bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transport of non-classical light mediated by topological domain walls in a SSH photonic lattice
Authors: Pérez Gabriel O’Ryan , Dueñas Joaquín Medina , Guzmán-Silva Diego , Torres Luis E. F. Foa , Hermann-Avigliano Carla 
Published: May 2024

AbstractAdvancements in photonics technologies have significantly enhanced their capability to facilitate experiments involving quantum light, even at room temperature. Nevertheless, fully integrating photonic chips that include quantum light sources, effective manipulation and transport of light minimizing losses, and appropriate detection systems remains an ongoing challenge. Topological photonic systems have emerged as promising platforms to protect quantum light properties during propagation, beyond merely preserving light intensity. In this work, we delve into the dynamics of non-classical light traversing a Su-Schrieffer-Heeger photonic lattice with topological domain walls. Our focus centers on how topology influences the quantum properties of light as it moves across the array. By precisely adjusting the spacing between waveguides, we achieve dynamic repositioning and interaction of domain walls, facilitating effective beam-splitting operations. Our findings demonstrate high-fidelity transport of non-classical light across the lattice, replicating known results that are now safeguarded by the topology of the system. This protection is especially beneficial for quantum communication protocols with continuous variable states. Our study enhances the understanding of light dynamics in topological photonic systems and paves the way for high-fidelity, topology-protected quantum communication.
Machine learning-based diagnostic prediction of IgA nephropathy: model development and validation study
Authors: Noda Ryunosuke , Ichikawa Daisuke , Shibagaki Yugo 
Published: May 2024

AbstractIgA nephropathy progresses to kidney failure, making early detection important. However, definitive diagnosis depends on invasive kidney biopsy. This study aimed to develop non-invasive prediction models for IgA nephropathy using machine learning. We collected retrospective data on demographic characteristics, blood tests, and urine tests of the patients who underwent kidney biopsy. The dataset was divided into derivation and validation cohorts, with temporal validation. We employed five machine learning models—eXtreme Gradient Boosting (XGBoost), LightGBM, Random Forest, Artificial Neural Networks, and 1 Dimentional-Convolutional Neural Network (1D-CNN)—and logistic regression, evaluating performance via the area under the receiver operating characteristic curve (AUROC) and explored variable importance through SHapley Additive exPlanations method. The study included 1268 participants, with 353 (28%) diagnosed with IgA nephropathy. In the derivation cohort, LightGBM achieved the highest AUROC of 0.913 (95% CI 0.906–0.919), significantly higher than logistic regression, Artificial Neural Network, and 1D-CNN, not significantly different from XGBoost and Random Forest. In the validation cohort, XGBoost demonstrated the highest AUROC of 0.894 (95% CI 0.850–0.935), maintaining its robust performance. Key predictors identified were age, serum albumin, IgA/C3, and urine red blood cells, aligning with existing clinical insights. Machine learning can be a valuable non-invasive tool for IgA nephropathy.
Identification of genomic regions controlling spikelet degeneration under FRIZZLE PANICLE (FZP) defect genetic background in rice
Authors: Wang Sheng-Shan , Tsai Pei-Hua , Cheng Shu-Fang , Chen Rong-Kuen , Chen Kai-Yi 
Published: May 2024

AbstractThe FZP gene plays a critical role in the formation of lateral branches and spikelets in rice panicle architecture. This study investigates the qSBN7 allele, a hypomorphic variant of FZP, and its influence on panicle architectures in different genetic backgrounds. We evaluated two backcross inbred lines (BILs), BC5_TCS10sbn and BC3_TCS10sbn, each possessing the homozygous qSBN7 allele but demonstrating differing degrees of spikelet degeneration. Our analysis revealed that BC5_TCS10sbn had markedly low FZP expression, which corresponded with an increase in axillary branches and severe spikelet degeneration. Conversely, BC3_TCS10sbn exhibited significantly elevated FZP expression, leading to fewer secondary and tertiary branches, and consequently decreased spikelet degeneration. Compared to BC5_TCS10sbn, BC3_TCS10sbn carries three additional chromosomal substitution segments from its donor parent, IR65598-112-2. All three segments significantly enhance the expression of FZP and reduce the occurrence of tertiary branch and spikelet degeneration. These findings enhance our understanding of the mechanisms regulating FZP and aid rice breeding efforts.
A review of machine learning methods for cancer characterization from microbiome data
Authors: Teixeira Marco , Silva Francisco , Ferreira Rui M. , Pereira Tania , Figueiredo Ceu , Oliveira Hélder P. 
Published: May 2024

AbstractRecent studies have shown that the microbiome can impact cancer development, progression, and response to therapies suggesting microbiome-based approaches for cancer characterization. As cancer-related signatures are complex and implicate many taxa, their discovery often requires Machine Learning approaches. This review discusses Machine Learning methods for cancer characterization from microbiome data. It focuses on the implications of choices undertaken during sample collection, feature selection and pre-processing. It also discusses ML model selection, guiding how to choose an ML model, and model validation. Finally, it enumerates current limitations and how these may be surpassed. Proposed methods, often based on Random Forests, show promising results, however insufficient for widespread clinical usage. Studies often report conflicting results mainly due to ML models with poor generalizability. We expect that evaluating models with expanded, hold-out datasets, removing technical artifacts, exploring representations of the microbiome other than taxonomical profiles, leveraging advances in deep learning, and developing ML models better adapted to the characteristics of microbiome data will improve the performance and generalizability of models and enable their usage in the clinic.
Mitigating gut microbial degradation of levodopa and enhancing brain dopamine: Implications in Parkinson’s disease
Authors: Cheng Gang , Hardy Micael , Hillard Cecilia J. , Feix Jimmy B. , Kalyanaraman Balaraman 
Published: May 2024

AbstractParkinson’s disease is managed using levodopa; however, as Parkinson’s disease progresses, patients require increased doses of levodopa, which can cause undesirable side effects. Additionally, the oral bioavailability of levodopa decreases in Parkinson’s disease patients due to the increased metabolism of levodopa to dopamine by gut bacteria, Enterococcus faecalis, resulting in decreased neuronal uptake and dopamine formation. Parkinson’s disease patients have varying levels of these bacteria. Thus, decreasing bacterial metabolism is a promising therapeutic approach to enhance the bioavailability of levodopa in the brain. In this work, we show that Mito-ortho-HNK, formed by modification of a naturally occurring molecule, honokiol, conjugated to a triphenylphosphonium moiety, mitigates the metabolism of levodopa—alone or combined with carbidopa—to dopamine. Mito-ortho-HNK suppresses the growth of E. faecalis, decreases dopamine levels in the gut, and increases dopamine levels in the brain. Mitigating the gut bacterial metabolism of levodopa as shown here could enhance its efficacy.
SGLT2 inhibition eliminates senescent cells and alleviates pathological aging
Authors: Katsuumi Goro , Shimizu Ippei , Suda Masayoshi , Yoshida Yohko , Furihata Takaaki , Joki Yusuke , Hsiao Chieh-Lun , Jiaqi Liang , Fujiki Shinya , Abe Manabu , Sugimoto Masataka , Soga Tomoyoshi , Minamino Tohru 
Published: May 2024

AbstractIt has been reported that accumulation of senescent cells in various tissues contributes to pathological aging and that elimination of senescent cells (senolysis) improves age-associated pathologies. Here, we demonstrate that inhibition of sodium–glucose co-transporter 2 (SGLT2) enhances clearance of senescent cells, thereby ameliorating age-associated phenotypic changes. In a mouse model of dietary obesity, short-term treatment with the SGLT2 inhibitor canagliflozin reduced the senescence load in visceral adipose tissue and improved adipose tissue inflammation and metabolic dysfunction, but normalization of plasma glucose by insulin treatment had no effect on senescent cells. Canagliflozin extended the lifespan of mice with premature aging even when treatment was started in middle age. Metabolomic analyses revealed that short-term treatment with canagliflozin upregulated 5-aminoimidazole-4-carboxamide-1-β-d-ribofuranoside, enhancing immune-mediated clearance of senescent cells by downregulating expression of programmed cell death-ligand 1. These findings suggest that inhibition of SGLT2 has an indirect senolytic effect by enhancing endogenous immunosurveillance of senescent cells.
Retention Rate of Free Pericardial Fat Grafts after Bronchial Stump Coverage
Authors: Karasaki Takahiro , Fujimori Sakashi , Suzuki Souichiro , Kikunaga Shinichiro 
Published: May 2024

AbstractThe postoperative course of the graft tissue after bronchial stump coverage remains unclear. We retrospectively analyzed 44 patients who underwent anatomical lung resection followed by bronchial stump coverage using free pericardial fat grafts. All patients underwent minimally invasive video-assisted thoracoscopic surgery. Computed tomography scans showed a graft retention rate of 100% on 60 days after surgery, 61% on 180 days, and plateauing at around 20% after 1 year. Free pericardial fat grafts, harvested minimally invasively, demonstrated a promising retention rate after surgery, making them a suitable option for patients with a high risk of bronchopleural fistula.
Long-Term Outcomes of Endovascular Repair of Thoracic Aortic Aneurysms
Authors: Gorton Andrew J. , Keshavamurthy Suresh , Saha Sibu P. 
Published: May 2024

AbstractThe thoracic aorta is a dynamic structure composed of the aortic root, ascending aorta, aortic arch, and descending aorta. It is subject to the pressure and volume of the cardiac cycle and susceptible to atherosclerotic and aneurysmal changes. With these changes, the risk for acute aortic syndromes increases, thus creating the impetus for earlier interventions. The previous standard of open surgical repair has undergone a transition in recent years toward endovascular repair being favored in the descending and abdominal aortas with ongoing investigation into approaches for the ascending and aortic arch. These therapies have been shown to improve early mortality and morbidity outcomes with the caveat of more interventions compared with open surgery. We undertook this review to analyze the current data available regarding long-term outcomes in patients undergoing endovascular repair for thoracic aortic disease. The data support long-term benefit of endovascular repair for thoracic aortic disease. The primary indications identified for reintervention are endoleak and further aneurysmal degeneration. As the devices available for endovascular repair evolve, ongoing review of these outcomes will be necessary. It will also be important to trend the results as further techniques become available for endovascular repair of the ascending aorta and aortic arch.
The impact of self-determination theory: the moderating functions of social media (SM) use in education and affective learning engagement
Authors: Alturki Uthman , Aldraiweesh Ahmed 
Published: May 2024

AbstractThis study attempts to explore the relationship between the two mediator variables effective learning engagement and educational social media (SM) usage and the study’s outcome measures, which include student satisfaction and learning performance. The distribution of a self-determination theory questionnaire with external factors to 293 university students served as the primary data collection method. King Saud University used a poll to personally collect data. Partial least squares structural equation modeling was then used to examine the data and assess the model in Smart-PLS. Students’ academic success and contentment at colleges and universities seem to be positively correlated, and their active involvement in learning activities and educational use of SM. It was shown that important factors influencing affective learning participation and the instructional use of SM for teaching and learning include perceived competence, perceived autonomy, perceived relatedness, information sharing, and collaborative learning environments. It was discovered that these connections were important. The self-determination theory provided confirmation that this model is appropriate for fostering students’ feelings of competence, autonomy, and relatedness in order to increase their affective learning involvement. This, in turn, improves students’ satisfaction and achievement in higher education.
Evaluating aliphatic CF, CF2, and CF3 groups as vibrational Stark effect reporters
Authors: Cruz R. , Ataka K. , Heberle J. , Kozuch J. 
Published: May 2024

Given the extensive use of fluorination in molecular design, it is imperative to understand the solvation properties of fluorinated compounds and the impact of the C–F bond on electrostatic interactions. Vibrational spectroscopy can provide direct insights into these interactions by using the C–F bond stretching [v(C–F)] as an electric field probe through the vibrational Stark effect (VSE). In this work, we explore the VSE of the three basic patterns of aliphatic fluorination, i.e., mono-, di-, and trifluorination in CF, CF2, and CF3 groups, respectively, and compare their response to the well-studied aromatic v(C–F). Magnitudes (i.e., Stark tuning rates) and orientations of the difference dipole vectors of the v(C–F)-containing normal modes were determined using density functional theory and a molecular dynamics (MD)-assisted solvatochromic analysis of model compounds in solvents of varying polarity. We obtain Stark tuning rates of 0.2–0.8 cm−1/(MV/cm), with smallest and largest electric field sensitivities for CFaliphatic and CF3,aliphatic, respectively. While average electric fields of solvation were oriented along the main symmetry axis of the CFn, and thus along its static dipole, the Stark tuning rate vectors were tilted by up to 87° potentially enabling to map electrostatics in multiple dimensions. We discuss the influence of conformational heterogeneity on spectral shifts and point out the importance of multipolar and/or polarizable MD force fields to describe the electrostatics of fluorinated molecules. The implications of this work are of direct relevance for studies of fluorinated molecules as found in pharmaceuticals, fluorinated peptides, and proteins.
The semantic extension of Korean ideophones in newspapers headlines
Authors: Park Ji-Yeon 
Published: May 2024

Abstract
This paper explores the semantic features of Korean ideophones in newspaper headlines. This paper argues that (i)
there is a strong relationship between the language-specific sound symbolic meanings – dark and light vowel polarity and the
meanings of ideophones in newspaper headlines and event descriptions; (ii) ideophones are much more common in articles about the
financial issues; (iii) ideophones which exhibit vowel alternation go through different semantic extension routes to those of
other ideophones. The findings of the paper suggest that Korean ideophones have been lexically highly conventionalized and
integrated into the language system.
Manufacturing and measurement of CMOS-MEMS-based micro thermoelectric generators with long-length thermocouples
Authors: Dai Zhi-Xuan , Chen Chun-Yu , Chiu Bo-Chun , Lee Chi-Yuan 
Published: May 2024

Abstract
The study explores the fabrication and evaluation of a micro thermoelectric generator (MTG) with long-length thermocouples (TCs) through the utilization of a commercial complementary metal oxide semiconductor process. The MTG consists of 23 TCs, and its performance is intricately linked to the temperature difference (T
diff) between the cold and hot sides of these TCs. An increase in T
diff leads to higher output voltage and power for the MTG. To enhance T
diff, the TCs are designed to be 700 µm in length, and an innovative design has been implemented on the cold side of the TCs, creating a suspended structure to improve heat dissipation A post-process is essential for achieving this suspended TC structure. The results demonstrate that the TC structure is fully suspended and remains undamaged. The measured outcomes reveal an output voltage of 13.8 mV when the T
diff reaches 3.5 K. Under these conditions, the MTG exhibits a voltage factor of 2.76 mV mm−2K−1. Furthermore, at a T
diff of 3.5 K, the maximum output power reaches 2.1 nW. The MTG demonstrates a power factor of 0.12 nW mm−2 K−2.
First principles prediction of novel quantum topological insulator state in two-dimensional XMg2Bi2 (X=Eu/Yb)
Authors: Choudhury Amarjyoti , Maitra T 
Published: May 2024

Abstract
Topological insulator (TIs), a novel quantum state of materials, has a lot of significance in the development of low-power electronic equipments as the conducting edge states display exceptional endurance against back-scattering. The absence of suitable materials with high fabrication feasibility and significant nontrivial bandgap, is now the biggest hurdle in their potential applications in devices. Here, we illustrate using first principles density functional calculations that the quintuplet layers of EuMg2Bi2 and YbMg2Bi2 crystals are potential two-dimensional TIs with a sizeable nontrivial gaps of 72 meV and 147 meV respectively. Dynamical stability of these quintuplet layers of EuMg2Bi2 and YbMg2Bi2 is confirmed by our phonon calculations. The weakly coupled layered structure of parent compounds makes it possible for simple exfoliation from a three-dimensional structure. We observed gapless edge states inside the bulk band gap in both the systems which indicate their TI nature. Further, we observed the anomalous and spin Hall conductivities to be quantized in two dimensional EuMg2Bi2 and YbMg2Bi2 respectively. Our findings predict two viable candidate materials as two dimensional quantum TIs which can be explored by future experimental investigations and possible applications of quantized spin and anomalous Hall conductance in spintronics.
Analysis of significant risk factors for sand accumulation on desert expressways
Authors: Wang Fang , Liu Shixiao , Sun Liyi , Huang Siping , Zhu Hao , Zou Honghao , Li Guorui 
Published: May 2024

Abstract
Expressways in desert areas are prone to sand lifting and accumulation. This study aims to explore the impact of various risk factors on sand accumulation on road surfaces. Initially, the study identifies the causes of these risks through on-site investigation. Subsequently, using Fluent numerical simulation, it examines how different wind speeds, wind directions, route angles, embankment heights, embankment widths, embankment slope ratios, and central median layouts affect sand accumulation. Finally, based on simulation results and sand accumulation data from the Uma Expressway’s desert section, the study evaluates the importance of these factors using ordered logistic regression analysis and proposes strategic recommendations. The findings indicate that the degree of sand accumulation increases with higher wind speeds, more significant embankment heights, and variations in wind direction, route angle, and embankment width, as well as the configuration of the central median. Wind speed and embankment height are identified as the main factors influencing sand accumulation. Based on the risk assessment, the study suggests a four-point preventive strategy: (i) implementing wind speed management measures; (ii) optimizing embankment design; (iii) developing sand prevention strategies for the central median; and (iv) adjusting the alignment of the road relative to the wind direction.
Deterministic Ansätze for the measurement-based variational quantum eigensolver
Authors: Schroeder Anna , Heller Matthias , Gachechiladze Mariami 
Published: May 2024

Abstract
Measurement-based quantum computing (MBQC) is a promising approach to reducing circuit depth in noisy intermediate-scale quantum algorithms such as the variational quantum eigensolver (VQE). Unlike gate-based computing, MBQC employs local measurements on a preprepared resource state, offering a trade-off between circuit depth and qubit count. Ensuring determinism is crucial to MBQC, particularly in the VQE context, as a lack of flow in measurement patterns leads to evaluating the cost function at irrelevant locations. This study introduces MBVQE-ansätze that respect determinism and resemble the widely used problem-agnostic hardware-efficient VQE ansatz. We evaluate our approach using ideal simulations on the Schwinger Hamiltonian and XY-model and perform experiments on IBM hardware with an adaptive measurement capability. In our use case, we find that ensuring determinism works better via postselection than by adaptive measurements at the expense of increased sampling cost. Additionally, we propose an efficient MBQC-inspired method to prepare the resource state, specifically the cluster state, on hardware with heavy-hex connectivity, requiring a single measurement round, and implement this scheme on quantum computers with 27 and 127 qubits. We observe notable improvements for larger cluster states, although direct gate-based implementation achieves higher fidelity for smaller instances.
Observation of a stationary double transport barrier in KSTAR
Authors: Lee M.W. , Hahn S.-H. , Kim D. , Kang J. , Ko W.H. , Jang J. , Lee W. , Sung C. 
Published: May 2024

Abstract
We have observed a stationary high confinement regime with a double transport barrier (DTB), including both internal and edge transport barriers (ITB and ETB) but without edge-localized modes (ELMs), in KSTAR. The ELM-free DTB phase has high thermal confinement comparable to typical H-mode operation in KSTAR. We investigated the characteristics of the DTB phase through various analyses. Transport analysis shows a reduction of ion heat diffusivity to near neoclassical level after the transition from the ELMy H-mode phase to the DTB phase. This result supports the formation of an ion ITB during the DTB phase. Furthermore, we observed that the DTB phase had an edge thermal transport barrier in the ion temperature profile, comparable to that of the H-mode, without a particle transport barrier at the edge. Peeling-ballooning stability analysis indicates that a lower pressure gradient due to density decrease in the DTB phase is mainly responsible for the ELM-free operation. Linear gyrokinetic analysis shows that the real frequency of the most unstable mode in the core region (

ρ

tor

= 0.32–0.47) is in the ion diamagnetic direction at both H-mode and DTB phases. At the DTB phase, the linear growth rate inside the ITB is reduced by 50% compared to the ITB foot, while the reduction is not shown at the H-mode phase. Further investigation including nonlinear effects will be needed to better understand the unique operation mode, which can contribute to applying the physical mechanism to fusion reactors in the future.