bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trees versus Neural Networks for enhancing tau lepton real-time selection in proton-proton collisions
Authors: Yaari Maayan , Barron Uriel , Dominguez Luis Pascual , Chen Boping , Barak Liron , Etzion Erez , Gyres Raja 
Published: June 2024

Abstract

This paper introduces supervised learning techniques for real-time selection (triggering) of hadronically decaying tau leptons in proton-proton colliders. By implementing classic machine learning decision trees and advanced deep learning models, such as Multi-Layer Perceptron or residual neural networks, visible improvements in performance compared to standard threshold tau triggers are observed. We show how such an implementation may lower selection energy thresholds, thus contributing to increasing the sensitivity of searches for new phenomena in proton-proton collisions classified by low-energy tau leptons. Moreover, we analyze when it is better to use neural networks versus decision trees for tau triggers with conclusions relevant to other problems in physics.
Detection and Mitigation of DDoS attacks based on Multi-dimensional Characteristics in SDN
Authors: Wang Kun , Fu Yu , Duan Xueyuan , Liu Taotao 
Published: June 2024

Abstract

Due to the large computational overhead, underutilization of features, and high bandwidth consumption in traditional SDN environments for DDoS attack detection and mitigation methods, this paper proposes a two-stage detection and mitigation method for DDoS attacks in SDN based on multi-dimensional characteristics. Firstly, an analysis of the traffic statistics from the SDN switch ports is performed, which aids in conducting a coarse-grained detection of DDoS attacks within the network. Subsequently, a Multi-Dimensional Deep Convolutional Classifier (MDDCC) is constructed using wavelet decomposition and convolutional neural networks to extract multi-dimensional characteristics from the traffic data passing through suspicious switches. Based on these extracted multi-dimensional characteristics, a simple classifier can be employed to accurately detect attack samples. Finally, by integrating graph theory with restrictive strategies, the source of attacks in SDN networks can be effectively traced and isolated. The experimental results indicate that the proposed method, which utilizes a minimal amount of statistical information, can quickly and accurately detect attacks within the SDN network. It demonstrates superior accuracy and generalization capabilities compared to traditional detection methods, especially when tested on both simulated and public datasets. Furthermore, by isolating the affected nodes, the method effectively mitigates the impact of the attacks, ensuring the normal transmission of legitimate traffic during network attacks. This approach not only enhances the detection capabilities but also provides a robust mechanism for containing the spread of cyber threats, thereby safeguarding the integrity and performance of the network.
The dual effect of work rumination in the relationship between challenge stress and innovative behavior: A moderated mediation model of information literacy
Authors: yao lifeng , li siqi , yao liping , jia qin , dai jing 
Published: June 2024

Abstract

Background
Nurses encounter significant challenge stress, which has the potential to influence their innovative behavior. However, the precise mechanisms underlying this phenomenon remain unclear. This study sought to examine the mediating role of work rumination in the relationship between challenge stress and innovative behavior. Additionally, it aimed to explore the moderating role of information literacy in the association between work rumination and innovative behavior among Chinese nurses.
Methods
A cross-sectional survey was conducted among 533 nurses from 25 hospitals in China in May 2024. Participants were instructed to complete an online questionnaire designed to measure challenge stress, work rumination, information literacy, and innovative behavior. The data collected from the questionnaire was subsequently analyzed using mediation and moderated mediation analyses, carried out with the aid of the PROCESS macro in SPSS.
Results
Challenge stress was positively associated with innovative behavior (r = 0.142, p < 0.01) and work rumination (r = 0.348, p < 0.01). Work rumination partially mediated the relationship between challenge stress and innovative behavior (indirect effect: 0.279, 95% CI [0.199, 0.362]). Affective rumination had a negative indirect effect (Effect=-0.135, 95% CI [-0.222, -0.043]), while problem-solving pondering had a positive indirect effect (Effect = 0.121, 95% CI [0.064, 0.182]). Information literacy moderated the relationship between work rumination and innovative behavior (interaction term β = 0.069, p = 0.019), with the mediating effect being stronger among nurses with higher information literacy (Effect = 0.204, 95% CI [0.121, 0.287]).
Conclusion
Work rumination plays a mediating role in the relationship between challenge stress and nurses' innovative behavior. Specifically, problem-solving pondering exerts a positive influence, while affective rumination exerts a negative influence. Information literacy enhances the positive mediating effect of work rumination. These findings underscore the significance of promoting positive work rumination and information literacy to cultivate innovative behavior among nurses who encounter challenge stress.
Crossroads of Choice: A qualitative study of the factors influencing decisions to transition from sex work among women engaged in sex work in Southern Uganda
Authors: Nattabi Jennifer , Bahar Ozge Sensoy , Nabayinda Josephine , Nabunya Proscovia , Kiyingi Joshua , Kizito Samuel , Namuwonge Flavia , Nsubuga Edward , Witte Susan S. , Ssewamala Fred M. 
Published: June 2024

Abstract

Background
Women Engaged in commercial Sex Work (WESW) are exposed to behavioral, biological, and structural factors that exacerbate their risk to HIV infection and other sexually transmitted infections. While commercial sex work may appear voluntary, WESW are more likely to be constrained to selling sex due to limited viable alternatives. To effectively support this vulnerable group of women, it is critical to understand factors that facilitate and impede their decisions to transition from sex work into other careers or jobs. The current study explored women’s decision to transition from sex work into other careers or jobs.
Methods
Semi-structured in-depth interviews were conducted with 53 WESW aged 20–47 enrolled within a larger study-Kyaterekera study, a randomized clinical trial (N = 542) implemented in 19 HIV hotspots in the Southern region of Uganda. Participants were selected based on their intervention attendance (high/medium/low attendance). The interviews were conducted in Luganda the widely spoken language in the study area to explore the factors influencing women’s decisions to from transition from sex work to other jobs or careers. The main interview question used for this study was, “What are some of the factors that may influence whether you would transition from sex work to other jobs or vocations?”. All interviews were audio-recorded, transcribed verbatim and translated into English. Thematic analysis in Dedoose software was used to analyze the data.
Results
Participants reported three primary types of decisions, including considering leaving sex work, deciding to leave, and continuing sex work. The emerging themes from the interviews were categorized into individual and structural level facilitators and barriers to leave sex work. Individual level factors included issues of stigma, discrimination, and aging as factors that facilitated women’s decision to leave sex work. At the structural level, factors which include interpersonal stigma and discrimination (from immediate family and community members), physical and sexual violence and income related factors were identified as facilitators and barriers to leaving sex work.
Conclusion
Our study highlights the complex decision-making processes among WESW as they navigate transitions to alternative jobs or careers. By advocating for multifaceted interventions and policies tailored to the diverse challenges faced by WESW, our study contributes to a more informed approach to supporting their transition out of sex work.
Analysis of the Impact of Inclined Grooves on the Interior Surface of Shaped Charge Liners on the Post-Penetration Damage Effects of Fragmentation Clouds
Authors: Zhou Peng , Li Rujiang , Zhou Dan 
Published: June 2024

Abstract

Due to the fact that traditional oxygen-free copper liners rely on the Monroe effect to generate a metal jet for penetrating target armor, resulting in the formation of a fragment cloud and residual jet particles post-armor penetration, which inflict damage on the target, there is a need to enhance the damaging effect of the metal jet after penetrating armor. In this regard, an internally inclined groove liner is designed based on the traditional oxygen-free copper liner. By varying the groove depth and quantity, the post-penetration effects are investigated using the Smoothed Particle Hydrodynamics (SPH) algorithm. The results indicate that increasing groove depth affects the maximum coalescence velocity of the fragment cloud. Furthermore, the number of inclined grooves is positively correlated with the maximum coalescence velocity of the fragment cloud and has a certain impact on the maximum fragment divergence angle. A complex relationship is observed between groove depth and average single-hole area, with variations at different depths, potentially influencing the area of small expansion holes. Differences are found in the average total single-hole area and maximum expansion hole area among different groove groups, notably in the widespread distribution of single-hole areas within the 8-groove group, potentially leading to greater unevenness in expansion hole areas. Numerical simulations and experimental results demonstrate that the liner with inclined grooves generates larger perforation areas compared to the intact liner, indicating enhanced lateral killing effects. The close agreement between experimental and numerical simulations suggests that the design of inclined grooves effectively enhances the post-damage performance of the liner.
Correlation-free large-scale probabilistic computing with true-random chaotic oscillator p-bit
Authors: Lee Woojin , Kim Hyunjin , Jung Hyundo , Choi Yohan , Jeon Jinwoo , Kim Chulwoo 
Published: June 2024

Abstract

Probabilistic computing—quantum-inspired computing that uses probabilistic bits (p-bits)—has emerged as a powerful method owing to its fast search speed and robust connectivity. Previous works used linear feedback shift registers (LFSRs) or stochastic magnetic tunnel junctions (MTJs) to implement p-bits. However, in large-scale problems, periodicity and correlation issues in LFSR p-bits and inherent variations in MTJ-based p-bits with narrow stochastic regions lead to unreliable results when seeking the appropriate solution. Therefore, we propose a fully CMOS frequency-scalable p-bit implemented with a discrete-time flipped-hook tent-map chaotic oscillator. The proposed chaotic oscillator produces high-quality noise voltage that is uniformly distributed across the entire supply voltage range, enabling aligned responses of p-bits free from calibration and an input resolution of 8 bits. In contrast to LFSR-based p-bits with hardware-dependent correlation, the chaotic oscillator p-bits could factorize semiprimes with lengths up to 64 bits without changing hardware size. The chaotic oscillator exhibited an energy efficiency of 4.26 pJ/bit at 1.8 V supply voltage. The robustness and the high randomness of the proposed chaotic oscillator p-bit suggest a new direction of a p-bit scalable to large-scale probabilistic computing.
Estimating effects of ocean environmental conditions on summer flounder (Paralichthys dentatus) distribution using R-INLA
Authors: Deen Samar , Jauss Verena , Sullivan Patrick 
Published: June 2024

Abstract

The spatial distribution of summer flounder (Paralichthys dentatus) in relative abundance in survey samples differs over time with changes in environmental factors, such as bottom depth, bottom salinity, bottom temperature and sea surface temperature (SST). In 1991–2014 NOAA Fisheries have collected data on fish abundance and environmental covariates through their Fall and Spring bottom trawl surveys. We use a conditional autoregressive (CAR) model with these environmental covariates under the R-INLA framework and fit the observations over an irregular survey strata lattice. Results indicate that distributions of summer flounder stock seasonally correlate well with regional-climate-driven changes in bottom depth, bottom temperature and sea surface temperature. Estimating spatial autocorrelation and a second-order random walk in time both as fixed and random effects improved model performance. However, our study shows that such models can often inadvertently be over parameterized when including higher order interaction terms between spatial and temporal random effects. This can lead to inflated variances in the estimates and predictions as well as lengthening model convergence times. Therefore, when constructing models of this type, care should be taken in identifying the level of model complexity as well as the structural and statistical assumptions being made.
Revealing Large-Scale Surface Subsidence in Jincheng City's Mining Clusters Using MT-InSAR and VMD-SSA-LSTM Time Series Prediction Model
Authors: Yang Fan , Zhi Menghui , An Yan 
Published: June 2024

Abstract

Jincheng City's mining areas have long been plagued by surface subsidence, posing significant threats to local residents' safety and impacting the region's economic and social stability. Understanding and effectively monitoring the driving factors and mechanisms of surface subsidence are crucial for devising scientific prevention measures and promoting the sustainable development of mining areas. This article aims to comprehensively reveal the large-scale surface subsidence phenomenon in Jincheng City's mining clusters by utilizing advanced remote sensing technology and machine learning models, identifying its main driving forces, and predicting future subsidence trends to provide scientific evidence for geological disaster prevention in mining areas. The study employs Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technology, using both Permanent Scatterer Interferometric SAR (PS-InSAR) and Small Baseline Subset Interferometric SAR (SBAS-InSAR) techniques for cross-validation, to confirm the existence of surface subsidence. Further, by integrating Variational Mode Decomposition (VMD), Singular Spectrum Analysis (SSA), and Long Short-Term Memory (LSTM) networks, a high-precision time series prediction model (VMD-SSA-LSTM) was developed. The results indicate that from 2018 to 2021, the surface subsidence rates in Jincheng City ranged from − 34 to 34 millimeters per year, with significant variations in subsidence levels across different areas. Gaoping City exhibited the highest subsidence, with rates ranging from − 34 to 5 mm per year, while Yangcheng County showed the most pronounced subsidence changes. These variations are primarily attributed to mining activities, land use changes, and adverse geological conditions in Jincheng City. This study unveils the large-scale surface subsidence phenomenon in Jincheng City's mining clusters, marking the first comprehensive ground deformation monitoring analysis of small mining clusters across four cities in Jincheng. The development of a high-precision surface subsidence prediction model provides new insights for scientifically understanding geological disasters in mining areas. These findings are significant for formulating effective geological disaster prevention measures and land management policies.
Numerical analysis on the MHD flow control of the hypersonic vehicle inlet
Authors: Li Hao , Huang Hulin , Zhu Guiping 
Published: June 2024

Abstract

Under the assumption of the low magnetic Reynolds number, the coupled model of the turbulent flow field and the electromagnetic field is established to simulate the flow characteristics of Weakly Ionized Gas (WIG) in the inlet under the MHD (Magnetohydrodynamic) effect. Results show that WIG has more active thermodynamic properties than that of air in inlet. Specifically, at the throat, the thermal conductivity of WIG is augmented by 1.64 times compared to that of air. For the inlet with an MHD acceleration zone, the separation shock waves will be fallen on the third ramp and converted into the reattachment shock waves here. And the separation bubbles generated by the reattachment shock waves are weakened due to the multiple reflections before entering the isolator, hence, the wall pressure and the skin friction coefficient have a decrease in the isolator. Nevertheless, in the inlet with an MHD deceleration zone, the separation shock waves will be fallen precisely at the throat under the effect of the countercurrent Lorentz force, so that the separation shock waves are directly transformed into reattachment shock waves at the throat and all reflected into the isolator, which leads to the peak manifestation of the wall pressure and the skin friction coefficient in the isolator.
Design and Signal Decoding Test Verification of Dual-Channel Round Inductosyn Decoding Circuit
Authors: Wang Jianyuan , Hu Zhuochen , Chen Jinbao , Wang Jian , Zhou Yiling 
Published: June 2024

Abstract

During the in-orbit operation of spacecraft, permanent magnet synchronous motors are commonly used as power sources in the drive mechanisms of solar panel arrays and the high-precision servo control systems based on satellite. Apart from the performance of the motors themselves and the software control algorithms, the accuracy of the entire control system is also influenced by angle sensors used to detect the rotor position of the motors. As a high-precision angular measuring instrument, the inductosyn possesses excellent environmental adaptability and a long service life. Effectively utilizing the inductosyn can greatly enhance the performance of servo control systems. To address the complexity of the decoding process for dual-channel round inductosyn-to-digital converters, this paper proposes a design of the decoding circuit for dual-channel round inductosyn based on the parallel synchronization decoding method of two AD2S1210 RDC decoding chips. The decoding circuit amplifies the excitation signal outputted by the AD2S1210 for driving the round inductosyn, and processes the sine and cosine induction signals outputted by the round inductosyn through filtering, amplification, and other methods, by using analog circuitry, the output signals of the dual-channel round inductosyn are processed to meet the input requirements of the AD2S1210. Finally, through both Multisim simulation experiments and physical experiments, it was verified that the decoding circuit designed in this paper can process the input/output signals of the dual-channel round inductosyn and AD2S1210, successfully achieving the intended functionality. This greatly simplifies the signal decoding process for the dual-channel round inductosyn.
Tracking chromatin structure changes by single-cell multi-epigenomics with RNA polymerase II binding profiles
Authors: Ohkawa Yasuyuki , Harada Akihito , Fujii Takeru , Tomimatsu Kosuke , Kato Michiko , Ito Miho , Maehara Kazumitsu , Sato Shoko , Kurumizaka Hitoshi , Sato Yuko , Kimura Hiroshi 
Published: June 2024

Abstract

Transcription factor-bound chromatin structures regulate cell lineages in multicellular organisms. Single-cell epigenomics has the potential to reveal lineage determination on chromatin structure, but the methodology is still in development. Here, we develop single-cell combinatorial-indexing multi-target Chromatin Integration Labeling followed by sequencing (sci-mtChIL-seq) as a single-cell multi-epigenomics approach, which enables simultaneous single-cell analysis of both RNA polymerase II binding to chromatin and epigenomic factors such as transcription factors/histones. We apply sci-mtChIL-seq to analyze the binding dynamics of skeletal-muscle-specific transcription factor MyoD during mouse embryonic myogenesis. Based on RNA polymerase II-bound gene profiles, single-cells are efficiently classified into myogenic-clusters and ordered pseudotemporally. MyoD exhibits genome-wide binding in the muscle-progenitor-cell population, but in myocytes, this transitions toward enrichment in muscle-specific genes on active chromatin. Thus, sci-mtChIL-seq can be a powerful tool to analyze epigenomic dynamics in cell fate determination.
Enhanced Tire Road Friction Coefficient Estimation Through Interacting Multiple Model Design based on Tire Force Observation
Authors: Wan Wenkang , Sheng Kai , Cai Qing , Ao Lei , OuYang Nan , Feng Haoxuan 
Published: June 2024

Abstract

Accurately understanding the Tire-Road Friction Coefficient (TRFC) interaction is crucial for enhancing overall vehicle control performance. However, existing estimation methods heavily rely on the accuracy of tire modeling, which may not predict TRFC effectively under poor modeling accuracy or changing operating conditions. This paper proposes an interacting multiple-model TRFC estimation method using tire force observation. Firstly, taking advantage of the observation capabilities of distributed drive electric vehicles, a longitudinal force estimator with unknown inputs is designed. Simultaneously, a lateral force observer based on adaptive sliding mode observer (ASMO) is developed, fully utilizing the onboard sensor data of the vehicle. A TRFC estimator with square root cubature Kalman filter, incorporating square root filtering, is proposed to reduce algorithm complexity while ensuring accuracy. Finally, an interacting multiple-model mechanism is specifically developed for both pure longitudinal dynamics and combined conditions. Through Carsim-Matlab co-simulation and high TRFC test conditions of a real vehicle equipped with a 6-axis wheel transducer, it is shown that the algorithm proposed in this article can accurately estimate tire force and TRFC under various maneuvering conditions and different TRFC conditions. Based on the comparison with traditional algorithms, it shows that our proposed algorithm has higher estimation accuracy and robustness.