carbon fiber fully wound hydrogen storage cylinder. A 1/8 scale model is selected for analysis. Using the finite element software ANSYS APDL and secondary development language, an orthotropic material performance equation is formulated and applied to the composite material lay-up. Following DOT CFFC standards, the cylinder undergoes simulated loading and unloading analysis to determine the optimal self-tightening pressure. Subsequently, progressive failure theory and the Tsai-Wu failure criterion are employed to identify the failure modes of the composite material. Continual adjustments to the element stiffness are made during the loading process. Employing the element birth and death technique, failed elements are terminated and recorded, and based on increasing trends, the burst pressure of the cylinder can be predicted. The results closely align with experimental data, validating its applicability as the basis for burst prediction.
Research on temperature rise characteristics of grease lubricated ball screw pair
Authors: Yang Linhui , Fu Jie , Pei Xiaqing , Zhang Zixuan , Fan Yuanxun
Published: May 2024

Aerospace ball screws cannot be lubricated for maintenance and replacement, so they use grease that can run for a long time and keep the performance. Under high speed and high load conditions, the ball screw will be warmed up rapidly, and the temperature has a great effect on the capability of the grease. In this paper, we deduce the formula for calculating the screw temperature, establish a thermodynamic simulation of the ball screw model to get its temperature under different conditions, and set up a test bench to try out the screw temperature rise to investigate thermal properties in the grease lubrication conditions.
Research on the calculation method of grinding temperature field of spiral bevel gear based on generative machining
Authors: Gu Biao , Wang Yuhang , Tan Rulong , Zhang Weiqing
Published: May 2024

At present, the process parameter setting of spiral bevel gear grinding is mainly based on an empirical method, and the tooth surface temperature is difficult to estimate effectively during grinding, which may lead to excessive tooth surface temperature and surface burn caused by improper selection of process parameters. Aiming at the above problems, this paper presents a method for calculating the temperature field of spiral bevel gear forming based on a combination of analytical and numerical methods. The motion equation of spiral bevel gear grinding is derived based on the method of tooth surface development. The time-varying heat flow calculation method in tooth surface grinding was developed through the discrete and two-dimensional contact zone. The time-varying temperature field analysis method of spiral bevel gear forming is developed using the time-varying heat flow and finite element calculation method. The related research can realize the temperature prediction of grinding tooth surfaces and provide the basis for improving grinding technology.
Research and design of an online monitoring device for hydrogen peroxide concentration
Authors: Yu Guangshuai , Lin Weiguo , Feng Guodong , Chen Yongmei
Published: May 2024

To address the issues of manual measurement, inaccurate instrument measurement, and frequent manual intervention required for hydrogen efficiency, oxygen efficiency, and raffinate in the production of hydrogen peroxide using the anthraquinone process, a hydrogen peroxide concentration online monitoring device was designed. The device includes a sampling module, extraction module, temperature control module, detection module, and display module. The detection module is designed based on the amperometric analysis method, using a constant potential instrument with a three-electrode system for current detection, establishing a relationship model between current and hydrogen peroxide concentration. It also includes calibration and detection modes to reduce detection errors generated during long-term operation. The device enables online analysis of hydrogen peroxide concentration through online sampling, pretreatment, and testing analysis, with a detection range of 0.05-15 g/L. The device has demonstrated good accuracy and reliability and has been tested and applied in industrial settings.
An object detection system using array planar capacitive sensors
Authors: Ma Hanxu , Wang Gang , Xu Pengyuan , Wang Hao , Huang Yulin
Published: May 2024

This paper presents a target detection system using array-based planar capacitive sensors, demonstrating excellent detection performance in gesture recognition. The system achieves gesture target classification by collecting the capacitance values of the planar capacitive sensor array and optimizing the BP neural network through a genetic algorithm for model training. Additionally, the system employs visual detection for gesture targets, using transfer learning with the MobileNet V2 network in the Keras framework to achieve gesture target classification. The system utilizes a data fusion mechanism to merge visual recognition and planar capacitive sensor array recognition for decision-making. Experimental results demonstrate that the target detection system exhibits outstanding detection performance in gesture recognition, with an average accuracy of up to 98.92%.
Design of low-correlation sidelobe FSK-PSK waveforms with controllable frequency points
Authors: Lv Shurong , Liu Siqi , Shi Huili , Zhang Jindong
Published: May 2024

Frequency shift keying-phase shift keying (FSK-PSK) waveforms are recognized for their superior resolution and signal detectability. However, the optimization of FSK-PSK parameters, particularly frequency hopping control, remains challenging and can lead to increased sidelobe levels. This paper develops an optimization model to substantially enhance the controllability of hopping frequency in FSK-PSK waveforms for radar systems. By harnessing the Karush-Kuhn-Tucker (KKT) conditions, the model strategically minimizes the autocorrelation integrated sidelobe level (ISL), thereby sharpening radar target discrimination and bolstering anti-jamming capabilities. An iterative algorithm specifically addresses the model’s optimal subproblems, optimizing frequency agility and stability. Simulation results show that our FSK-PSK waveform outperforms the waveform optimized by the Multi-Objective Quantum Genetic Algorithm (MoQGA) with a 4.93 dB sidelobe suppression gain, enhancing detection accuracy and anti-jamming performance in disturbed environments.
Simulation and design optimization of embedded steam baking integrated machine bottom plate structure
Authors: Cheng Liangguo , Nie Qingfeng , Yu Keda , Chen Zhenlei , Tan Yongqiang
Published: May 2024

To address the challenges related to excessive deformation of the bottom plate during the opening and closing of the steam-baking integrated machine door, a comprehensive approach that incorporates finite element simulation and experimental testing was employed to investigate the plate’s deformation characteristics. Various structural parameters influencing the bottom plate were evaluated, and a series of enhancement strategies for the bottom plate structure were proposed. Following the optimization process, subsidence deformation of the bottom plate was reduced by 64%, and warpage deformation was reduced by 13.6%. Thus, a solid groundwork was established for subsequent structural stiffness analysis and optimization endeavors in the realm of embedded steam-baking integrated machines.
Reliability analysis of diesel engine cooling system based on improved Bayesian network
Authors: Liu Peng , Gu Yingkui , Ao Shancheng
Published: May 2024

For the benefit of solving the problem of absoluteness of conditional probability distribution and difficulty in obtaining basic event probability in Bayesian networks, this paper studies the reliability of diesel engine cooling systems through leakage noise or gate intuitionistic fuzzy Bayesian network. Firstly, the leakage noise or gate is introduced into the intuitionistic fuzzy Bayesian network, which makes the results more realistic. Secondly, prior probability in the Bayesian network is obtained based on the similarity aggregation method of triangular intuitionistic fuzzy numbers. The results show that the introduction of leakage noise or gate, intuitionistic fuzzy set, and Bayesian network can solve the problem that the probability of basic events in a Bayesian network is difficult to obtain. The conditional probability table corrected by leakage noise or gate is more realistic and greatly reduces the workload. It is determined that the two weakest components of the cooling system are the thermostat and the water pump. The results show that the way in this paper can provide support for the reliability analysis of the complex system.
Fiber-end control algorithm based on back-propagation neural network
Authors: Zhao Zhiqiang , Ouyang Xinyuan , Jia Mengzhao , Wang Yuanfei , Li Zhe
Published: May 2024

The evenness of the trajectory of the optical fiber grinding track has a substantial effect on the quality of the transmission of optical signals. To boost this transmission quality, we present a blueprint for the trajectory of the optical fiber grinding track, together with the recently introduced equipment for shaping the end-face of the optical fiber. This model establishes the correlation between the grinding trajectory and the rotational speed of the grinding motor, enabling control of the grinding trajectory of the optical fiber connector by manipulating the motor’s rotation speed. Three-speed control methods, namely the Proportional-Integral-Derivative (PID) controller, fuzzy control algorithm, and Back-Propagation (BP) neural network PID control algorithm, were compared for effectiveness using Matlab/Simulink simulation software. The BP neural network displayed exceptional performance, leading us to implement the PID control algorithm to govern the speed of the grinding motor. Our experimental findings validate the superior efficacy of the BP neural network PID control algorithm in governing the speed of the grinding motor, thereby ensuring a consistent grinding trajectory for optical fibers.
FPGA implementation of joint synchronization algorithm based on short training sequence
Authors: Liu Yuanhang , Zhang Yanmin , Zhu Bowei , Valentinovich Volvenko Sergey , Xu Yidong
Published: May 2024

Synchronization processing is a vital component of the Orthogonal Frequency Division Multiplexing (OFDM) receiver, playing a decisive role in determining the performance of the OFDM receiver. Based on the repetitive structure of the Short Training Sequence (STS) in the IEEE 802.11 physical layer protocol data unit, this paper proposes and implements a joint synchronization algorithm to address issues related to data packet detection and coarse frequency offset correction during the synchronization process. Through software simulation and Field-Programmable Gate Array (FPGA) board-level validation, it is concluded that the algorithm ensures performance while, to some extent, conserving FPGA resources.
Coverage optimization of wireless sensor networks based on bottle sea sheath optimization algorithm
Authors: Ou Xiaopeng , Yang Xu
Published: May 2024

To tackle the problem of inadequate placement of wireless sensor networks’ sensor nodes, a proposed algorithm aims to enhance network coverage through a more optimal approach. Recognizing limitations in the Salp Swarm Algorithm (SSA) optimization, specifically its insufficient local search capability and susceptibility to local extreme values, a hybrid strategy is introduced in the search step. This strategy involves adaptive weight factor adjustments and incorporates Levy flight, achieving a better balance between global search, convergence speed, and computational accuracy. Consequently, this refinement contributes to improved effective network coverage, enhancing the overall network coverage in wireless sensor networks and facilitating faster coverage of the nodes.
A point cloud semantic segmentation method with augmented local geometry
Authors: Wang Zhiyuan , Wang Haifeng , Han Cong , Ma Yuhui , Wang Jiaxu
Published: May 2024

With the development of 3D sensors, complex spatial structures can be established from point cloud data. Accurate semantic segmentation of 3D point clouds is beneficial for tasks such as robotic scene understanding. To extract the geometric features of the point cloud, most prior works use the xyz coordinates to potentially learn the shapes of 3D objects, which is not insufficient to handle complex scenes. In this paper, a Local Geometry Encoding (LGE) module is proposed to provide local normal information and express 3D shapes explicitly. Furthermore, considering that most prior methods use a single decoder to recover from abstract features, a Multi-Decoder (MD) ensemble module is proposed to restore multiple segmentation results from various scale feature maps in the encoder, and then a multi-attention fusion mechanism is utilized to produce single segmentation results. Benefiting from the local geometry encoding module and Multi-Decoder ensemble module, our network performs 6-fold cross-validation on the S3DIS dataset and achieves 75% mIoU with fewer parameters.
Study of the energy calibration of the DEAP-3600 detector using Na-22 source data and simulations
Authors: Luzzi L. ,   the DEAP-3600 collaboration
Published: May 2024

DEAP-3600 is a single-phase liquid argon (LAr) direct-detection dark matter experiment, operating 2 km underground at SNOLAB (Sudbury, Canada). The detector consists of 3.3 tons of LAr contained in a spherical acrylic vessel. At WIMP mass of 100 GeV, DEAP-3600 has a projected sensitivity of 10-46 cm2 for the spin independent elastic scattering cross section of WIMPs. Radioactive sources have been used for the energy calibration and to test the detector performance. One of the most effective calibration run has been taken with a 22Na source deployed in a tube located around the DEAP-3600 steel shell. The simultaneous emission of three γs by the source provides an excellent tagging for the 22Na decay. The results concerning the energy response of the detector and the agreement between data and Monte Carlo simulations in DEAP-3600 are investigated in this study.
Secondary estuarine circulation and the related vertical mixing at the sill of Ambon Bay, eastern Indonesia
Authors: Giliant Salamena Gerry
Published: May 2024

Secondary estuarine circulation at the sill of Ambon Bay during wet season (July 2019) was investigated to add important insights into the existing knowledge on primary estuarine circulation done by a recent study. The datasets from the previous study were employed to calculate tidal-mean vertical advection as secondary estuarine circulation at the sill. Vertical mixing at the sill was also quantified using the continuity equation. The vertical profiles of vertical advection at the sill of Ambon Bay formed bow-like shapes with zero value at the surface that increased to reach maximum at the mid-depth of the sill (∼6 m depth), subsequently decreasing to zero at the seabed. Vertical advection at the sill was found to be larger during spring tide (∼2.5 × 10−3 m/s) than during neap tide (∼1 × 10−3 m/s). Vertical diffusivity, indicating the magnitude of vertical mixing at the sill of Ambon Bay, showed similar characteristics to vertical advection in terms of vertical profiles (bow-like shapes) and spring/neap tidal variation (spring tide value: 8.5 × 10−3 m2/s; neap tide value: ∼5 × 10−3 m2/s). The intense vertical mixing at the sill of Ambon Bay has the potential to create turbid water linked to resuspension of seabed sediment in the location.
The Effect of Different Concentration of Liquid Organic Fertilizer on the Growth of Sea Grape (Caulerpa lentillifera)
Authors: Kesaulya Gloria Hillary , Pattiasina Bethsy Jane , Loupatty Joice Wenny , Kesaulya Taufiniringsi
Published: May 2024

Sea grapes (Caulerpa lentillifera) have potential economic value and need to be conserved in their natural environment. The growth and distribution of C. lentillifera depend on physical (such as substrate) and chemical (nutrient) factors of the marine environment. The purpose of this study is to analyze the effect of different concentrations of liquid organic fertilizers on the growth of C. lentillifera in a closed culture system. This research was done from April to June 2022. The culture of C. lentillifera was done under a closed culture system using a fiber cage (50 x 50 x 60 cm) inside a (plastic) greenhouse. The experimental design used a complete randomized design of 5 treatments with three replications each. Variables observed during this study were length, weight, and sea grape ramuli quantity. The data was analyzed by using one-way ANOVA. The results show that adding liquid organic fertilizer with different concentrations has an impact on the sea grape weight (F
value
3.764 > F
tab
3.48) and an increase in the quantity of sea grape ramuli (F
value
3.608 > F
tab
3.48). The optimum concentration of liquid organic fertilizer for the growth of sea grapes was 20 ml.L−1. The culture of C. lentillifera can be done in a closed system and give good results in its growth. Further study still needs to be done by applying different treatments such as salinity and temperature in order to get exactly good conditions for C. lentillifera to grow in culture conditions and give a good quality that can be consumed and a good economic value.
Oceanic turbulence parameters recognition based on convolutional neural network
Authors: Gao Siyu , Liu Xiaoyun , Chen Yonghao , Jiang Jinyang , Liu Ying , Chai Tengfei , Jiang Yueqiu
Published: May 2024

The distortion induced by ocean turbulence has a substantial impact on the propagation of light in water, posing challenges for applications including underwater wireless optical communications and submarine surveys. Obtaining accurate information about the properties of oceanic turbulence (OT), particularly the parameters describing OT, is crucial for addressing these challenges and enhancing the performance of such applications. In this paper, we propose a convolutional neural network (CNN) and validate its ability to recognize OT parameters. The physical quantities of oceanic turbulence collectively influence the formation and strength of turbulence. We recognize the dissipation rate of temperature variance χ

T
and the turbulent kinetic energy dissipation rate ɛ, taking into account various balance parameter ω, transmission distance z. Furthermore, in order to simultaneously recognize χ

T
and ɛ, we enhanced the existing network by modifying the output structure, resulting in a dual-output architecture that facilitates concurrent classification of both χ

T
and ɛ. Our method for classifying turbulence parameters will contribute to the field of underwater wireless optical communication and promote its further development.
Breaking the mirror symmetry of photonic spin-orbit interaction using a geometrically symmetric chiral resonator
Authors: Chen Pei-Gang , Lo Tsz Wing , Lei Dangyuan
Published: May 2024

The symmetries of photonic spin-orbit interaction (PSOI) at waveguide interfaces provide flexible modulation capability but limit their practical implementation due to the stringent requirements of excitation conditions. This limitation can be mitigated by intentionally breaking local symmetries, offering a novel platform for achieving directional coupling and optical isolation with PSOI-based interfaces. For example, breaking the inversion symmetry of a nanofiber PSOI interface using a nanosphere scatterer reduces the required accuracy in the size and position of excitation spots. This study introduces a novel approach to break the mirror symmetry of a PSOI-based nanofiber waveguide by coupling it with a geometrically symmetric chiral gold nanohelicoid (GNH) resonator, which relaxes the original requirement of circularly polarized excitations. Finite-difference time-domain simulations demonstrate unidirectional light coupling and propagation under both circularly and linearly polarized excitations, showcasing the versatility of this hybrid symmetry-broken system. The Fano-like features observed in directionality spectra align with the GNH’s circular dichroism spectrum, emphasizing an intricate correlation between plasmonic near-field chirality and far-field scattering dichroism. This work paves the way for enhancing the functionalities of PSOI-based waveguide interfaces through locally coupling them with nanoscale chiral resonators, thereby expanding their application in quantum photonics, information transport and plasmonic nanophotonics.
Phase retrieval in inverse ghost diffraction using Sagnac interferometer
Authors: Gautam Akanksha , Chandra Sourav , Singh Rakesh Kumar
Published: May 2024

Ghost diffraction (GD) involves the use of non-local spatial correlations to image objects with light, which has not interacted with them. Here, we propose and experimentally demonstrate a new technique for first-order correlation measurement and retrieval of two-dimensional phase objects in the GD from inversion of the experimentally measured two-point complex correlation function in a first order interferometer. The GD scheme is experimentally implemented by a specially designed experimental setup wherein one of the orthogonal polarization components of the transversely polarized light interacts with the object and the other polarization component of the light remains intact and directly reaches the detector. The Fourier spectrum of the object is encoded into the two-point spatial correlation of these two orthogonal polarization components which is experimentally detected in an interferometer with a radial shearing in the Sagnac geometry. We experimentally demonstrated imaging of spatially varying phase objects and results are presented for three different cases.
Matrix stiffening promotes perinuclear clustering of mitochondria
Authors: Daga Piyush , Thurakkal Basil , Rawal Simran , Das Tamal
Published: May 2024

Mechanical cues from the tissue microenvironment, such as the stiffness of the extracellular matrix, modulate cellular forms and functions. As numerous studies have shown, this modulation depends on the stiffness-dependent remodeling of cytoskeletal elements. In contrast, very little is known about how the intracellular organelles such as mitochondria respond to matrix stiffness and whether their form, function, and localization change accordingly. Here, we performed an extensive quantitative characterization of mitochondrial morphology, subcellular localization, dynamics, and membrane tension on soft and stiff matrices. This characterization revealed that while matrix stiffness affected all these aspects, matrix stiffening most distinctively led to an increased perinuclear clustering of mitochondria. Subsequently, we could identify the matrix stiffness-sensitive perinuclear localization of filamin as the key factor dictating this perinuclear clustering. The perinuclear and peripheral mitochondrial populations differed in their motility on soft matrix but surprisingly they did not show any difference on stiff matrix. Finally, perinuclear mitochondrial clustering appeared to be crucial for the nuclear localization of RUNX2 and hence for priming human mesenchymal stem cells towards osteogenesis on a stiff matrix. Taken together, we elucidate a dependence of mitochondrial localization on matrix stiffness, which possibly enables a cell to adapt to its microenvironment.
GTPase activity regulates FtsZ ring positioning in Caulobacter crescentus
Authors: Barrows Jordan M. , Talavera-Figueroa Barbara K. , Payne Isaac P. , Smith Erika L. , Goley Erin D.
Published: May 2024

Bacterial cell division is crucial for replication and requires careful coordination via proteins collectively called the divisome. The tubulin-like GTPase FtsZ is the master regulator of this process and serves to recruit downstream divisome proteins and regulate their activities. Upon assembling at mid-cell, FtsZ exhibits treadmilling motion driven by GTP binding and hydrolysis. Treadmilling is proposed to play roles in Z-ring condensation and in distribution and regulation of peptidoglycan (PG) cell wall enzymes. FtsZ polymer superstructure and dynamics are central to its function, yet their regulation is incompletely understood. We addressed these gaps in knowledge by evaluating the contribution of GTPase activity to FtsZ’s function in vitro and in Caulobacter crescentus cells. We observed that a lethal mutation that abrogates FtsZ GTP hydrolysis impacts FtsZ dynamics and Z-ring positioning, but not constriction. Aberrant Z-ring positioning was due to insensitivity to the FtsZ regulator MipZ when GTPase activity is reduced. Z-ring mislocalization resulted in DNA damage, likely due to constriction over the nucleoid. Collectively, our results indicate that GTP hydrolysis serves primarily to position the Z-ring at mid-cell in Caulobacter. Proper Z-ring localization is required for effective coordination with chromosome segregation to prevent DNA damage and ensure successful cell division.
A PACAP-activated network for secretion requires coordination of Ca2+ influx and Ca2+ mobilization
Authors: Chen Xiaohuan , Bell Nicole A. , Coffman Breanna L. , Rabino Agustin A. , Garcia-Mata Rafael , Kammermeier Paul J. , Yule David I. , Axelrod Daniel , Smrcka Alan V. , Giovannucci David R. , Anantharam Arun
Published: May 2024

Chromaffin cells of the adrenal medulla transduce sympathetic nerve activity into stress hormone secretion. The two neurotransmitters principally responsible for coupling cell stimulation to secretion are acetylcholine and pituitary adenylate activating polypeptide (PACAP). In contrast to acetylcholine, PACAP evokes a persistent secretory response from chromaffin cells. However, the mechanisms by which PACAP acts are poorly understood. Here, it is shown that PACAP induces sustained increases in cytosolic Ca2+ which are disrupted when Ca2+ influx through L-type channels is blocked or internal Ca2+ stores are depleted. PACAP liberates stored Ca2+ via inositol trisphosphate receptors (IP3Rs) on the endoplasmic reticulum (ER), thereby functionally coupling Ca2+ mobilization to Ca2+ influx and supporting Ca2+-induced Ca2+-release. These Ca2+ influx and mobilization pathways are unified by an absolute dependence on phospholipase C epsilon (PLCε) activity. Thus, the persistent secretory response that is a defining feature of PACAP activity, in situ, is regulated by a signaling network that promotes sustained elevations in intracellular Ca2+ through multiple pathways.
Husserl’s Normative Account of Perception
Authors: Doyon Maxime
Published: May 2024

The aim of this chapter is to present the phenomenological notion of perceptual norms at work in the philosophy of Edmund Husserl. After having shown how his conception of intentionality departs from Brentano’s, the chapter zeroes in on his accounts of perception, illusion, and hallucination, and demonstrates the central role of coherence (Section 1.1) and optimality (Section 1.2), which are the two basic perceptual norms Husserl works with, in his phenomenological descriptions of these phenomena. The main argument of the chapter is that perception is best understood as conforming to norms of regular perceptual experiencing, whereas illusions and hallucinations are conceived as experiences of deviation therefrom (Section 1.3). Independently of the metaphysical implications one can draw from these claims (Section 1.4), the chapter argues that concordance and optimality have a constitutive function in Husserl’s framework: they constitute what perceptions, illusions, and hallucinations are.
Bodily Self-Awareness and Agency
Authors: Doyon Maxime
Published: May 2024

The idea that our perceptual openness to the world is normative can mean different things. In the Kantian tradition, it is tied to epistemic justification—to our readiness to provide reasons for our actions and our beliefs. In the phenomenological tradition of Husserl and Merleau-Ponty, the notion of norm-responsiveness relevant to perceptual experience has more to do with perception’s capacity to guide action or elicit certain behaviours. While both camps agree on the connection between perceptual consciousness and self-consciousness, there is disagreement about the nature of this relation. At stake are two conceptions of intentionality: the first is understood as a cognitive disposition that concerns our conceptual capacity to represent what there is; the second is bodily informed and includes the set of motor activities relevant for orienting and guiding perception. This chapter argues that the phenomenological model provides the best alternative to account for the normative character of perception.