bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modulation instability and optical wave profiles for the conformable Schrödinger–Poisson dynamical system
Authors: Yasin Muhammad Waqas , Baber Muhammad Zafarullah , Munir Muskan , Hassaballa Abaker A. , Inc Mustafa , Iqbal Muhammad Sajid , Rezapour Shahram 
Published: July 2024

AbstractThis manuscript studies the exact solitary wave profiles for the conformable Schrödinger–Poisson dynamical system. This system has a significant role in gravity’s quantum state operation approximates the interaction between quantum mechanics and gravitation. The diverse exact solitary wave profiles are constructed by using the Khater method. The different closed-form solutions are obtained such as dark, singular, hyperbolic, periodic, and plane waves. Moreover, the modulation instability is also discussed for this dynamical system. To, show the physical significance of desired results we plot the 3D and 2D plots along with the related contour graphs, which are also drawn. The constraint criteria for the exact solutions are also exposed.
Optimizing Care: Integrative Oncology in Myeloproliferative Neoplasm
Authors: Singh Shagun , Peshin Supriya , Larsen Ashley , Gowin Krisstina 
Published: July 2024

Abstract
Purpose of Review
Myeloproliferative neoplasm (MPN) burdens the lives of those affected. MPN patients endure significant impacts on their physical, psychological, and social well-being. While pharmacological interventions offer some disease and symptom control, they often have unfavorable side effects. This review explores the potential of Integrative Oncology (IO) therapies in managing MPNs and their associated symptoms.

Recent Findings
IO is dedicated to augmenting conventional treatments through integrating interventions targeting the mind, body, nutrition, supplements, and other supportive care therapies. Several small studies suggest the benefit of an IO approach in MPN patients. These benefits are postulated to be modulated through enhanced physical capacity, reduced disease-related inflammation, subconscious mind training, and gut microbiome modulation.

Summary
By combining IO with evidence-based pharmacological treatments, the potential exists to enhance the quality of life and clinical outcomes for individuals with MPNs. Future research should prioritize well-powered studies, including diverse demographics and symptom profiles, with appropriate study duration, to draw definite conclusions regarding the observed effects.
lncRNA FLJ20021 regulates CDK1-mediated PANoptosis in a ZBP1-dependent manner to increase the sensitivity of laryngeal cancer-resistant cells to cisplatin
Authors: Yin Xiaoyan , Zhang Haizhong , Wang Jingmiao , Bian Yanrui , Jia Qiaojing , Yang Zhichao , Shan Chunguang 
Published: July 2024

AbstractIn this study, we investigated the role of the newly discovered lncRNA FLJ20021 in laryngeal cancer (LC) and its resistance to cisplatin treatment. We initially observed elevated lncRNA FLJ20021 levels in cisplatin-resistant LC cells (Hep-2/R). To explore its function, we transfected lncRNA FLJ20021 and cyclin-dependent kinase 1 (CDK1) into Hep-2/R cells, assessing their impact on cisplatin sensitivity and PANoptosis. Silencing lncRNA FLJ20021 effectively reduced cisplatin resistance and induced PANoptosis in Hep-2/R cells. Mechanistically, lncRNA FLJ20021 primarily localized in the nucleus and interacted with CDK1 mRNA, thereby enhancing its transcriptional stability. CDK1, in turn, promoted panapoptosis in a ZBP1-dependent manner, which helped overcome cisplatin resistance in Hep-2/R cells. This study suggests that targeting lncRNA FLJ20021 can be a promising approach to combat cisplatin resistance in laryngeal cancer by regulating CDK1 and promoting PANoptosis via the ZBP1 pathway. These findings open up possibilities for lncRNA-based therapies in the context of laryngeal cancer.
DyHANE: dynamic heterogeneous attributed network embedding through experience node replay
Authors: Martirano Liliana , Ienco Dino , Interdonato Roberto , Tagarelli Andrea 
Published: July 2024

AbstractWith real-world network systems typically comprising a large number of interactive components and inherently dynamic, Graph Continual Learning (GCL) has gained increasing popularity in recent years. Furthermore, most applications involve multiple entities and relationships with associated attributes, which has led to widely adopting Heterogeneous Information Networks (HINs) for capturing such rich structural and semantic meaning. In this context, we deal with the problem of learning multi-type node representations in a time evolving graph setting, harnessing the expressive power of Graph Neural Networks (GNNs). To this purpose, we propose a novel framework, named DyHANE—Dynamic Heterogeneous Attributed Network Embedding, which dynamically identifies a representative sample of multi-typed nodes as training set and updates the parameters of a GNN module, enabling the generation of up-to-date representations for all nodes in the network. We show the advantage of employing HINs on a data-incremental classification task. We compare the results obtained by DyHANE on a multi-step, incremental heterogeneous GAT model trained on a sample of changed and unchanged nodes, with the results obtained by either the same model trained from scratch or the same model trained solely on changed nodes. We demonstrate the effectiveness of the proposed approach in facing two major related challenges: (i) to avoid model re-train from scratch if only a subset of the network has been changed and (ii) to mitigate the risk of losing established patterns if the new nodes exhibit unseen properties. To the best of our knowledge, this is the first work that deals with the task of (deep) graph continual learning on HINs.
Treatment of effluent from a malting processing plant using bio-coagulants
Authors: Murisa V. , Ncube S. , Moyo L. B. , Danha G. , Mamvura T. A. 
Published: July 2024

AbstractStringent measures by water authorities worldwide on water clarification has resulted in the use of chemical-based coagulants to be a formidable challenge. This has driven the need to find alternative sustainable coagulants such as plant-based bio coagulants which are readily available, abundant and cost effective in developing countries such as Zimbabwe. In this regard, the effectiveness of treating effluent from a brewery malting processing plant using bio-coagulants (Aloe vera, Cactus opuntia and Okra seeds) was investigated compared to that of a chemical coagulant (Alum). The water pollution parameters that were investigated include turbidity, total dissolved solids, electrical conductivity, temperature and pH. The results showed that Alum was the most effective coagulant as it reduced the turbidity from 734 NTU to 68.3 NTU and Total Dissolved Solids (TDS) from 19,800 ppm to 880 ppm at a dosage of 40 mg/L. Okra seeds had an optimum dosage of 35 mg/L with a turbidity and TDS removal of 88.83% and 95.25% respectively. Aloe Vera had an optimum dosage of 40 mg/L with a turbidity and TDS removal of 74.25% and 95.40% respectively. For Cactus opuntia it was 50 mg/L obtaining turbidity and TDS removal of 74.66% and 95% respectively. The best blend of the bio coagulants had a ratio of (0.17, 0.17, and 0.67) for Aloe vera, Cactus opuntia and Okra seeds respectively. At a dosage of 40 mg/L the turbidity removal was 83.92% and TDS removal was 95.12%. The results indicated that blending the plant-based coagulants had a positive synergistic effect.
Graphical Abstract
Exploring torque characteristics of an integrated ultra conducting magnetic coupling incorporating axial magnetic field through magnetic equivalent circuit modelling
Authors: Ombolo Djomo Patrick 
Published: July 2024

AbstractUltra-conductors are a recent class of materials that display superconducting attributes at room temperature and even at higher temperatures. In this paper, we introduce a novel hybrid ultra-conducting coupling (NHUC) where the secondary component includes copper and an ultra-conductor (considered as a room temperature superconductor in much research). We suggest a model based on magnetic equivalent circuit (MEC) to evaluate the distribution of magnetic fields and characteristics related to torque. The 3D model accounts for boundary impacts during mating, and formulation for magnetic flux and torque are derived using Kirchhoff’s and Ampere’s loop laws, respectively. A 3D finite element (FEM) model is constructed, and simulations are performed using iodine-doped double-walled carbon nanotube (IDWCT) as the ultra-conductor for a wider operating range. At a high slip speed of 1200 rpm, a maximum torque of 309 Nm and stable torque of 113 Nm are observed. Adjusting air gap thickness or permanent magnet dimensions results in torque variations. Additionally, due to carbon nanotube (CNT) characteristics, a reduction in losses from the Joule effect is noted. The maximum error between torque results from simulation and the suggested model is 7.68%, confirming accordance. Comparison alongside the slotted eddy current coupling (SEC) reveals that the torque of the NHUC exceeds that of the SEC, diminishing as the air gap widens.
New Views of Lunar Seismicity Brought by Analysis of Newly Discovered Moonquakes in Apollo Short‐Period Seismic Data
Authors: Onodera Keisuke 
Published: July 2024

AbstractIn the 1970s, two types of seismometers were installed on the nearside of the Moon. One type is called the Long‐Period (LP) seismometer, which is sensitive below 1.5 Hz. The other is called the Short‐Period (SP) seismometer, whose sensitivity is high around 2–10 Hz. So far, more than 13,000 seismic events have been identified through analyzing the LP data, which allowed us to investigate lunar seismicity and its internal structure. On the other hand, most of the SP data have remained unanalyzed because they include numerous artifacts. This fact leads to the hypotheses that (a) we have missed lots of high‐frequency seismic events and (b) lunar seismicity could be underestimated. To verify these ideas, I conducted an analysis of the SP data. In the analysis, I denoised the original SP data and performed the event detections by comparing the spectral features between the cataloged high‐frequency events (such as shallow moonquakes) and the continuous SP data. Eventually, I discovered 22,000 new seismic events, including thermal moonquakes, impact‐induced events, and shallow moonquakes. Among these, I focused on analyzing shallow moonquakes—tectonic‐related quakes. Consequently, it turned out that there were 2.6 times more tectonic events than considered before. Furthermore, additional detections of shallow moonquakes enabled me to see the regionality in seismicity. Comparing three landing sites (Apollo 14, 15, and 16), I found that the Apollo 15 site was more seismically active than others. These findings can change the conventional views of lunar seismicity.
An appearance quality classification method for Auricularia auricula based on deep learning
Authors: Li Yang , Hu Jiajun , Wu Haiyun , Wei Yong , Shan Huiyong , Song Xin , Hua Xiuping , Xu Wei , Jiang Yongcheng 
Published: July 2024

AbstractThe intelligent appearance quality classification method for Auricularia auricula is of great significance to promote this industry. This paper proposes an appearance quality classification method for Auricularia auricula based on the improved Faster Region-based Convolutional Neural Networks (improved Faster RCNN) framework. The original Faster RCNN is improved by establishing a multiscale feature fusion detection model to improve the accuracy and real-time performance of the model. The multiscale feature fusion detection model makes full use of shallow feature information to complete target detection. It fuses shallow features with rich detailed information with deep features rich in strong semantic information. Since the fusion algorithm directly uses the existing information of the feature extraction network, there is no additional calculation. The fused features contain more original detailed feature information. Therefore, the improved Faster RCNN can improve the final detection rate without sacrificing speed. By comparing with the original Faster RCNN model, the mean average precision (mAP) of the improved Faster RCNN is increased by 2.13%. The average precision (AP) of the first-level Auricularia auricula is almost unchanged at a high level. The AP of the second-level Auricularia auricula is increased by nearly 5%. And the third-level Auricularia auricula AP is increased by 1%. The improved Faster RCNN improves the frames per second from 6.81 of the original Faster RCNN to 13.5. Meanwhile, the influence of complex environment and image resolution on the Auricularia auricula detection is explored.
The South Atlantic Dipole via multichannel singular spectrum analysis
Authors: Manta Gaston , Bach Eviatar , Talento Stefanie , Barreiro Marcelo , Speich Sabrina , Ghil Michael 
Published: July 2024

AbstractThis study analyzes coupled atmosphere–ocean variability in the South Atlantic Ocean. To do so, we characterize the spatio-temporal variability of annual mean sea-surface temperature (SST) and sea-level pressure (SLP) using Multichannel Singular Spectrum Analysis (M-SSA). We applied M-SSA to ERA5 reanalysis data (1959–2022) of South Atlantic SST and SLP, both individually and jointly, and identified a nonlinear trend, as well as two climate oscillations. The leading oscillation, with a period of 13 years, consists of a basin-wide southwest–northeast dipole and is observed both in the individual variables and in the coupled analysis. This mode is reminiscent of the already known South Atlantic Dipole, and it is probably related to the Pacific Decadal Oscillation and to El Niño–Southern Oscillation in the Pacific Ocean. The second oscillation has a 5-year period and also displays a dipolar structure. The main difference between the spatial structure of the decadal, 13-year, and the interannual, 5-year mode is that, in the first one, the SST cold tongue region in the southeast Atlantic’s Cape Basin is included in the pole closer to the equator. Together, these two oscillatory modes, along with the trend, capture almost 40% of the total interannual variability of the SST and SLP fields, and of their co-variability. These results provide further insights into the spatio-temporal evolution of SST and SLP variability in the South Atlantic, in particular as it relates to the South Atlantic Dipole and its predictability.
Oil painting teaching design based on the mobile platform in higher art education
Authors: Yi Guodong 
Published: July 2024

AbstractTo improve the current oil painting teaching mode in Chinese universities, this study combines deep learning technology and artificial intelligence technology to explore oil painting teaching. Firstly, the research status of individualized education and related research on image classification based on brush features are analyzed. Secondly, based on a convolutional neural network, mathematical morphology, and support vector machine, the oil painting classification model is constructed, in which the extracted features include color and brush features. Moreover, based on artificial intelligence technology and individualized education theory, a personalized intelligent oil painting teaching framework is built. Finally, the performance of the intelligent oil painting classification model is evaluated, and the content of the personalized intelligent oil painting teaching framework is explained. The results show that the average classification accuracy of oil painting is 90.25% when only brush features are extracted. When only color features are extracted, the average classification accuracy is over 89%. When the two features are extracted, the average accuracy of the oil painting classification model reaches 94.03%. Iterative Dichotomiser3, decision tree C4.5, and support vector machines have an average classification accuracy of 82.24%, 83.57%, and 94.03%. The training speed of epochs data with size 50 is faster than that of epochs original data with size 100, but the accuracy is slightly decreased. The personalized oil painting teaching system helps students adjust their learning plans according to their conditions, avoid learning repetitive content, and ultimately improve students' learning efficiency. Compared with other studies, this study obtains a good oil painting classification model and a personalized oil painting education system that plays a positive role in oil painting teaching. This study has laid the foundation for the development of higher art education.
Energy harvesting from fuel cell bicycles for home DC grids using soft switched DC–DC converter
Authors: Ramesh S. , Elangovan D. 
Published: July 2024

AbstractFuel cell vehicles (FCVs) are gaining significance due to their potential to reduce greenhouse gas emissions and dependence on fossil fuels. Their efficient fuel cell cycle makes them ideal for last-mile transportation, offering zero emissions and longer range compared to battery electric vehicles. Additionally, the generation of electricity through fuel cell stacks is becoming increasingly popular, providing a clean energy source for various applications. This paper focuses on utilizing the energy from fuel cycle bicycles when it's not in use and feeding it into the home DC grid. To achieve this, a dual-phase DC to DC converter is proposed to boost stack voltage and integrate with the 24 V DC home grid system. The converter design is simulated using the PSIM platform and tested in a hardware-in-the-loop (HIL) environment with real-time simulation capabilities.
Spatially resolved imaging of human macular capillaries using adaptive optics-enhanced optical coherence tomography angiography
Authors: Bonnin S. , Gocho K. , Norberg N. , Gofas E. , Lejoyeux R. , Chaumette C. , Grieve K. , Couturier A. , Paques M. 
Published: July 2024

AbstractDocumenting the organization of the retinal capillaries is of importance to understand the visual consequences of vascular diseases which may differentially affect the microvascular layers. Here we detailed the spatial organization of the macular capillaries in ten healthy human subjects using a prototypic adaptive optics-enhanced optical coherence tomography angiography (AO-OCTA) system. Within the central 6° × 6°, the radial peripapillary capillaries and the superficial, intermediate and deep vascular plexuses (SVP, IVP and DVP, respectively) were consistently resolved. In 8 out of the 10 eyes, the capillary segments composing the perifoveal arcade (PFA) were perfused only by the SVP, while drainage of the PFA showed more variability, comprising a case in which the PFA was drained by the DVP. Around the center, a distinct central avascular zone could be documented for each layer in 7 of the 10 cases; in three eyes, the IVP and SVP merged tangentially around the center. In all eyes, the foveal avascular zone was larger in the DVP than in the SVP and IVP. In one eye with incomplete separation of the inner foveal layers, there was continuity of both the SVP and the IVP; a central avascular zone was only present in the DVP. The diversity of perfusion and drainage patterns supported a connectivity scheme combining parallel and serial organizations, the latter being the most commonly observed in perifoveal vessels. Our results thus help to further characterize the diversity of organization patterns of the macular capillaries and to robustly analyze the IVP, which will help to characterize early stages of microvascular diseases.
Photosymbiosis reduces the environmental stress response under a heat challenge in a facultatively symbiotic coral
Authors: Wuitchik D. M. , Aichelman H. E. , Atherton K. F. , Brown C. M. , Chen X. , DiRoberts L. , Pelose G. E. , Tramonte C. A. , Davies S. W. 
Published: July 2024

AbstractThe symbiosis between corals and dinoflagellates of the family Symbiodiniaceae is sensitive to environmental stress. The oxidative bleaching hypothesis posits that extreme temperatures lead to accumulation of photobiont-derived reactive oxygen species ROS, which exacerbates the coral environmental stress response (ESR). To understand how photosymbiosis modulates coral ESRs, these responses must be explored in hosts in and out of symbiosis. We leveraged the facultatively symbiotic coral Astrangia poculata, which offers an opportunity to uncouple the ESR across its two symbiotic phenotypes (brown, white). Colonies of both symbiotic phenotypes were exposed to three temperature treatments for 15 days: (i) control (static 18 °C), (ii) heat challenge (increasing from 18 to 30 °C), and (iii) cold challenge (decreasing from 18 to 4 °C) after which host gene expression was profiled. Cold challenged corals elicited widespread differential expression, however, there were no differences between symbiotic phenotypes. In contrast, brown colonies exhibited greater gene expression plasticity under heat challenge, including enrichment of cell cycle pathways involved in controlling photobiont growth. While this plasticity was greater, the genes driving this plasticity were not associated with an amplified environmental stress response (ESR) and instead showed patterns of a dampened ESR under heat challenge. This provides nuance to the oxidative bleaching hypothesis and suggests that, at least during the early onset of bleaching, photobionts reduce the host’s ESR under elevated temperatures in A. poculata.
A study of impact of climate change on the U.S. stock market as exemplified by the NASDAQ 100 index constituents
Authors: Li Cunpu , Liu Yingjun , Pan Lishuo 
Published: July 2024

AbstractThis paper employs an innovative event study methodology to demonstrate the impact of climate change on the NASDAQ index from the unique perspective of extreme weather events. This is achieved through the application of the event study methodology to a total of 526 biological, climatic, geological, hydrological, and meteorological disasters of climate change occurring in the U.S. during the period of 2000–2019. The results of the study demonstrate that: ① it can be generally observed that the five dimensions of climate change have a significant impact on stock returns. ② Empirical evidence indicates that the impact of different climate change dimensions on the return rate of stocks from NASDAQ stocks varies. In contrast, the biological and hydrological dimensions have a significantly negative impact on the return rate of stocks from the NASDAQ index, while the climate dimension has a significantly positive impact on the return rate of stocks from the NASDAQ index. ③ From the perspective of time, the impact of the five dimensions of climate change on the stock yield exhibits certain non-linear characteristics. This can be observed in the phenomenon of shock reversal, which occurs before and after the event.