bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying mosquito plant hosts from ingested nectar secondary metabolites
Authors: Cooper Amanda N. , Malmgren Louise , Hawkes Frances M. , Farrell Iain W. , Hien Domonbabele F. d. S. , Hopkins Richard J. , Lefèvre Thierry , Stevenson Philip C. 
Published: February 2025

Abstract
Establishing how plants contribute food and refuge to insects can be challenging for small species that are difficult to observe in their natural habitat, such as disease vectoring mosquitoes. Currently indirect methods of plant-host identification rely on DNA sequencing of ingested plant material but are often unsuccessful for small insects that feed primarily on plant sugars or have little contact with plant cells. Here we developed an innovative approach to determine species-specific phytophagy by detecting taxon-specific plant secondary metabolites (PSMs) in nectar. Two mosquito species were exposed to three PSMs, each present in the nectar of a known plant host, firstly from dosed sucrose solutions and secondly from flowers. Both experiments yielded high rates of PSM detection in mosquitoes using liquid chromatography-mass spectrometry (LC-MS). PSMs were consistently detected in mosquitoes up to 8 h post-ingestion. In experiments consisting of two or three plant species, multiple PSMs from different host plants could be detected. These positive results demonstrate that PSMs could be useful indicators of insect plant-hosts selection in the wild. With expanded knowledge of nectar-based PSMs across a landscape, improved knowledge of plant-host relationships could be achieved where direct observations in their natural habitat are lacking. Increasing understanding of vector insect ecology will have an important role in tackling vector-borne disease.
Flower fertilization optimization algorithm with application to adaptive controllers
Authors: Albedran Hazim , Alsamia Shaymaa , Koch Edina 
Published: February 2025

Abstract
This article presents the Flower Fertilization Optimization Algorithm (FFO), a novel bio-inspired optimization technique inspired by the natural fertilization process of flowering plants. The FFO emulates the behavior of pollen grains navigating through the search space to fertilize ovules, effectively balancing exploration and exploitation mechanisms. The developed FFO is theoretically introduced through the article and rigorously evaluated on a diverse set of 32 benchmark optimization problems, encompassing unimodal, multimodal, and fixed-dimension functions. The algorithm consistently outperformed 14 state-of-the-art metaheuristic algorithms, demonstrating superior accuracy, convergence speed, and robustness across all test cases. Also, exploitation, exploration, and parameter sensitivity analyses were performed to have a comprehensive understanding of the new algorithm. Additionally, FFO was applied to optimize the parameters of a Proportional-Integral-Derivative (PID) controller for magnetic train positioning—a complex and nonlinear control challenge. The FFO efficiently fine-tuned the PID gains, enhancing system stability, precise positioning, and improved response times. The successful implementation underscores the algorithm’s versatility and effectiveness in handling real-world engineering problems. The positive outcomes from extensive benchmarking and practical application show the FFO’s potential as a powerful optimization tool. In applying multi-objective PID controller parameter optimization, FFO demonstrated superior performance with a sum of mean errors of 190.563, outperforming particle swarm optimization (250.075) and dynamic differential annealed optimization (219.629). These results indicate FFO’s ability to achieve precise and reliable PID tuning for control systems. Furthermore, FFO achieved competitive results on large-scale optimization problems, demonstrating its scalability and robustness.
Feasibility and comparison of 3D modified rosette ultra-short echo time (PETALUTE) with conventional weighted acquisition in 31P-MRSI
Authors: Bozymski Brian , Shen Xin , Özen Ali , Chiew Mark , Thomas M. Albert , Clarke William T. , Sawiak Stephen , Dydak Ulrike , Emir Uzay 
Published: February 2025

Abstract
Phosphorus-31 magnetic resonance spectroscopic imaging (31P-MRSI) provides valuable non-invasivein vivoinformation on tissue metabolism but is burdened by poor sensitivity and prolonged scan duration. Ultra-short echo time (UTE) acquisitions minimize signal loss when probing signals with relatively short spin-spin relaxation time (T2), while also preventing first-order dephasing. Here, a three-dimensional (3D) UTE sequence with a rosette k-space trajectory (PETALUTE) is applied to 31P-MRSI at 3T. Conventional weighted MRSI employs highly regular Cartesian k-space sampling, susceptible to substantial artifacts when accelerated via undersampling. In contrast, this novel sequence’s “petal-like” pattern offers incoherent sampling more suitable for compressed sensing (CS). These results showcase the competitive performance of PETALUTE against conventional weighted 31P-MRSI with simulation, phantom, and in vivo leg muscle comparisons.
Advancing extrapolative predictions of material properties through learning to learn using extrapolative episodic training
Authors: Noda Kohei , Wakiuchi Araki , Hayashi Yoshihiro , Yoshida Ryo 
Published: February 2025

Abstract
Recent advancements in machine learning have demonstrated its potential to significantly accelerate the discovery of new materials. Central to this progress is the development of rapidly computable property predictors, which allow identifying novel materials with the desired properties from vast material spaces. However, the limited availability of data resources poses a significant challenge in data-driven material research, particularly hindering the exploration of innovative materials beyond the boundaries of existing data. Although machine-learning predictors are inherently interpolative, establishing a general methodology to create an extrapolative predictor remains a fundamental challenge. In this study, we leveraged the attention-based architecture of neural networks and a meta-learning algorithm to enhance extrapolative generalization capabilities. Meta-learners trained repeatedly on arbitrarily generated extrapolative tasks show outstanding generalization for unexplored material spaces. Through the tasks of predicting the physical properties of polymeric materials and hybrid organic–inorganic perovskites, we highlight the potential of such extrapolatively trained models, particularly their ability to rapidly adapt to unseen material domains in transfer-learning scenarios.
Fixed‐Time Fault‐Tolerant Dynamic Formation Control for Heterogeneous Multi‐Agent Systems With Communication Link Faults for Collaborative Wildfire Monitoring
Authors: Mawanza Joewell T. 
Published: February 2025

ABSTRACTThis paper addresses the problem of heterogeneous multi‐agent systems (HMAS), comprising multiple uncrewed ground vehicles (UGVs) and multiple uncrewed aerial vehicles (UAVs), collaboratively monitoring the wildfire in the presence of actuator faults and communication link faults during the fire monitoring mission. It presents a fixed‐time fault‐tolerant dynamic formation control scheme designed for HMAS, with the objective of monitoring either the circular or elliptical propagation of a wildfire. The paper adopts a fixed‐time extended state observer (FxESO) to estimate the multi‐source disturbances arising from external disturbances and actuator faults, ensuring fixed‐time convergence of the estimation errors of the FxESO. By utilizing the Lyapunov candidate theorem, the collaborative tracking errors will converge to zero in fixed time, regardless of the initial position, ensuring that all agents in HMAS monitor the dynamic wildfire perimeter. Comparative simulation results are presented to illustrate the effectiveness of the proposed control scheme.
A GGIW PMBM Smoother for Multiple Extended Object Tracking
Authors: Wang Wenhui , Xu Ye , Zhang Kejie , Sun YouPeng , Li Peng 
Published: February 2025

ABSTRACTPoisson multi‐Bernoulli mixture (PMBM) filtering is an effective method for multi‐extended target tracking. However, it has a low utilization of information from multiple time scans, leading to potential errors such as jumps and discontinuities in the target trajectories. To address this, propose a gamma Gaussian inverse Wishart PMBM filter that uses multiple time scans for smoothing. The results of continuous tracking are smoothed and corrected at regular intervals, resulting in more accurate tracking performance. Simulation results show that the proposed algorithm effectively reduces generalized optimal sub‐pattern assignment errors compared to the original PMBM filter.
Endometrium-Karzinom
Authors: Giagounidis Aristoteles 
Published: February 2025

Was ist neu?Erhebliche prognostische Verbesserungen für Früh- und Spätstadien der Endometrium-Karzinome zeichnen sich durch neue diagnostische und therapeutische Entwicklungen ab. So hat die Molekularpathologie sowohl die Klassifikation als auch die adjuvante und palliative Therapie dieser Tumoren revolutioniert. Neuerdings werden 4 Hauptgruppen unterschieden: POLE-mutierte Tumoren machen etwa 7% aller Karzinome aus und werden als „ultramutiert“ klassifiziert. Sie weisen eine exzellente Prognose auf. Mismatch-Repair-defiziente Tumoren (MMRd) sind mit etwa 25% häufig und gelten als „hypermutiert“. Sie sind ausgesprochen empfindlich gegen Immun-Checkpoint-Inhibitoren. Die größte Gruppe, Tumoren ohne spezifische molekulare Signatur (No specific molecular Profile, NSMP), sind prognostisch etwa den MMRd-Tumoren vergleichbar. Schließlich werden TP53-mutierte Endometrium-Karzinome unterschieden, die eine ungünstige Prognose aufweisen.Diese molekularpathologischen Grundlagen wurden kürzlich in die neue FIGO-Klassifikation von 2023 integriert. Dadurch verändert sich die adjuvante Therapie-Indikation erheblich: Während ohne Molekularpathologie früher 60% der POLE-mutierten Tumoren adjuvant radio/(chemo)therapiert wurden, bleiben sie heutzutage aufgrund ihrer exzellenten Prognose therapiefrei. FIGO 2023 erkennt u.a. auch neue günstige Subgruppen wie das synchrone Endometrium- und Ovarial-Karzinom an.Niedrigrisiko-Patientinnen benötigen keine adjuvante Therapie. Intermediärstadien (z.B. Stadium IIB) profitieren von adjuvanter Radiotherapie. Molekulare Marker entscheiden über den zusätzlichen Therapiebedarf: POLE-mutierte Tumoren werden therapiefrei belassen, G3-endometrioide Tumoren ohne TP53-Mutation erhalten meist nur eine adjuvante Strahlentherapie, während TP53-mutierte Tumoren intensiv radiochemotherapiert werden. Hochrisiko-Patientinnen (ab Stadium IIC) erhalten üblicherweise eine Kombination aus Radiochemotherapie, gefolgt von Chemotherapie, oder eine alleinige Chemotherapie.In der Therapie der fortgeschrittenen und metastasierten Stadien haben sowohl die Immun-Checkpoint-Inhibitoren als auch der PARP-Inhibitor Olaparib einen festen Stellenwert. Bei Patientinnen ohne Mismatch-Repair-Defizienz ist in der Erstlinien-Therapie der Immun-Checkpoint-Inhibitor Durvalumab plus Chemotherapie, gefolgt von Durvalumab und Olaparib, neu zugelassen. Bei Mismatch-Repair-defizienten Tumoren ist die vorgenannte Therapie ohne Olaparib – ebenso wie Dostarlimab und Carboplatin/Paclitaxel – als Erstlinien-Behandlung zugelassen. Aufgrund des mannigfachen immunologischen Nebenwirkungspotenzials und möglicher Interaktionen ist auch für den allgemeinmedizinisch und internistisch tätigen Hausarzt die Auseinandersetzung mit den neuen Therapieoptionen von Vorteil.
Telling stories matters
Authors: Allen Annie R. , Kim Jeong-Hee , Cho Jeasik 
Published: February 2025

Abstract
Narrative inquiry has emerged as a distinct and valuable research methodology within the human and
social sciences. This chapter introduces the concept and significance of narrative inquiry as a means to gain profound
insights into the diverse aspects of society, culture, and human actions. It begins by providing an overview of its
central tenets and elements as a research approach, delving into the ethical considerations and reflexive aspects
necessary to ensure the responsible and careful exploration of human experiences. The limitations of narrative inquiry
are also discussed, including the “Rashomon effect” and the challenges of conducting “backyard research.” The chapter
then examines the pedagogical implications of narrative inquiry, highlighting its potential to enrich educational
practices and enhance student engagement. Looking toward the future, “Posthuman Narrative Inquiry” is proposed as a
potential direction for the field. This chapter concludes by elucidating how stories shape realities and inspire a
deeper understanding of the human condition, inviting researchers and students alike to appreciate the power of
narratives and their transformative influence on the world.
Narrative inquiry in Applied Linguistics Research
Authors: Okada Hanako 
Published: February 2025

Abstract
Everyone loves a good story, including an increasing number of scholars in Applied Linguistics. A
well-told story holds our attention, conveys messages that might otherwise be lost in conventional research reports’
dense, dry prose, and connects readers to experiences in their own lives. Novice and experienced scholars alike who
are deeply interested in people’s lives may find that some Applied Linguistics literature misses what they are most
drawn to. Its distanced and impersonal stance somehow does not feel right when we wish to learn about people’s lives.
The fact that stories are so (deceptively) easy to tell and compelling to read and listen to thus holds great appeal,
particularly for novice scholars who are interested in doing research on people’s lives and experiences with
languages, such as learning and teaching second and foreign languages. However, they may not fully comprehend the
perils, as well as the pleasures, of conducting and writing up narrative inquiry. In this chapter, I begin with a
brief background and history of narrative inquiry in applied linguistics. I follow by addressing the pleasures and
perils, as well as the ethical concerns involved in conducting and writing narrative inquiry, with the goal of making
a case for the value of carefully done narrative inquiry in Applied Linguistics research.
Extracting gravitational wave signals from LISA data in the presence of artifacts
Authors: Castelli Eleonora , Baghi Quentin , Baker John , Slutsky jacob , Bobin Jérôme , Karnesis Nikolaos , Petiteau Antoine , Sauter Orion , Wass Peter J , Weber William J. 
Published: February 2025

Abstract
The Laser Interferometer Space Antenna (LISA) mission is being developed by ESA with NASA participation. As it has recently passed the Mission Adoption milestone, models of the instruments and noise performance are becoming more detailed, and likewise prototype data analyses must as well. Assumptions such as Gaussianity, stationarity, and data continuity are unrealistic, and must be replaced with physically motivated data simulations, and data analysis methods adapted to accommodate such likely imperfections. To this end, the LISA Data Challenges have produced datasets featuring time-varying and unequal constellation armlength, and measurement artifacts including data interruptions and instrumental transients. In this work, we assess the impact of these data artifacts on the inference of Galactic Binary and Massive Black Hole properties. Our analysis shows that the treatment of noise transients and gaps is necessary for effective parameter estimation, as they substantially corrupt the analysis if unmitigated. We find that straightforward mitigation techniques can significantly if imperfectly suppress artifacts. For the Galactic Binaries, mitigation of glitches was essentially total, while mitigations of the data gaps increased parameter uncertainty by approximately 10%. For the Massive Black Hole binaries the particularly pernicious glitches resulted in a 30% uncertainty increase after mitigations, while the data gaps can increase parameter uncertainty by up to several times. Critically, this underlines the importance of early detection of transient gravitational waves to ensure they are protected from planned data interruptions.
Direct sampling for recovering a clamped cavity from the biharmonic far-field data
Authors: Harris Isaac , Lee Heejin , Li Peijun 
Published: February 2025

Abstract
This paper concerns the inverse shape problem of recovering an unknown clamped cavity embedded in a thin infinite plate. The model problem is assumed to be governed by the two-dimensional biharmonic wave equation in the frequency domain. Based on the far-field data, a resolution analysis is conducted for cavity recovery via the direct sampling method. The Funk–Hecke integral identity is employed to analyze the performance of two imaging functions. Our analysis demonstrates that the same imaging functions commonly used for acoustic inverse shape problems are applicable to the biharmonic wave context. This work presents the first extension of direct sampling methods to biharmonic waves using far-field data. Numerical examples are provided to illustrate the effectiveness of these imaging functions in recovering a clamped cavity.
Effect of varying laser energy density at LaScO3/SrTiO3 interface
Authors: Nehra Simran , Shrivastava Shikha , Gangwar Sunil , Manral Pooja , Yadav C S , Malik V. K. , Dogra Anjana 
Published: February 2025

Abstract
The genesis of conductivity at the interface between two insulating perovskite oxides is the subject of rigorous investigation within the scientific community. The emergence of conductivity observed at the interface between insulating LaScO3 (LSO) and SrTiO3 (STO) is attributed to the phenomenon known as polar catastrophe. In this study, we fabricated LSO films on TiO2-terminated STO substrates using the pulsed laser deposition technique. The investigation revealed a correlation between the film resistance and the variation in laser energy density during the deposition process, emphasizing the influence of energy density modulation on the electronic properties of the films. Also, the effect of cation non-stoichiometry in LSO films on mobility is examined and compared with the previously documented LAO/STO and LVO/STO interfaces.
Magnetodielectric Properties in Two Dimensional Magnetic Insulators
Authors: Dey Koushik , Khatun Hasina , Ghosh Anudeepa , Das Soumik , Das Bikash , Datta Subhadeep 
Published: February 2025

Abstract
Magnetodielectric (MD) materials are important for their ability to spin-charge conversion, magnetic field control of electric polarization and vice versa. Among these, two-dimensional (2D) van der Waals (vdW) magnetic materials are of particular interest due to the presence of magnetic anisotropy (MA) originating from the interaction between the magnetic moments and the crystal field. Also, these materials indicate a high degree of stability in the long-range spin order and may be described using suitable spin Hamiltonians of the Heisenberg, XY, or Ising type. Recent reports have suggested effective interactions between magnetization and electric polarization in 2D magnets. However, MD coupling studies on layered magnetic materials are still few. This review covers the fundamentals of magnetodielectric coupling by explaining related key terms. It includes the necessary conditions for having this coupling and sheds light on the possible physical mechanisms behind this coupling starting from phenomenological descriptions. Apart from that, this review classifies 2D magnetic materials into several categories for reaching out each and every class of materials. Additionally, this review summarizes recent advancements of some pioneer 2D magnetodielectric materials. Last but not the least, the current review provides possible research directions for enhancing magnetodielectric coupling in those and mentions the possibilities for future developments.&#xD;
Photoemission spectroscopy and {\it ab-initio} simulation of CrFeVGa and CoFeVSb : A Comparative Study
Authors: Nag Jadupati , Vijay Kritika , Bandyopadhyay Barnabha , Banik Soma , Alam Aftab , Suresh K G 
Published: February 2025

Abstract
We present a comprehensive photoemission study of two Vanadium-based quaternary Heusler alloys, CrFeVGa and CoFeVSb, which are highly promising candidates for spintronics and topological quantum applications. CrFeVGa exhibits large anomalous Hall conductivity due to the large Berry curvature originating from its non-trivial topological bands. In contrast, CoFeVSb displays a spin-valve-like behavior alongside excellent thermoelectric properties, such as ultra-low thermal conductivity and high power factor at room temperature. By utilizing synchrotron X-ray photoemission spectroscopy (XPS) and resonant photoemission spectroscopy, we have investigated the core levels and valence band of both the alloys. Our analysis shows that the V 3\textit{d} states are primarily responsible for the electronic states at the Fermi level which result in the high spin polarization, consistent with our theoretical predictions. The presence of the Fermi edge in the valence band spectra in both the systems confirms the predicted metallic or half/semi-metallic features. The observed spectra match qualitatively with our simulated partial density of states. A close inspection of the temperature dependent valence band spectra indicates that some of the intriguing bulk properties reported earlier on these two systems are intimately connected with their unique band structure topology. This in turn facilitate a deeper insight into the origin of such interesting properties of these alloys. Such direct measurements of electronic structure provide a guiding platform towards a better understanding of the anomalous properties of any material in general.
Diamond nanoneedles for biosensing
Authors: Quarshie Mariam M. , Golubewa Lena , Giraulo Caterina , Morello Silvana , Cirillo Claudia , Sarno Maria , Xu Bo , Balasubramanian Priyadharshini , Mindarava Yuliya , Tutkus Marijonas , Obraztsov Alexander , Jelezko Fedor , Kuzhir Polina , Malykhin Sergei 
Published: February 2025

Abstract
Nanoparticles and nanomaterials are revolutionizing medicine by offering diverse tools for diagnosis and therapy, including devices, contrast agents, drug delivery systems, adjuvants, therapeutics, and theragnostic agents. Realizing full applied potential requires a deep understanding of the interactions of nano dimensional objects with biological cells. In this study, we investigate interaction of single-crystal diamond nanoneedles (SCDNNs) containing silicon vacancy (SiV-) colour centres with biological substances. Four batches of the diamond needles with sizes ranging between 200 nm to 1300 nm and their water suspensions were used in these studies. The human lung fibroblast cells were used for the proof-of-concept demonstration. Employing micro-photoluminescence (PL) mapping, confocal microscopy, and lactate dehydrogenase (LDH) viability tests, we evaluated the cellular response to the SCDNNs. Intriguingly, our investigation with PL spectroscopy revealed that the cells and SCDNNs can coexist together with approved efficient registration of SiV- centres presence. Notably, LDH release remained minimal in cells exposed to optimally sized SCDNNs, suggesting a small number of lysed cells, and indicating non-cytotoxicity in concentrations of 2 µg/ml to 32 µg/ml. The evidence obtained highlights the potential of SCDNNs for extra- or/and intracellular drug delivery when the surface of the needle is modified. In addition, fluorescent defects in the SCDNNs can be used for bioimaging as well as optical and quantum sensing.&#xD;