bluuebunny/crossref_metadata_2025 huggingface dataset:
A study on the ground loss and foundation coupling loss for railway vibration prediction in greater Perth area of Western Australia
Authors: Liu Ying , Zoontjens Luke
Published: November 2023

Railway noise and vibration have emerged as significant concerns affecting the well-being of residents living in proximity to railway tracks and the structural integrity of nearby infrastructure. As such, accurate and reliable predictions of railway vibration levels are necessary in order to properly assess the risks and develop effective mitigations. The propagation of railway vibration from the source to the receiving point involves a complex process, wherein ground loss and foundation coupling loss play crucial roles. Therefore, comprehensive capture of these factors is necessary for improving the accuracy of railway vibration prediction. This paper presents a study focused on the measurements of ground damping loss and foundation coupling loss in great Perth area of Western Australia. The measurements have been undertaken in generally sandy soil conditions. The foundation coupling loss was primarily measured at single-storey residential dwellings. The collected field data were subsequently analyzed to identify the characteristics of ground loss and foundation coupling loss. The study revealed that ground loss and foundation coupling loss exhibited variability dependent on the specific location, ground conditions, and structural characteristics of the dwellings. These measured results can serve as input for modeling efforts, thereby enabling more accurate prediction of railway vibration levels. Furthermore, the study provides valuable insights into the characterization of vibration propagation in sandy soils.
Robust sonic boom reduction in primary boom carpet
Authors: Ueno Atsushi , Ishikawa Hiroaki , Koganezawa Shinya , Makino Yoshikazu
Published: November 2023

Japan Aerospace Exploration Agency has conducted a low-boom design for a small-sized (about 50 PAX) supersonic airliner. In this study, sonic boom loudness is evaluated in a primary boom carpet, while the focus boom is not considered. Two geometries having different robustness with respect to loudness distribution in a primary boom carpet are designed. One is designed considering only a cruise Mach number, and sonic boom loudness is reduced at both under-track and off-track positions. The other is designed considering bothcruise and off-design Mach numbers, and the maximum sonic boom loudness in a primary boom carpet is minimized. In the presentation, design examples to achieve low-boom characteristics at both under-track and off-track positions are reported. In addition, a low-boom design concept using canard is proposed to minimize the maximum sonic boom loudness in a primary boom carpet. Finally, differences of loudness distribution in a primary boom carpet between two geometries are discussed.
An improved computational bioacoustic monitoring approach for detecting sparse features
Authors: McEwen Ben J. , Soltero Kaspar , Cone Isaac , Gutschmidt Stefanie , Bainbridge-Smith Andrew , Atlas James , Green Richard
Published: November 2023

The collection and annotation of bioacoustic data presents a number of challenges to researchers, often constraining analysis to highly vocal species. Computational tools allow monitoring to be extended to less vocal and more challenging species but data limitations remain an issue. We present a human-in-the-loop approach that combines the efficiency of computational tools with the accuracy of human analysis. We use a wavelet-based segmentation method that automatically extracts transient features within field recordings which can reduce data by up to 90% and requires as few as one reference feature. Segmented features are then used to fine-tune a transformer-based model, audio spectrogram transformer (AST), the output of which is verified by a human and the adjusted data fed back into the model to improve performance over time. We also present an outlier detection approach based on Mel-frequency Cepstral Coefficients. Coefficients are projected to 2-D and outliers are detected using silhouette score. This approach was able to achieve 98.8% validation accuracy on a binary classification task using a limited dataset of 200 5-min recordings with sparse features (occurrence rates of less than 1%). This approach makes real-time bioacoustic monitoring of less-vocal species a possibility.
A novel bearing-time record estimation method based on α-stabledistribution modeling
Authors: Yu Ge , Tang Bingbing , Piao Shengchun
Published: November 2023

Bearing-time record (BTR) is widely used in the field of passive sonar information processing for target tracking. Most existing BTR estimation methods of ship radiated noise are generally based on energy-varying under the assumption of Gaussian modeling in the time domain. However, some weak trajectories may exist in BTR for the decentralized energy distribution and unstable goodness of fit with Gaussian modeling caused by the spatiotemporal instability of the marine environment. In this paper, a novel ship trajectory enhancement method which is based on α-stable distribution modeling theory is presented. In order to make the statistical characteristic of ship radiated noise better reflected, the proposed method utilizes the α-stable distribution modeling in the real part of ship radiated noise Discrete Fourier Transform (DFT) coefficient instead of the Gaussian modeling in the time domain. The scale parameter γ of α-stable distribution is substituted for variance and enhanced BTR is achieved. According to the experimental results, the real part of the DFT coefficient of ship radiated noise could be fitted by α-stable distribution at the significant level of 0.05. Compared with traditional BTR estimation method, the proposed method could gain 3.1dB enhancement on peak signal-to-noise ratio (PSNR).
Comparative theoretical and experimental analysis of vibration damping performance in multilayer constrained layer damping structures: Aluminium versus glass fiber reinforced polymer
Authors: Sharma Gaurav , Kumaraswamy Adepu , Rath Sangram Kesari
Published: November 2023

This study investigates the dynamic behavior of multilayer Constrained Layer Damping (CLD) structures, specifically focusing on constraining layers made of aluminum and Glass Fiber Reinforced Polymer (GRP). Numerical simulations are compared with experimental results using the finite element method (FEM) and the widely used Ross–Kerwin–Ungar (RKU) model to achieve this. Experimental modal analysis is conducted on a vibration shaker to validate the FEA findings. The research reveals valuable insights into the damping performance of aluminum and GRP as constraining layers. Notably, aluminum demonstrates superior damping properties, particularly in the higher frequency range (ultimate loss factor 0.2), while GRP exhibits better-damping characteristics in the lower frequency range (ultimate loss factor 0.13). These results underscore the significance of considering the frequency-dependent behavior of materials when selecting appropriate constraining layers. By shedding light on the dynamic behavior and damping performance of multilayer CLD structures with different constraining layers, this study contributes to the effective mitigation of vibrations in various engineering applications. This endeavor will enhance the understanding and application of constraining layer materials for effective structural vibration control, paving the way for improved engineering solutions.
Optimal design of fibrous materials for sound absorption
Authors: Yang Tao , Maeder Marcus , Marburg Steffen
Published: November 2023

Fibrous materials, which are typical porous materials, play a crucial role in noise control and improving sound quality in the building and automotive industries. Researchers have extensively investigated the acoustic properties of fibrous materials, including both natural and synthetic fibers. Additionally, various numerical and semi-phenomenological models have been employed to accurately predict their acoustic properties. Despite the existence of accurate models, most research on the acoustic properties of fibrous materials has been experiment-oriented. Furthermore, very few studies have focused on reliable and straightforward approaches to optimize these properties and guide the preparation process of fibrous materials. This work aims to develop a robust optimization approach for single-layer and multi-layer fibrous materials by combining numerical optimization methods with numerical and semi-phenomenological acoustic models. The ultimate goal of this optimization approach is to provide designed parameters for fabricating fibrous materials with excellent sound absorption properties. To validate and refine the optimization approach, the fabricated fibrous materials will be thoroughly measured.
Interkingdom and intrakingdom interactions in the microbiome of
Heterobasidion
fruiting body and associated decayed woody tissues
Authors: Ren Wenzi , Penttilä Reijo , Kasanen Risto , Asiegbu Fred O.
Published: November 2023

The
Heterobasidion annosum
species complex is a major threat to the forest industry in the northern temperate regions of the world. The fungal and bacterial biota communities in
Heterobasidion
-infected trees have been extensively studied, but less is known about the interkingdom and intrakingdom interactions among the microbiome. The bacteria-fungi interkingdom analysis has revealed significant findings compared to the intrakingdom analysis in recent studies. In this study, we aimed to (i) unravel the contribution and development of the bacteria and other fungi in the
Heterobasidion
-infected wood decay process; (ii) uncover how environmental factors and the conifer pathogen drive the microbiome community structure and function changes; and (iii) identify the core microbiome during the
Heterobasidion
-mediated wood decay process. Internal transcribed spacer and 16S amplicon sequencing data from the
Heterobasidion
fruiting body and its associated woody tissue were applied in this analysis. Samples collected from managed forest and nature reserve forest were classified into four decay classes based on the extent of decay of the wood. Our result showed that bacteria and fungi have different abundances and activities in both study materials. The
Heterobasidion
ecological correlation network is conserved, especially in the fruiting body. The core microbiome defined in our analysis showed huge potential for the microbiome community’s functioning. A particular
Heterobasidion
Operational Taxonomic Units (OTU) had the most important impact on the community and disease development. Forest management has the biggest impact on the microbiome assembly, and the fungal community is more sensitive to environmental changes.

IMPORTANCE

We applied macro- (forest stand and forest management) and micro-scale (bacterial and fungal community) analyses for a better understanding of the
Heterobasidion
pathosystem and associated wood decay process. The core microbiome, as defined by hierarchy analysis and a consistent model, and environmental factors correlation with the community assembly were found to be novel.
Draft genome sequence of
Enterococcus
sp. SB12 isolated from artisanal cheese of the Carpathian
Authors: Mushynska Viktoriia , Roman Ivan , Tistechok Stepan , Slyvka Iryna , Tsisaryk Orysia , Gromyko Oleksandr , Shtapenko Oksana , Syrvatka Vasyl
Published: November 2023

In this study, we present the draft genome sequence of the
Enterococcus
sp. strain SB12, which was isolated from artisanal cheese of the Carpathian region (Ukraine). The
de novo
assembly produced 64 contigs, with a total length of 2,514,601 bp. Phylogenetic analysis revealed its proximity to the
Enterococcus faecium
strains.
Pharmacokinetics and safety evaluation of intravenously administered
Pseudomonas
phage PA_LZ7 in a mouse model
Authors: Wang Si-yun , Tan Xin , Liu Zi-qiang , Ma Hui , Liu Tian-bin , Yang Yong-qing , Ying Yong , Gao Ru-yue , Zhang Dai-zhou , Ma Ying-fei , Chen Kai , Lin Lin , Jiang Zhi-huan , Yu Jia-lin
Published: November 2023

Phage therapy has become one of the most promising alternatives to antibiotics as the surge of multi-drug-resistant (MDR) bacteria severely threatens global public health. The lack of a thorough understanding of pharmacokinetics (PK) and the safety study of phage has limited its clinical application. In this study, we aimed to evaluate the PK and safety of a lytic phage PA_LZ7 that infects MDR
Pseudomonas aeruginosa
using intravenous (IV) route in an uninfected immune-competent mice model. The active phage of PA_LZ7 exhibited an exponential decay in plasma at 2*10
8
(low dosage), 2*10
10
[medium dosage (MD)], and 2*10
11
PFU/kg [high dosage (HD)] after IV administration, and the phage titer dropped to ~4 log
10
PFU/mL over 24 h for all dosages. Phages primarily accumulated in the spleen at 1 h post-administration and gradually decreased in all dosages. The active phage titer in other organs decreased globally within 72 h as well. Plasma cytokines IL-6, IL-10, KC/GRO, and tumor necrosis factor-alpha sharply increased 1 h post-administration in mice of MD and HD groups and dropped to a normal range within 24 h. No obvious toxic effect was observed, except for the increased spleen weight and relative spleen weight in the MD and HD group and the slight lymphocytosis in the white pulp of the spleen in the HD group. In conclusion, PA_LZ7 possesses good PK properties and shows no obvious toxicity; it could be considered as a potent therapeutic candidate for the treatment of MDR
P. aeruginosa
infections in future phage therapy.

IMPORTANCE

Phage therapy is gaining traction as an alternative to antibiotics due to the rise of multi-drug-resistant (MDR) bacteria. This study assessed the pharmacokinetics and safety of PA_LZ7, a phage targeting MDR
Pseudomonas aeruginosa
, in mice. After intravenous administration, the phage showed an exponential decay in plasma and its concentration dropped significantly within 24 h for all dosage groups. Although there was a temporary increase in certain plasma cytokines and spleen weight at higher dosages, no significant toxicity was observed. Therefore, PA_LZ7 shows potential as an effective and safe candidate for future phage therapy against MDR
P. aeruginosa
infections.
Intrusion tip velocity controls the emplacement mechanism of sheet intrusions
Authors: Köpping Jonas , Cruden Alexander R. , Thiele Samuel T. , Magee Craig , Bunger Andrew
Published: November 2023

Space for intruding magma is created by elastic, viscous, and/or plastic deformation of host rocks. Such deformation impacts the geometries of igneous intrusions, particularly sills and dikes. For example, tapered intrusion tips indicate linear-elastic fracturing during emplacement, whereas fluidization of host rocks has been linked to development of elongate magma fingers with rounded tips. Although host rock fluidization has only been observed at the lateral tips of magma fingers, it is assumed to occur at their leading edges (frontal tips) and thereby control their propagation and geometry. Here, we present macro- and microstructural evidence of fluidized sedimentary host rock at the lateral tips of magma fingers emanating from the Shonkin Sag laccolith (Montana, western United States), and we explore whether fluidization could have occurred at their frontal tips. Specifically, we combine heat diffusion modeling and fracture tip velocity estimates to show that: (1) low intrusion tip velocities (≤10−5 m s−1) allow pore fluids ahead of the intrusion to reach temperatures sufficient to cause fluidization, but (2) when tip velocities are high (~0.01–1 m s−1), which is typical for many sheet intrusions, fluidization ahead of propagating tips is inhibited. Our results suggest that intrusion tip velocity (i.e., strain rate) is a first-order control on how rocks accommodate magma. Spatially and temporally varying velocities of lateral and frontal tips suggest that deformation mechanisms at these sites may be decoupled, meaning magma finger formation may not require host rock fluidization. It is thus critical to consider strain rate and three-dimensional intrusion geometry when inferring dominant magma emplacement mechanisms.
Use of social media in recruiting young people to mental health research: a scoping review
Authors: Smith Megan V A , Grohmann Dominique , Trivedi Daksha
Published: November 2023

Objectives

This review explored the literature on the use of social media in recruiting young people, aged 13–18 years, to mental health research. It aimed to identify barriers and facilitators to recruitment and strategies to improve participation in future research.

Design

Scoping review.

Data sources

Articles published between January 2011 and February 2023 were searched for on PubMed, Scopus, Medline (via EBSCOhost) and Cochrane Library databases.

Eligibility criteria

Studies that outlined social media as a recruitment method and recruited participants aged 13–18 years.

Data extraction and synthesis

Data was extracted by two reviewers independently and cross-checked by a third reviewer. Data on study design, aims, participants, recruitment methods and findings related specifically to social media as a recruitment tool were collected.

Results

24 journal articles met the inclusion criteria. Studies were predominantly surveys (n=13) conducted in the USA (n=16) recruiting via Facebook (n=16) and/or Instagram (n=14). Only nine of the included articles provided a summary of success and reviewed the efficacy of social media recruitment for young people in mental health research. Type of advertisement, the language used, time of day and the use of keywords were all found to be factors that may influence the success of recruitment through social media; however, as these are based on findings from a small number of studies, such potential influences require further investigation.

Conclusion

Social media recruitment can be a successful method for recruiting young people to mental health research. Further research is needed into recruiting socioeconomically marginalised groups using this method, as well as the effectiveness of new social media platforms.

Registration

Open Science Framework Registry (https://osf.io/mak75/).
Improvement of response bandwidth and sensitivity of Rydberg receiver using multi-channel excitations
Authors: Hu Jinlian , Jiao Yuechun , He Yunhui , Zhang Hao , Zhang Linjie , Zhao Jianming , Jia Suotang
Published: November 2023

We investigate the response bandwidth of a superheterodyne Rydberg receiver at a room-temperature vapor cell, and present an architecture of multi-channel lasers excitation to increase the response bandwidth and keep sensitivity, simultaneously. Two microwave fields, denoted as a local oscillator (LO) $E_{\text{LO}}$

E
LO

and a signal field $E_{\text{SIG}}$

E
SIG

, couple two Rydberg states transition of $|52D_{5/2}\rangle \to |53P_{3/2}\rangle $
|
52

D

5
/
2

〉
→
|
53

P

3
/
2

〉
. In the presence of the LO field, the frequency difference between two fields can be read out as an intermediate frequency (IF) signal using Rydberg electromagnetically induced transparency (EIT) spectroscopy. The bandwidth of the Rydberg receiver is obtained by measuring the output power of IF signal versus the frequency difference between two fields. The bandwidth dependence on the Rabi frequency of excitation lasers is presented, which shows the bandwidth decrease with the probe Rabi frequency, while it is quadratic dependence on the coupling Rabi frequency. Meanwhile, we investigate the effect of probe laser waist on the bandwidth, showing that the bandwidth is inversely proportional to the laser waist. We achieve a maximum response bandwidth of the receiver about 6.8 MHz. Finally, we design an architecture of multi-channel lasers excitation for increasing the response and keeping the sensitivity, simultaneously. Our work has the potential to extend the applications of Rydberg atoms in communications.
sEMG-Based Inter-Session Hand Gesture Recognition via Domain Adaptation with Locality Preserving and Maximum Margin
Authors: Guo Yao , Liu Jiayan , Wu Yonglin , Jiang Xinyu , Wang Yalin , Meng Long , Liu Xiangyu , Shu Feng , Dai Chenyun , Chen Wei
Published: November 2023

Surface electromyography (sEMG)-based gesture recognition can achieve high intra-session performance. However, the inter-session performance of gesture recognition decreases sharply due to the shift in data distribution. Therefore, developing a robust model to minimize the data distribution difference is crucial to improving the user experience. In this work, based on the inter-session gesture recognition task, we propose a novel algorithm called locality preserving and maximum margin criterion (LPMM). The LPMM algorithm integrates three main modules, including domain alignment, pseudo-label selection, and iteration result selection. Domain alignment is designed to preserve the neighborhood structure of the feature and minimize the overlap of different classes. The pseudo-label selection and iteration result selection can avoid the decrease in accuracy caused by mislabeled samples. The proposed algorithm was evaluated on two of the most widely used EMG databases. It achieves a mean accuracy of 98.46% and 71.64%, respectively, which is superior to state-of-the-art domain adaptation methods.
Multi-strategy ensemble Harris hawks optimization for smooth path planning of mobile robots
Authors: Zong Xinlu , Liu Yin , Ye Zhiwei , Xia Xue
Published: November 2023

Efficient and safe path planning for autonomous navigation is paramount in advancing the motion control capabilities of mobile robots. To obtain the global optimal smooth path for mobile robots, a multi-strategy ensemble Harris hawks optimization algorithm (SDHHO) is proposed in this paper. The spiral search strategy is adopted to improve the early update method of the algorithm, which can improve the global exploration ability. To achieve better balance between global exploration and local exploitation, the Sine chaotic map is introduced to the escape energy, replacing random components. Furthermore, an elite differential mutation strategy combined with Gaussian mutation is designed to prevent the algorithm from falling into local optima. We compared the SDHHO algorithm with other classical and novel algorithms on 23 benchmark functions, and the results demonstrated the superiority of SDHHO. The proposed algorithm is applied to the smooth path planning for mobile robots, which is transformed into an optimization problem of control nodes of high-order Bezier curves. Empirical evaluations across diverse environments underscore the proficiency of the proposed method in generating paths characterized by reduced length and enhanced safety and continuity.
Optimality Conditions in Uncertain Multi-Objective Optimization Problems with a Variable Domination Structure
Authors: Fan Cong , Wang Qilin
Published: November 2023

In this paper, we first establish some new properties of a kind of nonlinear scalarization function. Second, based on set approaches, we introduce a class of new definitions of robustness for an uncertain multi-objective optimization problem with a variable domination structure. Finally, by applying the scalarization method, we obtain the necessary and sufficient optimality conditions of the robustness for the uncertain multi-objective optimization problem with a variable domination structure in a more general setting. Some of the obtained results extend and imply the corresponding ones in recent literature.
A low-frequency sound insulation metastructure with relatively high ventilation
Authors: Zhen Ni , Shi Lei , Zhu Ying-Li
Published: November 2023

Noise pollution is growing nowadays and there is always a conflict between ventilation and noise insulation. The advances in acoustic metamaterials provide an effective solution for this conflict. In this paper, we propose a metastructure with protruded necks based on Helmholtz resonance. Sound transmission loss (STL) of 13 dB at low-frequency of 488[Formula: see text]Hz is obtained in experiment with the ventilation of 20%, which is in good agreement with the simulation. It is revealed that introduction of protruded neck can reduce the resonant frequency. Sound absorption is the main mechanism for noise insulation at low frequency. Next, the effects of geometric parameters on sound insulation are discussed. A reduction in cross-sectional area of neck, an increase in neck length, and an increase in ventilation all lead to a decrease in both resonant frequencies and STL amplitudes. Finally, a two-layer structure is constructed by the proposed metastructure with different neck length in each unit. Both the amplitude and frequency range of STL are enlarged. These results exhibit a practical application for ventilated metastructure in sound insulation at low frequency.
Applicability of OCR Engines for Text Recognition in Vehicle Number Plates, Receipts and Handwriting
Authors: Poudel Utsav , Regmi Aayush Man , Stamenkovic Z. , Raja S. P.
Published: November 2023

Optical character recognition (OCR) is a computer vision technique that enables computers to recognize text from images. Text detection and computer vision have made significant advancements, leading to the development of various OCR technologies. However, selecting the most suitable OCR system for a specific purpose has become a challenging task. This research paper aims to explain the theoretical concepts and mathematical formulas underlying OCR engines, providing a better understanding of their functioning and performance. The analysis covers various aspects, including the theories, algorithms, and techniques employed by OCR engines. This paper presents experiments conducted on five different image categories: vehicle number plates, receipts, handwriting, symbols and plain text images. Evaluation metrics such as Character Error Rate (CER), Word Error Rate (WER), Insertion Error Rate (IER), Deletion Error Rate (DER), End-to-end recognition rate (EEER), Word Error Rate (WER), Recall, Precision, and F1-score were utilized. The findings reveal that OCR systems perform well on plain documents, with recall and F1-score values exceeding 0.85 and 0.8, respectively. However, there are still areas for improvement in OCR, which are discussed in detail in this paper. This research provides valuable insights for researchers, developers, and practitioners interested in employing OCR technology for their commercial projects.
A Method of Printmaking Image Generation Based on Convolutional Neural Network
Authors: Zhou Zhifen , Luo Haiying
Published: November 2023

In this paper, a novel image reconstruction method for printmaking is proposed via the combination of nonlinear diffusion filtering and convolution neural network. Nonlinear diffusion filtering based on a partial differential equation abstracts the input image to extract color features and texture features of images by nonlinear structured tensors. The image color features and texture features are combined to obtain a feature vector, and the feature vector is fed into the model as the input data. Then, the pre-trained deep learning model VGG-19 is utilized as the backbone network for further feature representation, and the extracted feature maps of each layer of the VGG19 model can be visualized for image reconstruction. The quality of the reconstructed images of prints is improved with the powerful feature extraction and combination ability of neural networks, which has the advantages of fast reconstruction speed and high quality of reconstructed images. Finally, the simulation experiments can demonstrate that the proposed reconstruction approach can achieve relatively ideal reconstruction performance in scenes of printmaking.
A Deep Neural Network-Based Assistive Decision Method for Financial Risk Prediction in Carbon Trading Market
Authors: Luo Ji , Zhuo Wuyang , Xu Binfei
Published: November 2023

The price of carbon emission rights in the market fluctuates greatly due to various factors from economy, finance, and climate. For an enterprise that needs to conduct carbon trading activities, it is extremely necessary to fully grasp the price of carbon trading in the future period. Thus in this paper, a deep neural network-based assistive decision model for financial risk prediction in carbon trading market is proposed for this purpose. Specifically, the dynamic risk spillover effects of domestic and international carbon trading markets are studied, and a frontier time-varying model is utilized to measure the risk spillover effects. Then, the deep neural network is used for quantitative research and to construct an intelligent decision scheme that outputs financial risk prediction results. Four perspectives, energy price, climate environment, carbon market price, and macroeconomics, are selected as the input to analyze the influence factors of carbon emission rights price. Finally, several linear regression models are adopted as the baseline methods for comparison, and experimental results show that the proposed method can achieve better prediction performance compared with baseline methods.
Hardware Prefetching Tuning Method Based on Program Phase Behavior
Authors: Huang Liangming , Yan Li , Wu Tiebin
Published: November 2023

Modern high-performance processor systems universally employ hardware prefetch engines to address the “memory wall” issue. Nonetheless, prefetchers are typically activated with the default configuration at system startup, and this fixed configuration does not always achieve the intended performance in the face of varied programs and may even degrade performance. As a result, it is crucial to investigate the prefetch configuration tuning method that adapts to different program characteristics in order to take full advantage of hardware prefetching. In this study, a hardware prefetching tuning method based on program phase behavior is proposed to determine the prefetch configuration that maximizes the overall predicted performance of the program through low-overhead online profiling. In the profiling process, the branch instruction vector sampled by the hardware performance counter is used to dynamically classify the program phase behavior, and the performance profiling is performed for each type of phase. Simultaneously, the recurring program phases are no longer profiled to reduce overhead. Following the profiling, the prefetch configuration with the best predicted performance is derived by combining the performance data from each phase and its running time proportion. The results of the tests on prefetch-sensitive programs in SPEC2006, NPB, and PARSEC demonstrate that the prefetch configuration obtained using the suggested method has a geometric average performance improvement of 7.34% over the default configuration and achieves 99.34% of the optimal configuration. Furthermore, the profiling run adds only 2.24% extra overhead as compared to the default configuration.
A Deep Learning-Based Knowledge Graph Framework for Intelligent Management Scheduling Decision of Enterprises
Authors: Ma Shiyong , Fan Song Qing
Published: November 2023

Due to the huge magnitude expansion of data volume, the application of cloud computing and the Internet of Things is growing year by year. However, more and more industrial production requires real-time and efficient handling of resource scheduling. Therefore, this paper develops a deep learning-based knowledge graph framework for resource scheduling decision of enterprise. Single-objective and multi-objective problems for computing resources are studied, and the network nodes of computing resources are set with the help of network topology theory. For the single-objective problem, the mathematical model is constructed with the optimization objective of minimizing the time delay. For the multi-objective problem, the mathematical model is constructed with the optimization objectives of minimizing both time delay and energy consumption. Combining the historical scheduling scheme with the introduction of a genetic algorithm, an initial optimization method is proposed for the scheduling problem of mixed flow shop, and the optimization problem is solved to minimize the maximum completion time. The simulation experiments are conducted to evaluate the proposed method, and the obtained results show that the proposal can well realize intelligent management scheduling decision for enterprises.
PAC-UNet: Parallel Dual Self-Attention with Convolution for Meniscal MRI Image Segmentation
Authors: Zhang Weijian , Feng Meiling , Xia Chengyi
Published: November 2023

Meniscal tears are common sports-injury disorders, and thus accurate segmentation of the meniscus is a worthwhile means of medical diagnosis. However, due to the limited research on image segmentation of the meniscus, most previous works have poor segmentation effects on the meniscus, which affects the adoption of assisted medical diagnosis of meniscus. To address this issue, we propose an improved neural network model, termed as the PAC-UNet model, which introduces a parallel dual self-attention with depth-wise convolution for the meniscus image segmentation. Firstly, in the encoder stage, the parallel block is used to eliminate the negative impact of weak modeling ability caused by weight sharing on shared dimensions, so as to better learn the semantic information. Then, in the decoder stage, the parallel block and patch expansion are used to restore the predicted results of meniscus segmentation by performing self-attention and up-sampling on the features. By analyzing the outcomes of experiments on the meniscus dataset, which were collected from the hospital, it is found that the proposed network performed better than other medical image segmentation networks, where the average Dice Similarity Coefficient (DSC), Intersection Over Union (IOU), precision, and Hausdorff_95 of the medial meniscus and lateral meniscus are up to 89.01%, 80.81%, 90.5%, and 2.43, respectively.
IMPACT OF HUNTING COOPERATION AND FEAR EFFECT IN A GENERALIST PREDATOR–PREY MODEL
Authors: UMRAO ANUJ KUMAR , SRIVASTAVA PRASHANT K.
Published: November 2023

Predator foraging facilitation or hunting cooperation and the antipredator behavior of prey are essential mechanisms in evolutionary biology and ecology and may strongly influence the predator–prey dynamics. In a real-world scenario, this behavioral tendency is well documented, but less is known about how it could affect the dynamics between predator and prey. Here, we investigate the impact of the fear of predator on prey and the hunting cooperation in predator on the predator–prey dynamics, where the predator is assumed to be of generalist type. We observe that without fear, even with the high level of hunting cooperation, both populations may coexist, though the increasing level of hunting cooperation reduces the prey density at coexistence equilibrium. Moreover, increasing level of fear also destabilizes the system with and without hunting cooperation. Further, in the presence of hunting cooperation and fear effect, the model shows three different types of bistability phenomena: bistability between two coexisting equilibria, bistability between coexisting equilibria and prey-free equilibrium, and bistability between stable limit cycle and coexisting equilibria. In addition, saddle-node, Hopf, transcritical bifurcation of codimension one, Bautin (generalized Hopf), Bogdanov–Takens, and cusp bifurcation of codimension two are observed.
EFFECT OF DEPOSITION PARAMETER ON EXTERIOR MORPHOLOGY, STRUCTURAL AND OPTICAL CHARACTERISTICS OF CHEMICAL BATH-DEPOSITED ZINC OXIDE THIN FILMS
Authors: NASRIN RAHIMA , OBAYDUL HAQ M. D. , MOHIUDDIN M. D. , AKTHER H.
Published: November 2023

In this research, Zinc Oxide thin films (ZOTF) have been placed onto a glass substrate at different times of deposition via chemical bath deposition (CBD) technique. The influence of deposition time (DT) on the exterior morphology, elemental, structural and optical behaviors of the prepared thin films has been studied through various characterization techniques for example field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX) spectroscopy, X-ray diffraction (XRD) analysis and UV-Vis spectroscopic analysis, respectively. According to FESEM images, the thin film surface existing on a dense and flower-like surface morphology was changed to flake-like structure due to increase of DT. EDX analysis exhibited the mass % and atomic % of Zn which is extant in greater proportion but O is lesser in the prepared ZOTF. The XRD pattern exposed the hexagonal wurtzite structure of ZOTF. The UV-V is results exhibited a decrease in transmittance and the optical band gap was significantly influenced by the alteration of DT. The observed high transparency of these thin films in the visible region makes them appropriate for utilization as transparent windows in numerous optical device applications.
Optimal prediction for kernel-based semi-functional linear regression
Authors: Guo Keli , Fan Jun , Zhu Lixing
Published: November 2023

This paper proposes a novel prediction approach for a semi-functional linear model comprising a functional and a nonparametric component. The study establishes the minimax optimal rates of convergence for this model, revealing that the functional component can be learned with the same minimax rate as if the nonparametric component were known and vice versa. This result can be achieved by using a double-penalized least squares method to estimate both the functional and nonparametric components within the framework of reproducing kernel Hilbert spaces. Thanks to the representer theorem, the approach also offers other desirable features, including the algorithm efficiency requiring no iterations. We also provide numerical studies to demonstrate the effectiveness of the method and validate the theoretical analysis.
Clifford algebra Cl(0,6) approach to beyond the standard model and naturalness problems
Authors: Lu Wei
Published: November 2023

Is there more to Dirac’s gamma matrices than meets the eye? It turns out that gamma zero can be factorized into a product of three operators. This revelation facilitates the expansion of Dirac’s space-time algebra to Clifford algebra [Formula: see text]. The resultant rich geometric structure can be leveraged to establish a combined framework of the standard model and gravity, wherein a gravi-weak interaction between the vierbein field and the extended weak gauge field is allowed. Inspired by the composite Higgs model, we examine the vierbein field as an effective description of the fermion–antifermion condensation. The compositeness of space-time manifests itself at an energy scale which is different from the Planck scale. We propose that all the regular classical Lagrangian terms are of quantum condensation origin, thus possibly addressing the cosmological constant problem provided that we exercise extreme caution in the renormalization procedure that entails multiplications of divergent integrals. The Clifford algebra approach also permits a weaker form of charge conjugation without particle–antiparticle interchange, which leads to a Majorana-type mass that conserves lepton number. Additionally, in the context of spontaneous breaking of two global [Formula: see text] symmetries, we explore a three-Higgs-doublet model which could explain the fermion mass hierarchies.
Non-relativistic quantum dynamics in Born–Infeld gravity inspired by Eddington spacetime global monopole
Authors: Pereira C. F. S. , Vitória R. L. L. , Soares A. R. , Bezerra V. B. , Belich H.
Published: November 2023

In this work, we investigate the quantum dynamics of non-relativistic systems in a Born–Infeld spacetime. We analyze some general scenarios, which concerns the effects of a harmonic oscillator and an inverse square-type potential as well as an Aharonov–Bohm geometric phase. We obtain an analytical solution for the most general case in terms of a confluent Heun function and define the energy spectrum by referring to the ground state, together with its respective eigenfunction. A graphical representation was built so that it was possible to visualize some of the possible energy configurations. For negative values of the Born–Infeld parameter [Formula: see text], we perform a connection with results of quantum dynamics already investigated in the literature for the Ellis–Bronnikov spacetime.
Geometry of almost contact metrics as almost ∗-Ricci solitons
Authors: Patra Dhriti Sundar , Mofarreh Fatemah , Ali Akram
Published: November 2023

In this paper, we give some characterizations by considering ∗-Ricci soliton as a Kenmotsu metric. We prove that if a Kenmotsu manifold represents an almost ∗-Ricci soliton and the potential vector field [Formula: see text] is a Jacobi along the Reeb vector field, then it is a steady ∗-Ricci soliton. Next, we show that a Kenmotsu matric endowed an almost ∗-Ricci soliton which is Einstein metric if it is [Formula: see text]-Einstein or the potential vector field [Formula: see text] is collinear to the Reeb vector field or [Formula: see text] is an infinitesimal contact transformation.
Nuclear matter equation of state and stability of charged compact stars embedded in f(T) modified gravity, under cosmic acceleration
Authors: Bandyopadhyay Mayukh , Biswas Ritabrata
Published: November 2023

This work mainly focuses on modeling the charged compact stars and investigating their properties in the framework of [Formula: see text] modified gravity, under the accelerated phase of the universe. In this study, we have introduced the modified gravity and dark matter to culture the evolution of the charged neutron stars by considering the present situation. True knowledge and proper study on the macroscopic parameters of the compact stars are very much needed to realize the microscopic properties and behavior of the core nuclear matter at very high density and pressure. The existence of modified Chaplygin gas as an exotic fluid inside the core of these stars in [Formula: see text] gravity plays a very important role inside the stars. We have found out that exotic fluid has a great impact on the equation of state of the core nuclear matter and even on the stability of the compact stars. Pressure anisotropy reduces the tidal deformability of the charged stars in an appreciable amount and helps to get a more compact structure. But surprisingly, the compact stars are still able to maintain their spherically stable and equilibrium configuration. Further, we can put constraints on several macroscopic parameters of the compact stars and can investigate their evolution from our present investigation.
Investigation of charged stellar structures in f(R,ϕ) gravity using Reissner–Nordstrom geometry
Authors: Malik Adnan , Bashir M. Rizwan , Ahmad Mushtaq , Jabeen Asma , Shamir M. Farasat
Published: November 2023

The purpose of this study is to investigate the behavior of charged stellar structures in the [Formula: see text] theory of gravity, where [Formula: see text] denotes the Ricci scalar and [Formula: see text] represents the scalar potential, respectively. For our current analysis, we consider Krori–Barua metrics to discuss the spherically symmetric solutions in [Formula: see text] gravity. We further develop some matching conditions between the spherically symmetric spacetime as interior geometry with Reissner–Nordstrom as exterior geometry. Moreover, we consider the observational data of three distinct stars namely Vela [Formula: see text], SAX [Formula: see text] and [Formula: see text] for present work. We investigate the behavior of energy density, radial pressure, tangential pressure, anisotropic parameter, equation of state parameters, equilibrium condition, sound speeds, Abreu’s criteria, adiabatic index and energy conditions respectively. Moreover, we investigate some other properties of the stellar structures including mass-radius relation, compactness factor, and surface redshift. Our investigation reveals that the observed anisotropic findings are physically appropriate and have the highest level of precision in the background of [Formula: see text] modified theory of gravity.
The First Cohomology of o s p ( 1,2 ) with Coefficients in Baby Verma Modules and Simple Modules
Authors: Wang Shujuan , Liu Wende
Published: November 2023

Over a field of characteristic [Formula: see text], the first cohomology of the orthogonal symplectic Lie superalgebra [Formula: see text] with coefficients in baby Verma modules and simple modules is determined by use of the weight space decompositions of these modules relative to a Cartan subalgebra of [Formula: see text]. As a byproduct, the first cohomology of [Formula: see text] with coefficients in the restricted enveloping algebra (under the adjoint action) is not trivial.
Nonlocal Lagrange multipliers and transport densities
Authors: Azevedo Assis , Rodrigues José Francisco , Santos Lisa
Published: November 2023

We prove the existence of generalized solutions of the Monge–Kantorovich equations with fractional [Formula: see text]-gradient constraint, [Formula: see text], associated to a general, possibly degenerate, linear fractional operator of the type, [Formula: see text] with integrable data, in the space [Formula: see text], which is the completion of the set of smooth functions with compact support in a bounded domain [Formula: see text] for the [Formula: see text]-norm of the distributional Riesz fractional gradient [Formula: see text] in [Formula: see text] (when [Formula: see text], [Formula: see text] is the classical gradient). The transport densities arise as generalized Lagrange multipliers in the dual space of [Formula: see text] and are associated to the variational inequalities of the corresponding transport potentials under the constraint [Formula: see text]. Their existence is shown by approximating the variational inequality through a penalization of the constraint and nonlinear regularization of the linear operator [Formula: see text]. For this purpose, we also develop some relevant properties of the spaces [Formula: see text], including the limit case [Formula: see text] and the continuous embeddings [Formula: see text], for [Formula: see text]. We also show the localization of the nonlocal problems ([Formula: see text]), to the local limit problem with classical gradient constraint when [Formula: see text], for which most results are also new for a general, possibly degenerate, partial differential operator [Formula: see text] with coefficients only integrable and bounded gradient constraint.
A Novel Battery Management and Recovery Control Algorithm for Mitigating the Memory Effect in Nickel Hydrogen Batteries for Space Missions
Authors: Mohamed Ahmed Mokhtar , Amer Fawzy ElTohamy H. , Elhalwagy Yehia Z. , Hanafy Mohamed E.
Published: November 2023

The spacecraft’s (SC) electric power system (EPS) is one of the vital systems. It could limit the SC capabilities or reduce the SC lifetime. The EPS should provide the required energy for the SC loads to perform their tasks successfully until End-of-Life (EOL). Furthermore, the EPS should guarantee the power needed to execute the customer requirements under all degradations (battery degradation, radiation, etc.) and other external factors (orbital degradation). The SC’s primary power generation sources are solar arrays and storage batteries. This paper investigates a SC with a Nickel Hydrogen Storage Battery (NHSB) consisting of 17 cells: 4 measured cells and 13 unmeasured cells. In this paper, two distinct objectives have been achieved: The first objective is formulating a control algorithm for battery testing and reconditioning (CABTR). This algorithm is applied to an NHSB in an orbital setting mode, rectifying the memory effect in the NHSB and restoring the battery’s total capacity. The second objective constructs an environment that effectively simulates the dynamic behavior of the battery during in-orbit operations. This simulated environment calculates crucial parameters such as the state of charging (SOC), battery temperature, voltage, and pressure of the NHSB during reconditioning. This computational analysis assures the robustness of the CABTR, and confirms the optimal battery performance. Subsequent validation encompasses ground tests and real-time telemetry data, which affirms the battery’s dynamic behavior and the developed algorithms’ efficacy.