bluuebunny/crossref_metadata_2025_split huggingface dataset:
New vaccination approach using formalin-killed Streptococcus pyogenes vaccine on the liver of Oreochromis niloticus fingerlings
Authors: Nasr-Eldahan Sameh , Attia Shreadah Mohamed , Maher Adham M. , El-Sayed Ali Tamer , Nabil-Adam Asmaa 
Published: August 2024

AbstractNewly synthesized vaccines prepared from formalin-killed bacteria Streptococcus pyogenes were investigated in the current study to evaluate the effectiveness of the newly synthesized vaccine as well as their safety by injected intraperitoneal. The study involved several steps 1st step is the preparation of the vaccine followed by the 2nd step: Evaluate the effectiveness and vaccine safety against pathogenic S. pyogenes through 4 different groups including control (Group I). Group II (Bacterial, infected group), Group III (Vaccine), and the Last group was the challenged group after the vaccination (Vacc + Bac). Different Immunological and biochemical parameters were measured in addition to hematological and histopathological examinations. For example, oxidative/antioxidants, inflammatory biomarkers, fragmentation and cell damage, and finally the histopathological study. The current study showed an increase in all oxidative, inflammatory, and cell damage (DNA fragmentation assays), additionally markedly elevation in histopathological cell damage in the infected group (Group II) compared with the control group. The vaccine and challenged after vaccination group (vaccine + Bacteria), showed great improvement in oxidative biomarkers (LPO) and an increase in antioxidants biomarkers (GSH, SOD, GST, DPPH, ABTS, GR and GPx), Also the inflammation and histopathological examination. The newly synthesized vaccine improved the resistance of Oreochromis niloticus and can be used as a preventive therapy agent for pathogenic bacteria S. pyogenes.
GelMA loaded with platelet lysate promotes skin regeneration and angiogenesis in pressure ulcers by activating STAT3
Authors: Jin Tingting , Fu Zexin , Zhou Liuyi , Chen Lulu , Wang Ji , Wang Lu , Yan Sheng , Li Ting , Jin Peihong 
Published: August 2024

AbstractPressure ulcers (PU) are caused by persistent long-term pressure, which compromises the integrity of the epidermis, dermis, and subcutaneous adipose tissue layer by layer, making it difficult to heal. Platelet products such as platelet lysate (PL) can promote tissue regeneration by secreting numerous growth factors based on clinical studies on skin wound healing. However, the components of PL are difficult to retain in wounds. Gelatin methacrylate (GelMA) is a photopolymerizable hydrogel that has lately emerged as a promising material for tissue engineering and regenerative medicine. The PL liquid was extracted, flow cytometrically detected for CD41a markers, and evenly dispersed in the GelMA hydrogel to produce a surplus growth factor hydrogel system (PL@GM). The microstructure of the hydrogel system was observed under a scanning electron microscope, and its sustained release efficiency and biological safety were tested in vitro. Cell viability and migration of human dermal fibroblasts, and tube formation assays of human umbilical vein endothelial cells were applied to evaluate the ability of PL to promote wound healing and regeneration in vitro. Real-time polymerase chain reaction (PCR) and western blot analyses were performed to elucidate the skin regeneration mechanism of PL. We verified PL’s therapeutic effectiveness and histological analysis on the PU model. PL promoted cell viability, migration, wound healing and angiogenesis in vitro. Real-time PCR and western blot indicated PL suppressed inflammation and promoted collagen I synthesis by activating STAT3. PL@GM hydrogel system demonstrated optimal biocompatibility and favorable effects on essential cells for wound healing. PL@GM also significantly stimulated PU healing, skin regeneration, and the formation of subcutaneous collagen and blood vessels. PL@GM could accelerate PU healing by promoting fibroblasts to migrate and secrete collagen and endothelial cells to vascularize. PL@GM promises to be an effective and convenient treatment modality for PU, like chronic wound treatment.
Pupil contagion variation with gaze, arousal, and autistic traits
Authors: Galazka Martyna A. , Thorsson Max , Lundin Kleberg Johan , Hadjikhani Nouchine , Åsberg Johnels Jakob 
Published: August 2024

AbstractPupillary contagion occurs when one’s pupil size unconsciously adapts to the pupil size of an observed individual and is presumed to reflect the transfer of arousal. Importantly, when estimating pupil contagion, low level stimuli properties need to be controlled for, to ensure that observations of pupillary changes are due to internal change in arousal rather than the external differences between stimuli. Here, naturalistic images of children’s faces depicting either small or large pupils were presented to a group of children and adolescents with a wide range of autistic traits, a third of whom had been diagnosed with autism. We examined the extent to which pupillary contagion reflects autonomic nervous system reaction through pupil size change, heart rate and skin conductance response. Our second aim was to determine the association between arousal reaction to stimuli and degree of autistic traits. Results show that pupil contagion and concomitant heart rate change, but not skin conductance change, was evident when gaze was restricted to the eye region of face stimuli. A positive association was also observed between pupillary contagion and autistic traits when participants’ gaze was constrained to the eye region. Findings add to a broader understanding of the mechanisms underlying pupillary contagion and its association with autism.
FishFocusNet: An improved method based on YOLOv8 for underwater tropical fish identification
Authors: Lu Zhaoxuan , Zhu Xiaolong , Guo Haitao , Xie Xingang , Chen Xiangzi , Quan Xiangqian 
Published: August 2024

AbstractAccurately identifying tropical fish serves as a crucial indicator, offering an insight into the state of marine biodiversity and the condition of coral reef ecosystems. However, the current detection networks are prone to omission and misidentification due to occlusion between fish and the complex underwater environment. This paper proposes a modified approach named FishFocusNet, in which alterable kernel convolution modules, asymptotic feature pyramid network (AFPN), and Shape‐IoU are integrated into YOLOv8. To extract a more comprehensive set of fish features, AKConv modules with arbitrary kernel sizes are proposed to take the place of the conventional fixed‐shaped kernels in the backbone for downsampling. AFPN is adopted as the feature integration structure in the neck, which enhances feature fusion and adaptive spatial fusion between non‐adjacent layers. In the detector head, Shape‐IoU is employed to achieve precise localization of fish targets. The superiorities of these modifications are proved by ablation experiments and comparative experiments. The experimental results show that the optimized approach obtained an mAP of 81.8% accompanied by 2.4 MB parameters and 3.6 GB FLOPS. Meanwhile, compared with more complicated models of similar scale, the proposed method can enhance recognition accuracy to 84.2% and significantly reduce computational costs.
Metastatic Malignant Melanoma of Brain: A Rare Case Report
Authors: Seervi Manoj Kumar , Jain Surendra , Meena Ugan Singh , Purohit Devendra Kumar 
Published: August 2024

AbstractMalignant melanoma is third most common cause of brain metastasis after lung and breast cancer. Most patients with brain metastases from malignant melanoma are diagnosed after treatment for known extracranial metastases and have a poor outcome despite various local and systemic therapeutic approaches. Here we discuss an unusual case of a 61-year-old male patient who presented with a brain metastasis as the initial disease presentation and the presumed primary lesion was later found in the gastrointestinal tract and the scalp. Treatment consisted of a surgical removal of the large intracranial lesion. Further evaluation for primary lesion was done by general physical examination, contrast-enhanced computed tomography (CECT) of the chest and whole abdomen. Apart from that, colonoscopy was done, and a biopsy was taken from a suspicious colonic lesion. The scalp pigmented lesion was also evaluated. Both biopsies were in favor of melanoma. Recently, management of metastatic melanoma of the brain is decided according to the number of lesions, accessibility, visceral metastasis, and resectability of the lesion. Various treatment options are surgical resection, whole brain radiotherapy (WBRT) and stereotactic radiosurgery (SRS). Malignant melanoma is relatively radioresistant, so the results are debatable. In conclusion, the prognosis of intracranial malignant melanoma is determined by the following factors: (1) the type of lesion; (2) the involvement of the leptomeninges; (3) the extent of tumor excised; and (4) the molecular immunology borstel number 1 (MIB 1) antibody index, which is the most relevant factor for prognosis in this type of cancer.
Alcohol- and drug-impaired e-scooter riding: exploring countermeasures from Australia, Belgium, New Zealand, and Norway
Authors: Alexander Marina , Bates Lyndel 
Published: August 2024

AbstractThis article explores the emerging problem of drug- and alcohol-impaired e-scooter riding. Fifteen government and e-scooter hire firm professionals from four jurisdictions (Australia, Belgium, New Zealand, Norway) described and assessed countermeasures designed to deter drug- and alcohol-impaired riding. Government professionals were from local/municipal councils, state and national departments of transport, and policing organisations. We used Braun and Clarke’s (Qual Res Psychol 18(3):328–352, 2020.https://doi.org/10.1080/14780887.2020.1769238) six-step method of thematic analysis and the NVivo qualitative analysis software system to analyse the interviews. All participants said traditional police enforcement is ineffective because laws and regulations are underdeveloped, and police have limited resources for patrols. Thematic analysis grouped countermeasures into four themes: enforcement, education, encouragement, and the road environment. Third-party policing initiatives show promise. For example, local/municipal councils required e-scooter hire firms to ban e-scooters from areas that sell alcohol through GPS-based geofencing. However, geofencing and other regulatory controls do not extend to privately owned e-scooters, a growing sector in the market. Other countermeasures used a combination of education and behavioural change techniques (BCTs) to encourage compliance. For example, innovative nudge methods (a type of BCT) have potential to change dangerous riding behaviours by targeting riding norms. However, participants said some people will continue to ride under the influence of alcohol or drugs either because they are addicted to substances or exhibit high-risk behaviours. Government should therefore adopt laws and regulations that build a more forgiving road environment, based on the safe system approach, to limit injuries when crashes occur.
A modified capacitance tomography image reconstruction approach based on iterative shrinkage-thresholding algorithm combined with deep networks
Authors: Xu Yi , Ma Zhiyang , Li Yi , Yang Wuqiang , Wang Haigang 
Published: August 2024

Abstract
Due to the ‘soft-field’ effect and the challenges posed by ill-posed and ill-conditioned inverse problems, it is difficult to obtain high quality images from an electrical capacitance tomography (ECT) system. To achieve both high-quality images and fast imaging speed with limited measurement data, an image reconstruction algorithm, which was initially proposed for compressive sensing, is adapted for ECT image reconstruction to optimize the ill-posed nature of its inverse problem. The proposed algorithm leverages deep learning networks inspired by the iterative shrinkage-thresholding algorithm (ISTA), thereby creating a model that is both mathematically interpretable and endowed with trainable parameters. Building upon this foundation, the conventional Landweber iteration is integrated with the ISTA-Net to refine the optimization process for ECT image reconstruction. In order to propose an effective model adapting to the actual multiphase flow characteristics and complex flow pattern changes, the training and test process is driven by a comprehensive dataset generated from dynamic simulations, rather than artificial samples of multiphase distributions. This numerical methodology simulates the dynamic measurement process of a virtual ECT sensor by coupling the gas–liquid two-phase flow field and the ECT electrostatic field. The results of the testing phase indicate that the proposed algorithm outperforms traditional ECT image reconstruction methods. Compared with the linear back projection algorithm, the average image error and gas fraction error have been reduced by 20.44% and 16.74%, respectively, while maintaining a computational speed comparable to that of the Landweber iteration. The accuracy of the new algorithm in reconstructing the two-phase interface and estimating the gas fraction has been validated by static experimental tests, showing its potential for practical application in online gas–liquid two-phase flow measurement scenarios.
A multi-channel fusion variational autoencoder-based RUL prediction approach for multi-sensor systems
Authors: Wang Yuxiao , Suo Chao , Zhao Yuyu 
Published: August 2024

Abstract
Deep learning (DL)-based approaches have demonstrated remarkable performance in predicting the remaining useful life (RUL) of complex systems, which is beneficial for making timely maintenance decisions. However, the majority of these DL methods suffer from a lack of interpretability, and it is difficult to mine the degradation features in the presence of significant measurement noises. To remedy the deficiency, a multi-channel fusion variational autoencoder (MCFVAE)-based approach is proposed. A feature fusion module is designed to capture and fuse the multi-channel features, which facilitates the disclosure of the degradation information from the multi-sensor data. A variational inference module is further introduced to generate the compressive representations and project them into a latent space as an interpretable component, which can display the degradation degree of the multi-sensor systems. A regressor module is finally utilized to establish the relationship between the compressive representations and the RUL. The superior feature fusion and distribution characteristics learning abilities of the MCFVAE contribute to achieving robust and interpretable RUL prediction. The effectiveness and superiority of the proposed method are experimentally validated through a publicly available Commercial modular aero propulsion system simulation dataset and compared with the existing methods.
Intelligent fault diagnosis of multi-source cross-machine bearings based on center-weighted optimal transport and class-level alignment domain adaptation
Authors: Shang Zhiwu , Wu Changchao , Liu Fei , Pan Cailu , Cheng Hongchuan 
Published: August 2024

Abstract
Most of the current domain adaptation research primarily focuses on the single-source or multi-source domain transfer constructed under different working conditions of the same machine. However, when faced with cross-machine tasks with significant domain discrepancies, forcing the direct feature alignment between source and target domain samples may lead to negative transfer, thereby reducing the model’s diagnostic performance. To overcome the above limitations, this paper proposes a multi-source deep transfer model based on center-weighted optimal transport (CWOT) and class-level alignment domain adaptation. Firstly, to enhance the representation capability of deep features, a multi-structure feature representation network is constructed to enrich the information capacity embedded within the deep features, thereby achieving better domain adaptation capabilities. Then, the local maximum mean discrepancy is introduced to fully exploit fine-grained information and discriminative features among different source domains, minimizing the distribution differences among the source domains to the greatest extent, thus capturing reliable and highly generalized multi-source domain invariant features. On this basis, a CWOT strategy is designed, which comprehensively considers the transport cost of intra-domain uncertainty and inter-domain correlation among samples, establishing a more effective transport between source and target domains, alleviating the problem of sample negative transfer, and improving the model’s cross-machine diagnostic performance. Finally, instance studies are conducted through multiple cross-machine transfer diagnostic tasks, demonstrating that the proposed method outperforms existing domain adaptation methods in terms of diagnostic accuracy and fault transfer capability. This research provides a reliable fault diagnosis method for detecting the health status of rotating machinery equipment, promoting the application of domain adaptation technology in practical industry.
Shuffle-fusion pyramid network for bearing fault diagnosis under noisy environments
Authors: Zhao Cheng , Deng Linfeng , Zhang Yuanwen , Wang Guojun 
Published: August 2024

Abstract
Recent advancements in deep learning have driven the development of big data-driven fault diagnosis techniques. However, traditional models often face significant computational challenges, making them impractical for on-site deployment in rolling bearing fault diagnosis. To address this issue, we introduce the Shuffle-Fusion Pyramid Network (Shuffle-FPN), a novel lightweight fault diagnosis model with a pyramid architecture. Shuffle-FPN enhances fault diagnosis by integrating fault signals across various scales through its pyramid structure, expanding the network’s scope while reducing its depth. The use of depth-wise separable convolutions streamlines network parameters, and channel shuffling ensures comprehensive information fusion across convolutional channels. Additionally, a global representation module compensates for the loss of global context due to increased convolutional depth. These enhancements enable Shuffle-FPN to extract nuanced fault features amidst noise and operate efficiently on devices with limited memory, ensuring real-time fault diagnosis even in complex environments. Rigorous experiments on public dataset from the Paderborn University and our research group’s dataset demonstrate that Shuffle-FPN excels in fault identification under noisy environments and significantly reduces the memory footprint.
Application of N-doped NiCo2O4/NiO/Co3O4 composites rich in oxygen vacancies in electromagnetic wave absorption
Authors: Li Junkang , Yang Yiqing , Ma Yongqing , Zhu Chuhong , Wang Meiling , Dai Zhenxiang , Zheng Ganhong , Ding Wei , Sheng Zhigao 
Published: August 2024

Abstract
In this work, N-doped and oxygen vacancy-rich NiCo2O4/NiO/Co3O4 composites are synthesized by the direct calcination method. Noticeably, by changing the additive concentrations of urea dissolved in DMF (N–N dimethylformamide), the electromagnetic wave (EMW) absorption abilities of NiCo2O4/NiO/Co3O4 composite effectively. A maximum reflection loss (RLmax) value at 12.94 GHz for a 2.8 mm thick sheet is −29.76 dB, while its effective absorption bandwidth (RL < −10 dB) reaches 4.21 GHz. In-depth research of possible mechanisms of EMW absorption enhancement. Owing to its simple preparation method and superb EMW absorption properties, the NiCo2O4/NiO/Co3O4 composites have a chance to be suitable candidates for high-property EMW absorbers.
The Lorenz system as a gradient-like system
Authors: Parker Jeremy P 
Published: August 2024

Abstract
We formulate, for continuous-time dynamical systems, a sufficient condition to be a gradient-like system, i.e. that all bounded trajectories approach stationary points and therefore that periodic orbits, chaotic attractors, etc do not exist. This condition is based upon the existence of an auxiliary function defined over the state space of the system, in a way analogous to a Lyapunov function for the stability of an equilibrium. For polynomial systems, Lyapunov functions can be found computationally by using sum-of-squares optimisation. We demonstrate this method by finding such an auxiliary function for the Lorenz system. We are able to show that the system is gradient-like for

0
⩽
ρ
⩽
12

when σ = 10 and

β
=
8

/

3

, significantly extending previous results. The results are rigorously validated by a novel procedure: First, an approximate numerical solution is found using finite-precision floating-point sum-of-squares optimisation. We then prove that there exists an exact solution close to this using interval arithmetic.
Axions and primordial magnetogenesis: the role of initial axion inhomogeneities
Authors: Anzuini Filippo , Maggi Angelo 
Published: August 2024

Abstract
The relic density of dark matter in the ΛCDM model restricts the parameter space for a cosmological axion field, constraining the axion decay constant, the initial amplitude of the axion field and the axion mass. It is shown via lattice simulations how the relic density of axion-like particles with masses close to the one of the QCD axion is affected by axion-gauge field interactions and by initial axion inhomogeneities. For pre-inflationary axions, once the Hubble parameter becomes smaller than the axion mass, the latter starts to oscillate, and part of its energy density is spent producing gauge fields via parametric resonance. If the gauge fields are dark photons and Standard Model photons, the energy density of dark photons becomes higher than the one of the axion, while the high conductivity of the primordial plasma damps the oscillations of the photon field. Such a scenario allows for the production of small-scale, primordial magnetic fields, and it is found that the relic density of axions with a low decay constant are within the bounds set by the ΛCDM model, while GUT-scale axions are far too abundant. It is also shown that initial inhomogeneities of the axion field can change substantially the gauge field production, boosting or suppressing (depending on the axion parameters and couplings) the magnetogenesis mechanism with respect to an homogeneous axion field. It is found that when the axion mass is far lighter than the QCD axion model and the initial axion field is inhomogeneous, weak but cosmologically relevant magnetic field seeds can be generated on scales of the order of 0.1 kpc.