bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fully-integrated photonic tensor core for image convolutions
Authors: Marquez Bicky A , Singh Jagmeet , Morison Hugh , Guo Zhimu , Chrostowski Lukas , Shekhar Sudip , Prucnal Paul , Shastri Bhavin J 
Published: June 2023

Abstract
Convolutions are one of the most critical signal and image processing operations. From spectral analysis to computer vision, convolutional filtering is often related to spatial information processing involving neighbourhood operations. As convolution operations are based around the product of two functions, vectors or matrices, dot products play a key role in the performance of such operations; for example, advanced image processing techniques require fast, dense matrix multiplications that typically take more than 90% of the computational capacity dedicated to solving convolutional neural networks. Silicon photonics has been demonstrated to be an ideal candidate to accelerate information processing involving parallel matrix multiplications. In this work, we experimentally demonstrate a multiwavelength approach with fully integrated modulators, tunable filters as microring resonator weight banks, and a balanced detector to perform matrix multiplications for image convolution operations. We develop a scattering matrix model that matches the experiment to simulate large-scale versions of these photonic systems with which we predict performance and physical constraints, including inter-channel cross-talk and bit resolution.
Boundedness in a logistic chemotaxis system with weakly singular sensitivity in dimension two
Authors: Zhao Xiangdong 
Published: June 2023

Abstract
This paper deals with the parabolic-elliptic Keller–Segel system with weakly singular sensitivity and logistic source under the homogeneous Neumann boundary:

u
t

=
Δ
u
−
χ
∇
⋅
(

u

v
α

∇
v
)
+
r
u
−
μ

u
2

,

0
=
Δ
v
−
v
+
u

in a smooth bounded domain

Ω
⊂

R

2

, with

χ
,
α
,
μ
>
0

,

r
∈

R

. It is proved that the system possesses a globally bounded classical solution for

α
∈
(
0
,
1
)

with µ > 0 suitably large, without establishing the uniformly positive bound for v from below. In addition, we give the explicit expression of the upper bound for solution u with respect to the parameters

χ
,
α
,
r
,
μ

via a recursive argument on α. This concludes that weakly singular sensitivity benefits to obtain the global boundedness of classical solution in dimension two.
HyperTDP-Net: A Hyper-densely Connected Compression-and-Decomposition Network Based on Trident Dilated Perception for PET and MRI Image Fusion
Authors: Li Bicao , Du Yifan , Wang Bei , Shao Zhuhong , Huang Jie , Wei Miaomiao , Lu Jiaxi 
Published: June 2023

Abstract

Objective. Since medical images generated by medical devices have low spatial resolution and quality, fusion approaches on medical images can generate a fused image containing a more comprehensive range of different modal features to help physicians accurately diagnose diseases. Conventional methods based on deep learning for medical image fusion usually extract only local features without considering their global features, which often leads to the problem of unclear detail information in the final fused image. Therefore, medical image fusion is a challenging task of great relevance. Approach. This paper proposes a novel end-to-end medical image fusion model for PET and MRI images to achieve information interaction between different pathways, termed as hyper-densely connected compression-and-decomposition network based on trident dilated perception for PET and MRI image fusion (HyperTDP-Net). In particular, in the compression network, a dual residual hyper densely module is constructed to take full advantage of middle layer information. Moreover, we establish the trident dilated perception module to precisely determine the location information of features, and improve the feature representation capability of the network. In addition, we abandon the ordinary mean square error as the content loss function and propose a new content-aware loss consisting of structural similarity loss and gradient loss, so that the fused image not only contains rich texture details but also maintains sufficient structural similarity with the source images.Main results. The experimental dataset used in this paper is derived from multimodal medical images published by Harvard Medical School. Extensive experiments illustrate that our model contains more edge information and texture detail information in the fusion result than the 12 state-of-the-art fusion models and ablation study results demonstrate the effectiveness of three technical innovations.Significance. As medical images continue to be used in clinical diagnosis, our method is expected to be a tool that can effectively improve the accuracy of physician diagnosis and automatic machine detection.
Virtual 4DCT generated from 4DMRI in gated particle therapy: phantom validation and application to lung cancer patients
Authors: Annunziata S , Rabe M , Vai A , Molinelli S , Nakas A , Meschini G , Pella A , Vitolo V , Barcellini A , Imparato S , Ciocca M , Orlandi E , Landry G , Kamp F , Kurz C , Baroni G , Riboldi M , Paganelli C 
Published: June 2023

Abstract

Objective. Respiration negatively affects the outcome of a radiation therapy treatment, with potentially severe effects especially in particle therapy (PT). If compensation strategies are not applied, accuracy cannot be achieved. To support the clinical practice based on 4D computed tomography (CT), 4D magnetic resonance imaging (MRI) acquisitions can be exploited. The purpose of this study was to validate a method for virtual 4DCT generation from 4DMRI data for lung cancers on a porcine lung phantom, and to apply it to lung cancer patients in PT. Approach. Deformable image registration was used to register each respiratory phase of the 4DMRI to a reference phase. Then, a static 3DCT was registered to this reference MR image set, and the virtual 4DCT was generated by warping the registered CT according to previously obtained deformation fields. The method was validated on a physical phantom for which a ground truth 4DCT was available and tested on lung tumor patients, treated with gated PT at end-exhale, by comparing the virtual 4DCT with a re-evaluation 4DCT. The geometric and dosimetric evaluation was performed for both proton and carbon ion treatment plans. Main results. The phantom validation exhibited a geometrical accuracy within the maximum resolution of the MRI and mean dose deviations, with respect to the prescription dose, up to 3.2% for target D
95%, with a mean gamma pass rate of 98%. For patients, the virtual and re-evaluation 4DCTs showed good correspondence, with errors on target D
95% up to 2% within the gating window. For one patient, dose variations up to 10% at end-exhale were observed due to relevant inter-fraction anatomo-pathological changes that occurred between the planning and re-evaluation CTs. Significance. Results obtained on phantom data showed that the virtual 4DCT method was accurate, allowing its application on patient data for testing within a clinical scenario.
Theory of Josephson current on a lattice model of grain boundary in d-wave superconductors
Authors: Sakamori Takashi , Kashiwaya Satoshi , Yano Rikizo , Tanaka Yukio , Hatano Takafumi , Yada Keiji 
Published: June 2023

Abstract
Identifying the origins of suppression of the critical current at grain boundaries of high-critical-temperature superconductors, such as cuprates and iron-based superconductors, is a crucial issue to be solved for future applications with polycrystalline materials. Although the dominant factor of current suppression might arise during material fabrication and/or processing, investigating it due to an internal phase change of the pair potential is an important issue in understanding the threshold of the critical current. In this paper, we study the Josephson current on a symmetric [001]-tilt grain boundary (GB) of a d-wave superconductor on a lattice model. In addition to the suppression of the maximum Josephson current associated with the internal phase change of the d-wave pair potential which has been predicted in continuum models, we find a unique phase interference effect due to folding of the Fermi surface in the lattice model. In particular, the resultant maximum Josephson current at low-tilting-angle regions tends to be suppressed more than that in preexisting theories. Because similar suppressions of the critical current at GBs have been reported in several experimental works, the present model can serve as a guide to clarify the complicated transport mechanism in GBs.
Memristive chaotic system-based hybrid image encryption application with AES and RSA algorithms
Authors: Sahin M Emin 
Published: June 2023

Abstract
The widespread use of information and communication tools today facilitates information access and highlights the significance of information and data security. In recent years, chaos-based encryption systems have emerged as a promising approach for protecting the confidentiality of transmitted images. In particular, memristor-based hyperchaotic systems have attracted significant attention because of their robustness and complexity. In this paper, we propose an image encryption model that employs a two-stage encryption method using various chaotic systems, including the logistic map, Lorenz chaotic system, and memristor-based hyperchaotic system, with AES and RSA encryption algorithms. The proposed hybrid scheme applies bit-based pixel diffusion and confusion techniques to improve the security of encrypted images. Statistical and security tests are conducted to compare the performance of the different encryption systems and algorithms and to present the measurement values obtained from the analysis. Our experimental results demonstrate the effectiveness of the proposed image encryption scheme in terms of security, speed, and reliability and provide valuable insights for the development of future chaos-based encryption systems.
Solitons, breathers and periodic rogue waves for the variable-coefficient seventh-order nonlinear Schrödinger equation
Authors: Jiang Dongzhu , Zhaqilao  
Published: June 2023

Abstract
Through Darboux transformation (DT) method, Several nonlinear wave solutions of seventh-order variable-coefficient nonlinear Schrödinger (vcNLS) equation are obtained, including solitons, breathers and rogue periodic waves. When the coefficients are linear, parabolic and periodic functions, the parabolic, cubic and quasi-periodic solitons and breathers can be constructed. Then we investigate their effects on the solutions, the variation of the coefficients affects the shape of the solutions. On this basis, the interactions between two solitons are studied and the interactions between two types of breathers are constructed. Next, through the approaches of the nonlinearization of spectral problem and DT method, rogue waves on the background of the Jacobi elliptic functions dn and cn for a seventh-order vcNLS equation are constructed. When the coefficients are selected as linear, exponential and periodic functions, the nonlinear dynamics of two kinds of rogue periodic waves are analysed.
Asymmetric dark matter abundance including non-thermal production
Authors: Qingshan Ma , Iminniyaz Hoernisa 
Published: June 2023

Abstract
We investigate the relic abundance of asymmetric dark matter where the asymmetric dark matter is non–thermally produced from the decay of heavier particles in addition to the usual thermal production. We discuss the relic density of asymmetric dark matter including the decay of heavy particles in low-temperature scenarios. Here, we still assume that the Universe is radiation-dominated and there is asymmetry before the decay of heavy particles. We obtain an increased abundance of asymmetric dark matter when there is an additional contribution from the decay of heavier particles. Finally, we find the constraints on the asymmetry factor and annihilation cross-section using Planck data.
Small intestine submucosa as a growth factor attractor promotes peripheral nerve regeneration by enhancing syndecan-3/glial cell line-derived neurotrophic factor (GDNF) signalling: in vivo study
*
Authors: Liu Chiung-Hui , Chu Yin-Hung , Chen Yin Hsiu , Chiang Yu Hsin , Chen Yu Hsuan , Ku Chung Yao , Hsu Min-Yen , Lee Yi-Ju , Yang Mao-Yi , Liao Wen-Chieh 
Published: June 2023

Abstract
Peripheral nerve regeneration (PNR) following trauma requires the reconstruction of the extracellular matrix (ECM) and the proper stimulation of growth factors. Decellularised small intestine submucosa (SIS) has been extensively used as an ECM scaffold for tissue repair, but its potential to enhance the effects of exogenous growth factors on PNR is not well understood. In this study, we evaluated the effects of SIS implantation combined with glial cell-derived growth factor (GDNF) treatment on PNR in a rat neurorrhaphy model. We found that both SIS and regenerating nerve tissue expressed syndecan-3 (SDC3), one of major heparan sulphate proteoglycans in nerve tissue, and that SDC3 interacted with GDNF in the regenerating nerve tissue. Importantly, the SIS-GDNF combined treatment enhanced the recovery of neuromuscular function and β3-tubulin-positive axonal outgrowth, indicating an increase in the number of functioning motor axons connecting to the muscle after neurorrhaphy. Our findings suggest that the SIS membrane offers a new microenvironment for neural tissue and promotes neural regeneration based on SDC3-GDNF signalling, providing a potential therapeutic approach for PNR.
Roles of chemistry modification for surface wettability of Polyether-Ether-Ketone (PEEK) by ultraviolet laser ablation
Authors: Xu Peiyun , Zhu Fengjin , Wang Xiaohui , Zhang Junjie , Sun Tao 
Published: June 2023

Abstract
Tailoring the functionality of Polyether-ether-ketone (PEEK) is critical for enhancing its application, which can be accomplished by the modification of surface morphology and chemistry. In the present work, we experimentally demonstrate the correlation of modified chemical composition of textured PEEK surface by 355 nm UV nanosecond pulsed laser ablation with enhanced surface wettability. Specifically, the impact of UV laser processing parameters on microgroove morphology and ablated surface quality of PEEK surface is evaluated, with which high precision grid surface textures with uniform ablation quality are fabricated. The modification of chemical elements and functional groups of textured PEEK surface by the laser ablation is further analyzed by XPS spectra characterization, which demonstrates the substantial change of C=O and O–C=O bonds, as well as freshly generated polar carboxylic acid groups. Experimental results indicate that the surface composition modification greatly increases surface polarity and surface free energy of textured PEEK surface accompanied by enhanced surface wettability.
A novel approach for recycling agricultural wastes in the synthesis of nanomaterials and their composites
Authors: Jeet Kiran , Kaur Ramandeep 
Published: June 2023

Abstract
In this study, main focus has been drawn on the utilization of agricultural waste sources to synthesize nanomaterials. Graphene oxide and nanocellulose were prepared using rice husk ash and sugarcane bagasse, respectively. Further, their nanocomposites were also prepared in (1:1) ratio of graphene oxide and nanocellulose. The synthesized nanomaterials from agricultural waste were compared with those prepared from conventional sources through varied characterizations. Scanning electron microscopy, transmission electron microscopy, fourier transform infrared spectroscopy and N2 adsorption-desorption analysis was performed to examine the structural, functional and surface properties of the prepared nanomaterials from different precursors. High resolution imaging revealed better structural characteristics of the nanomaterials fabricated from agri-waste precursors. SEM images showed well exfoliated structure of GO and porous nature of NC. The folded layers of GO represent the presence of hydroxyl groups in the TEM images of GO @ graphite powder. TEM images of nanocellulose showed circular shaped nanoparticles of NC @ cellulose powder. Fourier transform infrared spectroscopy confirmed the presence of all the essential functional groups in the structure of prepared nanomaterials. The nanocomposites prepared using agricultural waste sources and conventional sources were inspected by N2 adsorption-desorption analysis, which demonstrated that the nanocomposites prepared from agri-waste sources exhibits much higher specific surface area than that of prepared from conventional precursors. R2 possess specific surface area of 82.832 m2 g−1 while, R1 possess only 6.721 m2 g−1. N2 adsorption-desorption analysis revealed the pore volume, pore diameter, micropore volume, micropore area and surface area of the prepared nanocomposites. The nanomaterials prepared using agricultural waste products shows desirable characteristics in all aspects which makes them equally applicable in energy storage devices, food packaging, drug delivery systems, nanosensors and water filtration systems.
Revamp of masonry structures using bio-additive infused air lime mortar as an applicator
Authors: Manoharan Abirami , Umarani C , Renuka S M 
Published: June 2023

Abstract
Lime masonry walls have been the initial type of masonry wall construction in the construction era. The minimally processed limestone extracted from the lime quarries gives a lesser carbon footprint than any other present-day construction material, making it superior to other construction materials in the construction industry and is the need of the hour. In this study, naturally fermented Bio-Additives, Jaggery and kadukkai were used to make lime mortar for the masonry prisms and walls, and the strength performance was investigated. The bio-additive and the lime powder combination were studied using a pH meter and pH strips to confirm their acidic/basic nature. The lime mortar was experimented with for its flexural strength using a beam specimen. The masonry prism study was initially made with stacked prisms and wall panels (English bond and Flemish bond) for testing compressive strength. The lime mortar thicknesses were varied into two for all the specimens of 10 mm and 15 mm for both the head and bed joints of the masonry. The experimental analysis revealed that a mortar thickness of 10 mm masonry increased the wall’s strength more than mortar of 15 mm thickness in the masonry, disproving the myth that higher mortar thickness in masonry increases the strength of the masonry. The mineralogical characterization of the mortar was carried out by SEM-EDAX to know the internal composition and morphological reactions, FTIR for the changes in the organic composition, and DSC-TGA to know the thermal properties of the mortar matrix. This study justifies the use of bio-additives-infused lime mortar for contemporary masonry projects.
EEG motor imagery classification using deep learning approaches in naïve BCI users
Authors: Guerrero-Mendez Cristian D , Blanco-Diaz Cristian F , Ruiz-Olaya Andres F , López-Delis Alberto , Jaramillo-Isaza Sebastian , Milanezi Andrade Rafhael , Ferreira De Souza Alberto , Delisle-Rodriguez Denis , Frizera-Neto Anselmo , Bastos-Filho Teodiano F 
Published: June 2023

Abstract
Motor Imagery (MI)-Brain Computer-Interfaces (BCI) illiteracy defines that not all subjects can achieve a good performance in MI-BCI systems due to different factors related to the fatigue, substance consumption, concentration, and experience in the use. To reduce the effects of lack of experience in the use of BCI systems (naïve users), this paper presents the implementation of three Deep Learning (DL) methods with the hypothesis that the performance of BCI systems could be improved compared with baseline methods in the evaluation of naïve BCI users. The methods proposed here are based on Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM)/Bidirectional Long Short-Term Memory (BiLSTM), and a combination of CNN and LSTM used for upper limb MI signal discrimination on a dataset of 25 naïve BCI users. The results were compared with three widely used baseline methods based on the Common Spatial Pattern (CSP), Filter Bank Common Spatial Pattern (FBCSP), and Filter Bank Common Spatial-Spectral Pattern (FBCSSP), in different temporal window configurations. As results, the LSTM-BiLSTM-based approach presented the best performance, according to the evaluation metrics of Accuracy, F-score, Recall, Specificity, Precision, and ITR, with a mean performance of 80% (maximum 95%) and ITR of 10 bits/min using a temporal window of 1.5 s. The DL Methods represent a significant increase of 32% compared with the baseline methods (p < 0.05). Thus, with the outcomes of this study, it is expected to increase the controllability, usability, and reliability of the use of robotic devices in naïve BCI users.
Using google street view panoramas to investigate the influence of urban coastal street environment on visual walkability
Authors: Huang Gonghu , Yu Yiqing , Lyu Mei , Sun Dong , Zeng Qian , Bart Dewancker 
Published: June 2023

Abstract
Urban street walkability can effectively promote public health and the construction of livable cities. In addition, the coastal streets play a positive role in showing urban vitality and image. Due to the growing leisure needs of residents, measuring the visual walkability perception (VIWP) in urban streets and exploring the influence mechanisms of urban coastal street environments on VIWP have theoretical and practical significance. However, the methods of the previous walkability studies have limitations in terms of cost, time and measurement scale. Based on Google Street View Panoramic (GSVP) image data, this study used the semantic difference (SD) method with virtual reality (VR) technology to evaluate the VIWP of Fukuoka coastal streets. Meanwhile, the proportion of streetscape elements was extracted from GSVP images by semantic segmentation. The correlation and regression analyses were performed between the VIWP evaluation values and streetscape elements. Then, the regression model of the VIWP and the streetscape elements was established. The results showed that the natural features had a positive influence on VIWP in coastal streets. Correspondingly, trees were the strongest contribution rate for the VIWP, followed by shrubs, grasses and water, however, buildings and cars had a negative influence on VIWP. The method extends previous studies for measuring walkability, and optimization strategies were proposed to improve the visual quality of the coastal streets. It can be applied in the construction and management of walkable coastal street environments.