bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determination of the parameters of rock viscoelastic creep model and analysis of parameter degradation
Authors: Zheng Zhiming , Yang Yu , Pan Cheng 
Published: April 2023

AbstractDifferent stress creep tests are conducted on the sandstone in this study to better describe the creep properties of rocks under different stress states. A model that describes the rock creep process is established. The various stages of creep can be described by combining the creep properties of the creep elements of the model. A new method for determining creep parameters is proposed by using the special point on the creep curve and the definition of creep deformation. The relationship between the creep parameters, stress, and time is analyzed. An improved creep model that considers the effects of stress state and time on the creep parameters is developed. This model is verified using experimental data and calculation results. Results shows that the improved creep model better describes the creep properties of rocks and provides a new method for determining future model parameters. The shear modulus of elastic model controls the instantaneous deformation. The shear modulus of viscoelastic model governs the limit of viscoelastic deformation. The shear viscoelastic coefficient of viscoelastic model increases with the increase in stress. The coefficient of viscoplastic model controls the viscoplastic creep rate. The coefficient of a nonlinear Newtonian dashpot mainly controls the accelerated creep deformation of rock. The calculation results of the proposed model agree well with the experimental data under the action of different stress levels. This model accurately reflects the creep characteristics of the primary and steady-state creep stages, and overcomes the shortcomings of the traditional Nishihara model in describing accelerated creep.
A gold nanoparticles coated unclad single mode fiber-optic sensor based on localized surface plasmon resonance
Authors: Fakhri Makram A. , Salim Evan T. , Tariq Sara M. , Ibrahim Raed Khalid , Alsultany Forat H. , Alwahib Ali. A. , Alhasan Sarmad Fawzi Hamza , Gopinath Subash C. B. , Salim Zaid T. , Hashim U. 
Published: April 2023

AbstractIn the last few decays, the fiber-optic was employed in the field of sensing because of its benefits in contrast to other types of sensors such as small size, easy to fabricate, high response, and flexibility. In this study, unclad single mode fiber-optic sensor is proposed to operate at 650 nm wavelength. COMSOL Multiphysics 5.1 finite element method (FEM) is used to design the sensor and tested it theoretically. The middle portion of the fiber cladding is removed and replaced by gold nanoparticles (Au NPs) of 50 nm thickness. Analytic layer of 3 μm thickness was immersed in different liquids in range of refractive index (RI) from 1.000281 to 1.39. These liquids are NaCl Deionized (DI) water solution, sucrose-Deionized (DI) water solution, and glycerol solution Deionized (DI) water. It was found that the highest obtained sensitivity and resolution are for glycerol-DI water solution with value of 3157.98 (nm/RIU) and 3.16 × 10–5(RIU), respectively. Furthermore, it is easy to fabricate and of low cost. In experiments, pulsed laser ablation (PLA) was used to prepare Au NPs. X-ray diffraction (XRD) shown that the peak of the intensity grew as the ablated energy increased as well as the structure crystallization. Transmission electron microscopy (TEM) revealed an average diameter of 30 nm at the three ablated energies, while X-ray spectroscopy (EDX) spectrum has indicated the presence of Au NPs in the prepared solution. The photoluminescence (PL) and ultraviolet–visible UV–Vis transmission were used to study the optical properties of the prepared Au NPs. An optical spectrum analyzer was used to obtain the sensor's output results. It has shown that best intensity was obtained for sucrose which confined with theoretical results.
Intravitreal anti-vascular endothelial growth factor monotherapy in age-related macular degeneration with submacular hemorrhage
Authors: Maruyama-Inoue Maiko , Kitajima Yoko , Yanagi Yasuo , Inoue Tatsuya , Kadonosono Kazuaki 
Published: April 2023

AbstractThe purpose of this study was to evaluate the 1-year visual outcomes of patients treated with intravitreal aflibercept (IVA) or brolucizumab (IVBr) for submacular hemorrhage (SMH) secondary to neovascular age-related macular degeneration (AMD). We retrospectively studied 62 treatment-naïve eyes with SMHs exceeding one disc area (DA) secondary to AMD treated with IVA or IVBr. All patients received three monthly intravitreal injections in the loading phase followed by as-needed injections or fixed dosing. If a vitreous hemorrhage (VH) developed during the follow-up period, injections were discontinued and vitrectomy was performed. We evaluated the changes in the best-corrected visual acuity (BCVA) and factors that affected the BCVA improvement and VH development. A VH during treatment developed in five eyes (8.1%) (VH + group), and the mean BCVA worsened from 0.45 to 0.92. The BCVA improved significantly (P = 0.040) in the remaining 57 eyes (VH − group) from 0.42 to 0.36. The development of VHs was associated with significantly (P < 0.001) less VA improvement. Furthermore, large DAs and younger age at baseline were associated significantly (P = 0.010 and 0.046, respectively) with the development of VHs. Both IVA and IVBr appeared to improve functional outcomes in patients with SMH secondary to AMD when VHs did not develop. However, a VH developed in 8.1% of eyes after treatment. Although anti-vascular endothelial growth factor treatments were well-tolerated, for cases with large SMH at baseline, it should be considered that VH may occur during the monotherapy treatment process using IVA or IVBr, and that achieving good visual outcomes may be difficult in some cases.
Rapid detection of isocitrate dehydrogenase 1 mutation status in glioma based on Crispr-Cas12a
Authors: Feng Zhebin , Kong Dongsheng , Jin Wei , He Kunyu , Zhao Junyan , Liu Bin , Xu Hanyun , Yu Xin’guang , Feng Shiyu 
Published: April 2023

AbstractThe aim is to use Crispr-Cas12a for the rapid detection of the single nucleotide polymorphism (SNP) of isocitrate dehydrogenase 1 (IDH1)-R132H locus and explore the effectiveness and consistency of this method with direct sequencing method for detecting IDH1-R132H of glioma tissue samples. 58 previous frozen tissue and 46 recent fresh tissue samples of adult diffuse glioma were selected to detect IDH1-R132H using Crispr-Cas12a. The results of immunohistochemistry (IHC) and direct sequencing methods were analyzed. We calculated the efficiency index of Crispr-Cas12a and IHC, and analyzed the consistency among Crispr-Cas12a, IHC and direct sequencing method using paired Chi-sequare test and Kappa identity test. We accomplished the rapid detection of IDH1-R132H in 60 min using Crispr-Cas12a. Regarding direct sequencing method as the gold standard, the sensitivity, specificity and consistency rate of Crispr-Cas12a was 91.4%, 95.7% and 93.1% in the frozen sample group, while 96.1%, 89.7% and 92.0% in the fresh sample group, respectively. Kappa test showed good consistency between the two methods (k = 0.858). Crispr-Cas12a can quickly and accurately detect IDH1-R132H and has good stability. It is a promising method to detect IDH1 mutation status intraoperatively.
Deep learning based automatic detection algorithm for acute intracranial haemorrhage: a pivotal randomized clinical trial
Authors: Yun Tae Jin , Choi Jin Wook , Han Miran , Jung Woo Sang , Choi Seung Hong , Yoo Roh-Eul , Hwang In Pyeong 
Published: April 2023

AbstractAcute intracranial haemorrhage (AIH) is a potentially life-threatening emergency that requires prompt and accurate assessment and management. This study aims to develop and validate an artificial intelligence (AI) algorithm for diagnosing AIH using brain-computed tomography (CT) images. A retrospective, multi-reader, pivotal, crossover, randomised study was performed to validate the performance of an AI algorithm was trained using 104,666 slices from 3010 patients. Brain CT images (12,663 slices from 296 patients) were evaluated by nine reviewers belonging to one of the three subgroups (non-radiologist physicians, n = 3; board-certified radiologists, n = 3; and neuroradiologists, n = 3) with and without the aid of our AI algorithm. Sensitivity, specificity, and accuracy were compared between AI-unassisted and AI-assisted interpretations using the chi-square test. Brain CT interpretation with AI assistance results in significantly higher diagnostic accuracy than that without AI assistance (0.9703 vs. 0.9471, p < 0.0001, patient-wise). Among the three subgroups of reviewers, non-radiologist physicians demonstrate the greatest improvement in diagnostic accuracy for brain CT interpretation with AI assistance compared to that without AI assistance. For board-certified radiologists, the diagnostic accuracy for brain CT interpretation is significantly higher with AI assistance than without AI assistance. For neuroradiologists, although brain CT interpretation with AI assistance results in a trend for higher diagnostic accuracy compared to that without AI assistance, the difference does not reach statistical significance. For the detection of AIH, brain CT interpretation with AI assistance results in better diagnostic performance than that without AI assistance, with the most significant improvement observed for non-radiologist physicians.
Lysyl oxidase-like 2 processing by factor Xa modulates its activity and substrate preference
Authors: Wang Huilei , Poe Alan , Martinez Yus Marta , Pak Lydia , Nandakumar Kavitha , Santhanam Lakshmi 
Published: April 2023

AbstractLysyl oxidase-like 2 (LOXL2) has been identified as an essential mediator of extracellular matrix (ECM) remodeling in several disease processes including cardiovascular disease. Thus, there is growing interest in understanding the mechanisms by which LOXL2 is regulated in cells and tissue. While LOXL2 occurs both in full length and processed forms in cells and tissue, the precise identity of the proteases that process LOXL2 and the consequences of processing on LOXL2’s function remain incompletely understood. Here we show that Factor Xa (FXa) is a protease that processes LOXL2 at Arg-338. Processing by FXa does not affect the enzymatic activity of soluble LOXL2. However, in situ in vascular smooth muscle cells, LOXL2 processing by FXa results in decreased cross-linking activity in the ECM and shifts substrate preference of LOXL2 from type IV collagen to type I collagen. Additionally, processing by FXa increases the interactions between LOXL2 and prototypical LOX, suggesting a potential compensatory mechanism to preserve total LOXs activity in the vascular ECM. FXa expression is prevalent in various organ systems and shares similar roles in fibrotic disease progression as LOXL2. Thus, LOXL2 processing by FXa could have significant implications in pathologies where LOXL2 is involved.
Continuous millisecond conformational cycle of a DEAH box helicase reveals control of domain motions by atomic-scale transitions
Authors: Becker Robert A. , Hub Jochen S. 
Published: April 2023

AbstractHelicases are motor enzymes found in every living organism and viruses, where they maintain the stability of the genome and control against false recombination. The DEAH-box helicase Prp43 plays a crucial role in pre-mRNA splicing in unicellular organisms by translocating single-stranded RNA. The molecular mechanisms and conformational transitions of helicases are not understood at the atomic level. We present a complete conformational cycle of RNA translocation by Prp43 in atomic detail based on molecular dynamics simulations. To enable the sampling of such complex transition on the millisecond timescale, we combined two enhanced sampling techniques, namely simulated tempering and adaptive sampling guided by crystallographic data. During RNA translocation, the center-of-mass motions of the RecA-like domains followed the established inchworm model, whereas the domains crawled along the RNA in a caterpillar-like movement, suggesting an inchworm/caterpillar model. However, this crawling required a complex sequence of atomic-scale transitions involving the release of an arginine finger from the ATP pocket, stepping of the hook-loop and hook-turn motifs along the RNA backbone, and several others. These findings highlight that large-scale domain dynamics may be controlled by complex sequences of atomic-scale transitions.
Drifting Faraday patterns under localised driving
Authors: Marín Juan F. , Riveros-Ávila Rafael , Coulibaly Saliya , Taki Majid , Gordillo Leonardo , García-Ñustes Mónica A. 
Published: April 2023

AbstractPhysical systems undergoing spontaneous pattern formation are governed by intrinsic length scales that may compete with extrinsic ones, resulting in exceptional spatiotemporal behaviour. In this work, we report experimental and theoretical evidence that spatial nonuniformity sets Faraday-wave patterns in motion, which are noticeable in the zigzag and drift dynamics exhibited by their wave crests. We provide a minimal theoretical model that succeeds in characterising the growth of localised patterns under nonuniform parametric driving. Furthermore, the derivation accounts for symmetry-breaking nonlinear gradients that we show are the source of the drift mechanism, which comes into play right after the system has crossed a secondary bifurcation point. Numerical solutions of the governing equations match our experimental findings and theoretical predictions. Our results advance the understanding of pattern behaviour induced by nonuniformity in generic nonlinear extended systems far from equilibrium.
A symmetric adaptive visibility graph classification method of orthogonal signals for automatic modulation classification
Authors: Bai Haihai , Yang Jingjing , Huang Ming , Li Wenting 
Published: April 2023

AbstractVisibility graph methods allow time series to mine non‐Euclidean spatial features of sequences by using graph neural network algorithms. Unlike the traditional fixed‐rule‐based univariate time series visibility graph methods, a symmetric adaptive visibility graph method is proposed using orthogonal signals, a method applicable to in‐phase and quadrature (I/Q) orthogonal signals for adaptive graph mapping for radio modulated signals in automatic modulation classification tasks. The method directly models the intra‐channel and inter‐channel graph relations of I/Q signals using two different types of convolutional kernels. It captures non‐Euclidean spatial feature information of I/Q signals using a graph neural network combining graph sampling aggregation and graph differentiable pooling as a feature extractor. Extensive experimental results on two benchmark datasets and a simulated dataset containing channel fading show that the proposed Quadrature Signal Symmetric Adaptive Visibility Graph (QSSAVG) method in this paper outperforms the benchmark method in terms of classification accuracy and is also more robust against channel fading and noise variations.
Cross‐class pest and disease vegetation detection based on small sample registration
Authors: Jiayao Liu , Linfeng Wang , Yunsheng Wang , MingMing An , Wenfei Jiang , Shipu Xu 
Published: April 2023

AbstractThis paper introduces few‐shot anomaly detection (FSAD), a practical and less anomaly detection (AD) method, which can provide a limited number of normal images for each class during training. So far, studies on FSAD have been carried out according to each model, and there is no discussion of commonalities between different types. Depending on how people detect unusual lies, the problematic images are compared to the normal ones. The image alignment method based on different classifications is used to train the target detection model independent of classification, and performed ablation experiments on the pest and disease datasets in different environments for verification. This is the first time the FSAD method has been used to train a single scalable model without the need to train new classifications or adjust parameters. The experimental results show that the application of AUC based on vegetation disease data set and vegetation pest data set in FSAD algorithm is improved by 19.5% compared with the existing algorithm.
A multiple spatio‐temporal features fusion approach for short‐term passenger flow forecasting in urban rail transit
Authors: Yu Qian , Zhang Yadong , Guo Jin , Ma Wengang , Liu Ruiqi , Lai Pei 
Published: April 2023

AbstractTimely and precise short‐term passenger flow forecasting (STPFF) is a key to intelligent urban rail transit (URT) operation. The uncertainty of passenger travel behaviors leads to passenger flow data showing high nonlinearities and complex spatio‐temporal correlation. Therefore, the ability to capture such correlations determines the prediction performance of the model. However, current methods either consider only the physical topology of URT network or lack the ability to model global spatial dynamics, making it difficult to obtain satisfactory predictions. Therefore, a Multiple Spatio‐Temporal Features Fusion (MSTFF) network is proposed for STPFF in URT networks. Specifically, the connectivity and passenger flow similarity relationships in URT networks are encoded as physical adjacency graph and virtual functional similarity graph, respectively, and then these two complementary graphs are input into two designed Residual Graph Convolutional Gated Recurrent Unit (RGCGRU) modules to extract their spatio‐temporal features. Second, an Attention‐based Gated Recurrent Unit (AGRU) module is designed to capture global dynamic evolutionary trends in both spatial and temporal dimensions. Finally, a fully connected neural network is used to fuse these features. Experiments on two real passenger flow datasets of URT show that MSTFF performs well on various prediction tasks (15, 30, 45, and 60 min).
Driver distraction detection via multi‐scale domain adaptation network
Authors: Wang Jing , Wu ZhongCheng 
Published: April 2023

AbstractDistracted driving is the leading cause of road traffic accidents. It is essential to monitor the driver's status to avoid traffic accidents caused by distracted driving. Current research on detecting distracting behaviours focuses on analysing image features using convolutional neural networks (CNNs). However, the generalisation ability of the current distracted driving models is limited. This paper aims to improve the generalisation ability of distracted driving models that are affected by factors such as the driver himself, the background, the monitoring angle, and so on. A new driver distraction detection method, which is referred to as multi‐scale domain adaptation network (MSDAN), was proposed to improve model adaptability. The method consists of three stages: first, multi‐scale convolution was introduced to build a new backbone to accommodate better the valuable feature of the target on different scales. Secondly, the authors designed the domain adaptation network to improve the model's adaptability to the difference in data sources through adversarial training. Finally, dropout is added to the fully connected layer to increase the model's generalisation ability. The comparison results on the large‐scale driver distraction detection dataset show that the authors’ method can accurately detect driver distraction and has good generalisation performance, with an accuracy improvement in the cross‐driver and cross‐dataset experiments.
A generalized space shift keying modulation for molecular MIMO systems
Authors: Ahuja Muskan , Bhatnagar Manav R. 
Published: April 2023

AbstractIndex modulation utilizes spatial dimensions for transmission of information in multiple‐input multiple‐output (MIMO) molecular communication systems. Molecular space shift keying (MSSK) is an IM‐based technique that modulates information in the antenna index and efficiently combats both intersymbol interference and interlink interference in molecular MIMO systems. In this paper, generalized form of the MSSK scheme, that is, generalized MSSK (GMSSK) is proposed which activates a fixed number of antennas for information transmission. The antenna constellation is selected judiciously to minimize the chances of errors in the proposed GMSSK strategy. Design guidelines are provided for the GMSSK antenna constellation for the case of two activated antennas at the transmitter side. Exploiting an additional degree of freedom, the presented GMSSK scheme is shown to achieve reasonably close or better error performance with a smaller antenna array size as compared to the traditional MSSK scheme.
Contribution des résidus de culture à la réduction du déficit alimentaire des troupeaux de ruminants dans l’Ouémé Supérieur au Bénin
Authors: Djohy Gildas Louis , Sounon Bouko Boni , Djohy Georges , Dossou Paulin Jésutin , Yabi Jacob Afouda 
Published: April 2023

L’utilisation de la biomasse des résidus de cultures présents sur les exploitations agricoles après les récoltes est importante pour alimenter les animaux durant la saison sèche. La présente étude vise d’une part à estimer la biomasse des résidus au champ, et d’autre part à analyser la capacité de charge qui en résulte dans l’Ouémé Supérieur au Bénin. Des enquêtes ont été réalisées auprès d’agriculteurs et d’éleveurs, ainsi que des mesures de biomasses de résidus. Trois cents éleveurs ont été interrogés sur l’importance, la durée d’utilisation et les modes d’accès aux résidus. Puis, 350 placettes de 5 × 5 m ont été installées dans une sélection de champs, dont 175 en 2020 et 175 en 2021. Les résultats montrent que les quantités de résidus disponibles à l’hectare varient selon les cultures et les années. En 2020, les quantités mesurées sont les suivantes : 5,3 t de Matière Sèche/ha pour le maïs ; 6,7 t MS/ha pour le sorgho ; 3,4 t MS/ha pour le riz ; 2,3 t MS/ha pour le niébé ; 2,0 t MS/ha pour le soja ; 1,0 t MS/ha pour l’arachide ; 1,0 t MS/ha pour le voandzou. En 2021 : 4,4 t MS/ha pour le maïs ; 5,3 t MS/ha pour le sorgho ; 3,2 t MS/ha pour le riz ; 2,1 t MS/ha pour le niébé ; 2,0 t MS/ha pour le soja ; 1,1 t MS/ha pour l’arachide ; 1,1 t MS/ha pour le voandzou. Le bilan entre la capacité de charge calculée à partir des résidus et la charge animale réelle est négatif sur les deux années d’étude. Les résidus ont couvert potentiellement 77 % (2020) et 66 % (2021) des besoins alimentaires du bétail entre décembre et février. La prise en compte de ces résultats dans l’élaboration des politiques agricoles et pastorales contribuerait à mieux gérer l’ensemble des ressources fourragères disponibles pour le bétail.
Iatrogenic Complications and Management of Biliary Interventions
Authors: Martens Spencer , Karani Kunal , Navuluri Rakesh 
Published: April 2023

AbstractIatrogenic complications can result from both diagnostic and therapeutic hepatobiliary interventions such as percutaneous transhepatic cholangiography, percutaneous biliary drain placement, percutaneous liver biopsy, transarterial liver-directed therapies for malignancy, and liver transplantation. In many of these procedures, the proximity of the biliary ductal system to the hepatic arteries and portal veins predisposes to injury. In other procedures, compromised arterial supply to the biliary system, errors related to complexity of the procedures, or the fragility of the structures themselves may be the root cause. Understanding the etiology of these iatrogenic complications as well as the management options is essential for a multidisciplinary team tasked with managing patients with complex hepatobiliary diseases.