bluuebunny/crossref_metadata_2025_split huggingface dataset:
Galois points and Cremona transformations
Authors: Abouelsaad Ahmed 
Published: April 2024

AbstractIn this article, we study Galois points of plane curves and the extension of the corresponding Galois group to
$\mathrm{Bir}(\mathbb{P}^2)$
. We prove that if the Galois group has order at most
$3$
, it always extends to a subgroup of the Jonquières group associated with the point
$P$
. Conversely, with a degree of at least
$4$
, we prove that it is false. We provide an example of a Galois extension whose Galois group is extendable to Cremona transformations but not to a group of de Jonquières maps with respect to
$P$
. In addition, we also give an example of a Galois extension whose Galois group cannot be extended to Cremona transformations.
Variance Decomposition and Cryptocurrency Return Prediction
Authors: Lee Suzanne S. , Wang Minho 
Published: April 2024

Abstract
This article examines how realized variances predict cryptocurrency returns in the cross section using intraday data. We find that cryptocurrencies with higher variances exhibit lower returns in subsequent weeks. Decomposing total variances into signed jump and jump-robust variances reveals that the negative predictability is attributable to positive jump and jump-robust variances. The negative pricing effect is more pronounced for smaller cryptocurrencies with lower prices, less liquidity, more retail trading activities, and more positive sentiment. Our results suggest that cryptocurrency markets are unique because retail investors and preferences for lottery-like payoffs play important roles in the partial variance effects.
Confirmation of hilsa shad (Tenualosa ilisha) in Vietnamese waters: a morphological and genetic analysis
Authors: Giap Vanthu , Rahman Md Rashedur , Li Chenhong 
Published: April 2024

Abstract
One specimen of tropical shad was caught from the Giang Thanh River, Kien Giang province, Vietnam in a survey on 16 October 2022. We identified the specimen as the hilsa shad, Tenualosa ilisha Hamilton, 1822 using morphological analysis, and further validated by its cytochrome oxidase subunit I (COI) sequence. The specimen was 418 mm long, 1428 g in weight, with a head length of 29.0% and pectoral fin length of 31.1% of its standard length. Notably, the presence of 34 scutes, a higher gill raker count and a caudal fin length within the moderate range for Tenualosa species distinguished it from T. macrura, T. toli and T. reevesii. The COI sequence of the sample matched closely to the T. ilisha. The results confirm that T. ilisha still endures Vietnamese water, where it was thought to be extinct. Climate change and Indo-Pacific Ocean currents may introduce expansion of distribution area of the T. ilisha. Further studies on distribution of the T. ilisha and other Tenualosa species and their dynamics are needed.
How is the path produced and sustained? Path-dependent college education expansion and underlying liberal rule in Korea
Authors: Jang Eunjeong 
Published: April 2024

AbstractThe conventional policy analyses with a path-dependent framework are featured by sequential causation composed of analytically two distinct phases: path production that occurs through a significant policy change at critical junctures and the subsequent path reproduction. This paper explores one policy area where the two-phase framework falls short in explaining path-making and maintenance – college education expansion in Korea. We argue that the shortcomings of the two-phase model can potentially be overcome by incorporating the underlying rule of the countries into the model. We identify the underlying rule relying on Esping-Andersen’s welfare regimes to highlight the political underpinnings of the countries. We show that the underlying liberal rule is a fundamental causal force behind the production and reproduction of college education expansion in Korea, using qualitative comparative analysis. Our framework based on the underlying rule provides a richer understanding of path dependency.
GENERALISED QUADRATIC FORMS OVER TOTALLY REAL NUMBER FIELDS
Authors: Browning Tim , Pierce Lillian B. , Schindler Damaris 
Published: April 2024

AbstractWe introduce a new class of generalised quadratic forms over totally real number fields, which is rich enough to capture the arithmetic of arbitrary systems of quadrics over the rational numbers. We explore this connection through a version of the Hardy–Littlewood circle method over number fields.
Multiband circularly-polarized stacked elliptical patch antenna with eye-shaped slot for GNSS applications
Authors: Abdalrazik Ahmad , Gomaa Ahmed , Afifi Asmaa 
Published: April 2024

AbstractThis paper introduces a tri-band stacked elliptical patch antenna featuring a right-handed circular polarized, designed to operate at the L2, L5, and L1 Global Navigation Satellite System bands. Initially, an elliptic patch is constructed and fed by a probe feed to generate TM110 and TM210 modes at resonance frequencies calculated using Mathieu functions. The probe position is precisely adjusted to excite the quasi-orthogonal mode of TM110 to generate circularly polarized (CP) waves at the L2 and L5 bands. Subsequently, an eye-shaped aperture is engraved into the elliptical patch to enhance the axial ratio (AR) beamwidth in the L2 and L5 bands and stimulate the orthogonal mode of TM210 to produce CP waves at the L1 band. Lastly, a stacked partially elliptical parasitic element is placed beneath the upper slotted elliptical patch to enhance the orthogonality of TM210 surface current versions and thus improve the AR beamwidth at the L1 band. The proposed antenna shows low reflection coefficient values at 1.12–1.33 (L2/L5), and 1.5–1.66 GHz (L1). The AR beamwidths are 133/213∘, 167/163∘, and 36/103∘ at two orthogonal cutplanes at L5, L2, and L1 bands, respectively. The antenna also has decent gains of 6–6.9 dBic across the three bands.
Permanence and Liability: Legal Considerations on the Integration of Carbon Dioxide Removal into the EU Emissions Trading System
Authors: Schuett Lukas 
Published: April 2024

AbstractThis article examines how carbon dioxide (CO2) removal credits can be integrated into the European Union (EU) Emissions Trading System (ETS), focusing on questions of permanence and climate liability. It identifies challenges within the integration process and analyzes approaches from practice and literature to cultivate learning. These approaches apply different strategies to address the issue of permanence, including temporary credit issuance, granting credits once a certain number of carbon tonne-years have been accumulated, or issuing credits at the beginning of the project period and relying on liability instead. Drawing from the findings of this research, the article presents legal considerations that may inform a proposal for an EU legislative act on the integration of carbon removal credits into the EU ETS. It suggests that only credits issued for permanent CO2 removal should be integrated to ensure the environmental integrity of the system. Furthermore, the liability of the project operator should transfer to the Member State under certain conditions to make liability risks more predictable.
Thermal and Physical Properties of Barrovian Metamorphic Sequence Rocks in the Ailao Shan‐Red River Shear Zone, and Implications for Crustal Channel Flow
Authors: Ji Lei , Liu Fulai , Palin Richard , Wang Fang , Sun Zaibo 
Published: April 2024

AbstractThe collisional history between Greater India and the Eurasian plate has been well constrained by the study of exhumed Barrovian metamorphic sequence (BMS) rocks in the Himalayan Range. However, in the southeastern Tibetan Plateau, the collisional records have been obscured by intense, regional‐scale strike‐slip overprinting and recrystallization. Here, in BMS rocks from the Ailao Shan–Red River shear zone (ARSZ), we report the first discovery of a >250 km long, high‐pressure (high‐P) granulite belt (>1.0 GPa), identified by the presence of relict kyanite and associated decompression reaction textures. Petrological phase equilibrium modeling showed that exposed micaschists in the region represent exhumed middle crust (20–25 km, 600–670°C), while the high‐P granulite rocks are remnants of thickened lower crust (45–55 km, 800–850°C). This indicates that the northeast edge of the ARSZ experienced an additional ∼25 km of uplift and exhumation compared to the southwest side, facilitated by brittle thrusting/imbrication along the Ailao Shan fault (micaschists) and ductile extrusion along the Red River fault (granulite). Geochronological study shows that the upper portion of the BMS preserves older metamorphic ages (52–34 Ma) than the lower portion (32–29 Ma), which was attributed to spatial variation in cooling rates. Using calculated P–T–t–d paths, we also examined variation in density and seismic wave speeds for BMS in the ARSZ. Our data correlate with fieldwork conducted elsewhere within the Himalayan Range indicating that the kyanite to sillimanite transition zone may serve as a “cap” for the horizontal migration of melt within the lower crust.
Research progress of post-acute sequelae after SARS-CoV-2 infection
Authors: Jiao Taiwei , Huang Yuling , Sun Haiyan , Yang Lina 
Published: April 2024

AbstractSARS-CoV-2 has spread rapidly worldwide and infected hundreds of millions of people worldwide. With the increasing number of COVID-19 patients discharged from hospitals, the emergence of its associated complications, sequelae, has become a new global health crisis secondary to acute infection. For the time being, such complications and sequelae are collectively called “Post-acute sequelae after SARS-CoV-2 infection (PASC)”, also referred to as “long COVID” syndrome. Similar to the acute infection period of COVID-19, there is also heterogeneity in PASC. This article reviews the various long-term complications and sequelae observed in multiple organ systems caused by COVID-19, pathophysiological mechanisms, diagnosis, and treatment of PASC, aiming to raise awareness of PASC and optimize management strategies.
Nonlinearity-induced topological phase transition characterized by the nonlinear Chern number
Authors: Sone Kazuki , Ezawa Motohiko , Ashida Yuto , Yoshioka Nobuyuki , Sagawa Takahiro 
Published: April 2024

AbstractAs first demonstrated by the characterization of the quantum Hall effect by the Chern number, topology provides a guiding principle to realize the robust properties of condensed-matter systems immune to the existence of disorder. The bulk–boundary correspondence guarantees the emergence of gapless boundary modes in a topological system whose bulk exhibits non-zero topological invariants. Although some recent studies have suggested a possible extension of the notion of topology to nonlinear systems, the nonlinear counterpart of a topological invariant has not yet been understood. Here we propose a nonlinear extension of the Chern number based on the nonlinear eigenvalue problems in two-dimensional systems and show the existence of bulk–boundary correspondence beyond the weakly nonlinear regime. Specifically, we find nonlinearity-induced topological phase transitions, in which the existence of topological edge modes depends on the amplitude of oscillatory modes. We propose and analyse a minimal model of a nonlinear Chern insulator whose exact bulk solutions are analytically obtained. The model exhibits the amplitude dependence of the nonlinear Chern number, for which we confirm the nonlinear extension of the bulk–boundary correspondence. Thus, our result reveals the existence of genuinely nonlinear topological phases that are adiabatically disconnected from the linear regime.
An RNA-hydrolyzing recombinant minibody prevents both influenza A virus and coronavirus in co-infection models
Authors: Luong Quynh Xuan Thi , Hoang Phuong Thi , Lee Yongjun , Ayun Ramadhani Qurrota , Na Kyungho , Park Seonhyeon , Lin Chengmin , Ho Phuong Thi , Lee Taek-Kyun , Lee Sukchan 
Published: April 2024

AbstractWith the lifting of COVID-19 non-pharmaceutical interventions, the resurgence of common viral respiratory infections was recorded in several countries worldwide. It facilitates viral co-infection, further burdens the already over-stretched healthcare systems. Racing to find co-infection-associated efficacy therapeutic agents need to be rapidly established. However, it has encountered numerous challenges that necessitate careful investigation. Here, we introduce a potential recombinant minibody-associated treatment, 3D8 single chain variable fragment (scFv), which has been developed as a broad-spectrum antiviral drug that acts via its nucleic acid catalytic and cell penetration abilities. In this research, we demonstrated that 3D8 scFv exerted antiviral activity simultaneously against both influenza A viruses (IAVs) and coronaviruses in three established co-infection models comprising two types of coronaviruses [beta coronavirus—human coronavirus OC43 (hCoV-OC43) and alpha coronavirus—porcine epidemic diarrhea virus (PEDV)] in Vero E6 cells, two IAVs [A/Puerto Rico/8/1934 H1N1 (H1N1/PR8) and A/X-31 (H3N2/X-31)] in MDCK cells, and a combination of coronavirus and IAV (hCoV-OC43 and adapted-H1N1) in Vero E6 cells by a statistically significant reduction in viral gene expression, proteins level, and approximately around 85%, 65%, and 80% of the progeny of ‘hCoV-OC43–PEDV’, ‘H1N1/PR8–H3N2/X-31’, and ‘hCoV-OC43–adapted-H1N1’, respectively, were decimated in the presence of 3D8 scFv. Taken together, we propose that 3D8 scFv is a promising broad-spectrum drug for treatment against RNA viruses in co-infection.
Predictive modeling for breast cancer classification in the context of Bangladeshi patients by use of machine learning approach with explainable AI
Authors: Islam Taminul , Sheakh Md. Alif , Tahosin Mst. Sazia , Hena Most. Hasna , Akash Shopnil , Bin Jardan Yousef A. , FentahunWondmie Gezahign , Nafidi Hiba-Allah , Bourhia Mohammed 
Published: April 2024

AbstractBreast cancer has rapidly increased in prevalence in recent years, making it one of the leading causes of mortality worldwide. Among all cancers, it is by far the most common. Diagnosing this illness manually requires significant time and expertise. Since detecting breast cancer is a time-consuming process, preventing its further spread can be aided by creating machine-based forecasts. Machine learning and Explainable AI are crucial in classification as they not only provide accurate predictions but also offer insights into how the model arrives at its decisions, aiding in the understanding and trustworthiness of the classification results. In this study, we evaluate and compare the classification accuracy, precision, recall, and F1 scores of five different machine learning methods using a primary dataset (500 patients from Dhaka Medical College Hospital). Five different supervised machine learning techniques, including decision tree, random forest, logistic regression, naive bayes, and XGBoost, have been used to achieve optimal results on our dataset. Additionally, this study applied SHAP analysis to the XGBoost model to interpret the model’s predictions and understand the impact of each feature on the model’s output. We compared the accuracy with which several algorithms classified the data, as well as contrasted with other literature in this field. After final evaluation, this study found that XGBoost achieved the best model accuracy, which is 97%.
On the reproducibility of electron-beam lithographic fabrication of photonic nanostructures
Authors: Sahoo Pankaj K. , Coates Eve , Silver Callum D. , Li Kezheng , Krauss Thomas F. 
Published: April 2024

AbstractPhotonic nanostructures such as gratings and ring resonators have become ubiquitous building blocks in Photonics. For example, they are used in filters, they resonantly enhance signals and act as grating couplers. Much research effort is invested in using such structures to create novel functionalities, which often employs electron-beam lithography. An intrinsic issue in this field is the ability to accurately achieve a specific operating wavelength, especially for resonant systems, because nanometer-scale variations in feature size may easily detune the device. Here, we examine some of the key fabrication steps and show how to improve the reproducibility of fabricating wavelength scale photonic nanostructures. We use guided mode resonance grating sensors as our exemplar and find that the exposure condition and the development process significantly affect the consistency of the resonance wavelength, amplitude, and sensitivity of the sensor. By having careful control over these factors, we can achieve consistent performance for all the sensors studied, with less than 10% variation in their resonance behaviors. These investigations provide useful guidelines for fabricating nanostructures more reliably and to achieve a higher success rate in exploratory experiments.
Spindle component 25 predicts the prognosis and the immunotherapy response of cancers: a pan-cancer analysis
Authors: Xia Fengjuan , Yang Haixia , Wu Huangjian , Zhao Bo 
Published: April 2024

AbstractSpindle component 25 (SPC25) is one of the four proteins that make up the nuclear division cycle 80 (NDC80) complex, the other three components being Ndc80p, Nuf2p, and spindle component 24. Deregulation of the components of this complex can lead to uncontrolled proliferation and reduced apoptosis. However, the prognostic and immunotherapeutic value of SPC25 in pan-cancer remains unclear. Data from the UCSC Xena, TIMER2.0, and TCGA were analyzed to investigate the overall differential expression of SPC25 across multiple cancer types. The survival prognosis, clinical features, and genetic changes of SPC25 were also evaluated. Finally, the relationship between SPC25 and immunotherapy response was further explored through Gene Set Enrichment Analysis, tumor microenvironment, and immune cell infiltration. The transcription and protein expression of SPC25 were significantly increased in most cancer types and had prognostic value for the survival of certain cancer patients such as ACC, CESC, KIRC, KIRP, LIHC, LUAD, MESO, STAD, THYM, and UCEC. In some cancer types, SPC25 expression was also markedly correlated with the TMB, MSI, and clinical characteristics. Gene Set Enrichment Analysis showed that SPC25 was significantly associated with immune-related pathways. In addition, it was also confirmed that the expression level of SPC25 was strongly correlated with immune cell infiltration, immune checkpoint genes, immune regulatory genes, Ferroptosis-related genes, Cuproptosis-related genes, and lactate metabolism-related genes. This study comprehensively explored the potential value of SPC25 as a prognostic and immunotherapeutic marker for pan-cancer, providing new direction and evidence for cancer therapy.
Unveiling energy security in agriculture through vital indicators extraction and insights
Authors: Haghjoo Reihaneh , Choobchian Shahla , Abbasi Enayat 
Published: April 2024

AbstractDespite advancements in meeting various human needs, energy supply remains a top priority for all countries worldwide. The escalating energy consumption in the agricultural sector underscores the necessity to scrutinize its energy usage. Presently, there exists an absence of a precise tool for accurately measuring this consumption. Hence, this study aims to identify indicators for measuring energy security in agriculture, conducted in three phases: content analysis, indicator validation, and field investigation. In the content analysis phase, energy security indicators were extracted and grouped into four categories: accessibility, availability, utilization, and sustainability. Following this, a two-stage validation process led to the identification of 18 indicators for assessing energy security in agriculture. In the field phase, a tailored questionnaire was distributed to 160 randomly selected farmers. The findings revealed that the availability component held the highest rank in establishing energy security, with an average score of 3.31. However, the current status of the access component indicates a more unfavorable situation compared to other dimensions. Consequently, to achieve energy security in agriculture, particular emphasis should be placed on enhancing energy access. Key areas to address include reducing transportation costs and minimizing the use of chemical pesticides. This indicates a necessity for focused interventions aimed at improving both energy access and sustainability within the agricultural sector. These efforts would contribute to enhancing economic efficiency and promoting environmental conservation.
Energy big data abnormal cluster detection method based on redundant convolution codec
Authors: Ma Rui , Yan Zhenhua , Liu Jia , Kang Wenni , Zhu Dongge 
Published: April 2024

AbstractDue to the scattered distribution and poor clustering of abnormal clusters in energy big data, the ability to detect anomalies is poor. Therefore, a high-energy data anomaly clustering detection method based on redundant convolutional encoding is proposed. Quantitative analysis of the coupling characteristics of electrical thermal gas optical time series for multi energy users based on Copula function, and incorporating quantitative values into multi energy feature indicators to extract the energy consumption behavior characteristics of multi energy users. Utilize redundant convolutional codecs to recombine and structurally encode abnormal features of energy big data, and capture multi energy coupling time features using coupling time capsule layers. Then, coupling time features are synthesized through fully connected linear regression layers to generate anomalous clustering feature components, and the energy time series data is then transformed into feature values of the time series in three-dimensional space. Based on this, a comprehensive energy system and massive multi energy user energy big data anomaly clustering analysis are carried out to determine the optimal number of multi energy users. Then, based on linear layers, the electricity heat gas light load characteristic map of multi energy users is transformed into one-dimensional form, and an energy big data anomaly clustering detection model is constructed to complete anomaly detection. The simulation results show that the proposed method has excellent feature clustering performance, detection accuracy above 98.7%, fast convergence speed, and an error rate below 0.1, which has reliable application value.