bluuebunny/crossref_metadata_2025_split huggingface dataset:
Boundary Traces of Holomorphic Functions on the Unit Ball in $$\mathbb {C}^n$$
Authors: Gryc William E. 
Published: June 2024

AbstractIt is a classical theorem that if a function on the unit circle is integrable, then it is the nontangential limit of a holomorphic function on the open disc (subject to a certain growth condition) if and only if its Fourier coefficients for nonnegative integers are zero. In this article we generalize this result to higher complex dimensions by proving that for an integrable function on the unit sphere, it is a “boundary trace” of a holomorphic function on the open unit ball if and only if two particular families of integral equations are satisfied. To do this, we use the theory of Hardy spaces as well as the invariant Poisson and Cauchy integrals.
Further regularity results in $$P-$$extremal setting
Authors: Perera Menuja 
Published: June 2024

AbstractIn our paper, Pluripotential theory and convex bodies: a Siciak-Zaharjuta theorem (Computational Methods and Function Theory (2020), 20(3-4), 571-590) by Bayraktar et al., we proved a regularity result of $$P-$$

P
-

extremal function. In this paper, we prove some other stronger regularity results analogue to those in the standard setting. Specifically we focus on proving the following proposition: Proposition: Let $$K={\bar{D}}\subset {\mathbb {C}}^d$$

K
=

D

¯

⊂

C

d

be the closure of a bounded domain D with $$\partial D$$

∂
D

of class $$C^{1,1}$$

C

1
,
1

. Then, for any $$Q\in {\mathcal {C}}_\alpha (K)$$

Q
∈

C
α

(
K
)

, where $${\mathcal {C}}_\alpha (K)$$

C
α

(
K
)

is the Hölder class $$\alpha$$
α
on K, we have $$V_{P,K,Q}\in {\mathcal {C}}_\alpha ({\mathbb {C}}^d) \text { for a convex body } P\subset (\mathbb {R^+})^d.$$

V

P
,
K
,
Q

∈

C
α

(

C

d

)

for a convex body

P
⊂

(

R
+

)

d

.
GABoT: A Lightweight Real-Time Adaptable Approach for Intelligent Fault Diagnosis of Rotating Machinery
Authors: Bagci Das Duygu , Das Oguzhan 
Published: June 2024

Abstract
Purpose
As the concept of Industry 4.0 is introduced, the significance of Smart Fault Diagnosis in the industry is increased. Therefore, it is essential to develop accurate, robust, and lightweight intelligent fault diagnosis approach that can be executed in real-time even with embedded systems. Additionally, it is preferable to use a single method for multi-purposes such as the fault detection, identification, and severity assessment. This study proposed a new approach called GaBoT for fault diagnosis of rotating machinery to satisfy those requirements.

Method
The proposed approach adopted the concept of the ensemble of ensembles by boosting random forest. The statistical features of discrete wavelet transform were considered since they are easy and fast to obtain. Model optimization was conducted by employing genetic algorithm to alleviate the computational load without decreasing the model performance. The proposed approach has been validated by unseen data from an experimental dataset including shaft, rotor, and bearing faults.

Results
The experimental results indicate that the proposed approach can effectively find the fault type with 99.85% accuracy. Besides, it successfully determines the fault severity by accuracy values between 96.45 and 99.72%. GABoT can also determine the imbalance severity in the presence of three bearing faults.

Conclusion
Employing GA eliminated most of the redundant features and reduced the model execution time consumption. The results yielded that GABoT is a highly accurate model, and can be utilized in real-time fault diagnosis of rotating machinery.
A survey on applications of reinforcement learning in spatial resource allocation
Authors: Zhang Di , Wang Moyang , Mango Joseph , Li Xiang , Xu Xianrui 
Published: June 2024

AbstractThe challenge of spatial resource allocation is pervasive across various domains such as transportation, industry, and daily life. As the scale of real-world issues continues to expand and demands for real-time solutions increase, traditional algorithms face significant computational pressures, struggling to achieve optimal efficiency and real-time capabilities. In recent years, with the escalating computational power of computers, the remarkable achievements of reinforcement learning in domains like Go and robotics have demonstrated its robust learning and sequential decision-making capabilities. Given these advancements, there has been a surge in novel methods employing reinforcement learning to tackle spatial resource allocation problems. These methods exhibit advantages such as rapid solution convergence and strong model generalization abilities, offering a new perspective on resolving spatial resource allocation problems. Despite the progress, reinforcement learning still faces hurdles when it comes to spatial resource allocation. There remains a gap in its ability to fully grasp the diversity and intricacy of real-world resources. The environmental models used in reinforcement learning may not always capture the spatial dynamics accurately. Moreover, in situations laden with strict and numerous constraints, reinforcement learning can sometimes fall short in offering feasible strategies. Consequently, this paper is dedicated to summarizing and reviewing current theoretical approaches and practical research that utilize reinforcement learning to address issues pertaining to spatial resource allocation. In addition, the paper accentuates several unresolved challenges that urgently necessitate future focus and exploration within this realm and proposes viable approaches for these challenges. This research furnishes valuable insights that may assist scholars in gaining a more nuanced understanding of the problems, opportunities, and potential directions concerning the application of reinforcement learning in spatial resource allocation.
FERONIA homologs in stress responses of horticultural plants: current knowledge and missing links
Authors: Huang Xinhua , Liu Yuhan , Jia Yanhong , Ji Lizhu , Luo Xiaomin , Tian Shiping , Chen Tong 
Published: June 2024

AbstractOwing to its versatile roles in almost all aspects of plants, FERONIA (FER), a receptor-like kinase of the Catharanthus roseus receptor-like kinase 1-like (CrRLK1L) subfamily, has received extensive research interests during the past decades. Accumulating evidence has been emerged that FER homologs in horticultural crops also play crucial roles in reproductive biology and responses to environmental stimuli (abiotic and biotic stress factors). Here, we provide a review for the latest advances in the studies on FER homologs in modulating stress responses in horticultural crops, and further analyze the underlying mechanisms maintained by FER. Moreover, we also envisage the missing links in current work and provide a perspective for future studies on this star protein.
Acetylation modification in the regulation of macroautophagy
Authors: Huang Li , Guo Hongwei 
Published: June 2024

AbstractMacroautophagy, commonly referred to as autophagy, is an evolutionarily conserved cellular process that plays a crucial role in maintaining cellular homeostasis. It orchestrates the delivery of dysfunctional or surplus cellular materials to the vacuole or lysosome for degradation and recycling, particularly during adverse conditions. Over the past few decades, research has unveiled intricate regulatory mechanisms governing autophagy through various post-translational modifications (PTMs). Among these PTMs, acetylation modification has emerged as a focal point in yeast and animal studies. It plays a pivotal role in autophagy by directly targeting core components within the central machinery of autophagy, including autophagy initiation, nucleation, phagophore expansion, and autophagosome maturation. Additionally, acetylation modulates autophagy at the transcriptional level by modifying histones and transcription factors. Despite its well-established significance in yeast and mammals, the role of acetylation in plant autophagy remains largely unexplored, and the precise regulatory mechanisms remain enigmatic. In this comprehensive review, we summarize the current understanding of the function and underlying mechanisms of acetylation in regulating autophagy across yeast, mammals, and plants. We particularly highlight recent advances in deciphering the impact of acetylation on plant autophagy. These insights not only provide valuable guidance but also inspire further scientific inquiries into the intricate role of acetylation in plant autophagy.
Unraveling the Atmospheric Energy Input and Ionization Due To EMIC‐Driven Electron Precipitation From ELFIN Observations
Authors: Capannolo L. , Marshall R. , Li W. , Berland G. , Duderstadt K. , Sivadas N. , Turner D. L. , Angelopoulos V. 
Published: June 2024

AbstractEnergetic electron precipitation (EEP) from the radiation belts into Earth's atmosphere leads to several profound effects (e.g., enhancement of ionospheric conductivity, possible acceleration of ozone destruction processes). An accurate quantification of the energy input and ionization due to EEP is still lacking due to instrument limitations of low‐Earth‐orbit satellites capable of detecting EEP. The deployment of the Electron Losses and Fields InvestigatioN (ELFIN) CubeSats marks a new era of observations of EEP with an improved pitch‐angle (0°–180°) and energy (50 keV–6 MeV) resolution. Here, we focus on the EEP recorded by ELFIN coincident with electromagnetic ion cyclotron (EMIC) waves, which play a major role in radiation belt electron losses. The EMIC‐driven EEP (∼200 keV–∼2 MeV) exhibits a pitch‐angle distribution (PAD) that flattens with increasing energy, indicating more efficient high‐energy precipitation. Leveraging the combination of unique electron measurements from ELFIN and a comprehensive ionization model known as Boulder Electron Radiation to Ionization (BERI), we quantify the energy input of EMIC‐driven precipitation (on average, ∼3.3 × 10−2 erg/cm2/s), identify its location (any longitude, 50°–70° latitude), and provide the expected range of ion‐electron production rate (on average, 100–200 pairs/cm3/s), peaking in the mesosphere—a region often overlooked. Our findings are crucial for improving our understanding of the magnetosphere‐ionosphere‐atmosphere system as they accurately specify the contribution of EMIC‐driven EEP, which serves as a crucial input to state‐of‐the‐art atmospheric models (e.g., WACCM) to quantify the accurate impact of EMIC waves on both the atmospheric chemistry and dynamics.
Two-photon emission from a superlattice-based superconducting light-emitting structure
Authors: Bouscher Shlomi , Panna Dmitry , Jacovi Ronen , Jabeen Fauzia , Schneider Christian , Höfling Sven , Hayat Alex 
Published: June 2024

AbstractSuperconductor-semiconductor hybrid devices can bridge the gap between solid-state-based and photonics-based quantum systems, enabling new hybrid computing schemes, offering increased scalability and robustness. One example for a hybrid device is the superconducting light-emitting diode (SLED). SLEDs have been theoretically shown to emit polarization-entangled photon pairs by utilizing radiative recombination of Cooper pairs. However, the two-photon nature of the emission has not been shown experimentally before. We demonstrate two-photon emission in a GaAs/AlGaAs SLED. Measured electroluminescence spectra reveal unique two-photon superconducting features below the critical temperature (Tc), while temperature-dependent photon-pair correlation experiments (g(2)(τ,T)) demonstrate temperature-dependent time coincidences below Tc between photons emitted from the SLED. Our results pave the way for compact and efficient superconducting quantum light sources and open new directions in light-matter interaction studies.
Simple and robust 3D MINFLUX excitation with a variable phase plate
Authors: Deguchi Takahiro , Ries Jonas 
Published: June 2024

AbstractMINFLUX has achieved extraordinary resolution in superresolution imaging and single fluorophore tracking. It is based on localizing single fluorophores by rapid probing with a patterned beam that features a local intensity minimum. Current implementations, however, are complex and expensive and are limited in speed and robustness. Here, we show that a combination of an electro-optical modulator with a segmented birefringent element such as a spatial light modulator produces a variable phase plate for which the phase can be scanned on the MHz timescale. Bisected or top-hat phase patterns generate high-contrast compact excitation point-spread functions for MINFLUX localization in the x, y, and z-direction, respectively, which can be scanned across a fluorophore within a microsecond, switched within 60 microseconds and alternated among different excitation wavelengths. We discuss how to compensate for non-optimal performance of the components and present a robust 3D and multi-color MINFLUX excitation module, which we envision as an integral component of a high-performance and cost-effective open-source MINFLUX.
Neurocognition and NMDAR co-agonists pathways in individuals with treatment resistant first-episode psychosis: a 3-year follow-up longitudinal study
Authors: Camporesi Sara , Xin Lijing , Golay Philippe , Eap Chin Bin , Cleusix Martine , Cuenod Michel , Fournier Margot , Hashimoto Kenji , Jenni Raoul , Ramain Julie , Restellini Romeo , Solida Alessandra , Conus Philippe , Do Kim Q. , Khadimallah Ines 
Published: June 2024

AbstractThis study aims to determine whether 1) individuals with treatment-resistant schizophrenia display early cognitive impairment compared to treatment-responders and healthy controls and 2) N-methyl-D-aspartate-receptor hypofunction is an underlying mechanism of cognitive deficits in treatment-resistance. In this case‒control 3-year-follow-up longitudinal study, n = 697 patients with first-episode psychosis, aged 18 to 35, were screened for Treatment Response and Resistance in Psychosis criteria through an algorithm that assigns patients to responder, limited-response or treatment-resistant category (respectively resistant to 0, 1 or 2 antipsychotics). Assessments at baseline: MATRICS Consensus Cognitive Battery; N-methyl-D-aspartate-receptor co-agonists biomarkers in brain by MRS (prefrontal glutamate levels) and plasma (D-serine and glutamate pathways key markers). Patients were compared to age- and sex-matched healthy controls (n = 114). Results: patient mean age 23, 27% female. Treatment-resistant (n = 51) showed lower scores than responders (n = 183) in processing speed, attention/vigilance, working memory, verbal learning and visual learning. Limited responders (n = 59) displayed an intermediary phenotype. Treatment-resistant and limited responders were merged in one group for the subsequent D-serine and glutamate pathway analyses. This group showed D-serine pathway dysregulation, with lower levels of the enzymes serine racemase and serine-hydroxymethyltransferase 1, and higher levels of the glutamate-cysteine transporter 3 than in responders. Better cognition was associated with higher D-serine and lower glutamate-cysteine transporter 3 levels only in responders; this association was disrupted in the treatment resistant group. Treatment resistant patients and limited responders displayed early cognitive and persistent functioning impairment. The dysregulation of NMDAR co-agonist pathways provides underlying molecular mechanisms for cognitive deficits in treatment-resistant first-episode psychosis. If replicated, our findings would open ways to mechanistic biomarkers guiding response-based patient stratification and targeting cognitive improvement in clinical trials.
The Caspase-Activated DNase drives inflammation and contributes to defense against viral infection
Authors: Moeed Abdul , Thilmany Nico , Beck Frederic , Puthussery Bhagya K. , Ortmann Noemi , Haimovici Aladin , Badr M. Tarek , Haghighi Elham Bavafaye , Boerries Melanie , Öllinger Rupert , Rad Roland , Kirschnek Susanne , Gentle Ian E. , Donakonda Sainitin , Petric Philipp P. , Hummel Jonas F. , Pfaffendorf Elisabeth , Zanetta Paola , Schell Christoph , Schwemmle Martin , Weber Arnim , Häcker Georg 
Published: June 2024

AbstractMitochondria react to infection with sub-lethal signals in the apoptosis pathway. Mitochondrial signals can be inflammatory but mechanisms are only partially understood. We show that activation of the caspase-activated DNase (CAD) mediates mitochondrial pro-inflammatory functions and substantially contributes to host defense against viral infection. In cells lacking CAD, the pro-inflammatory activity of sub-lethal signals was reduced. Experimental activation of CAD caused transient DNA-damage and a pronounced DNA damage response, involving major kinase signaling pathways, NF-κB and cGAS/STING, driving the production of interferon, cytokines/chemokines and attracting neutrophils. The transcriptional response to CAD-activation was reminiscent of the reaction to microbial infection. CAD-deficient cells had a diminished response to viral infection. Influenza virus infected CAD-deficient mice displayed reduced inflammation in lung tissue, higher viral titers and increased weight loss. Thus, CAD links the mitochondrial apoptosis system and cell death caspases to host defense. CAD-driven DNA damage is a physiological element of the inflammatory response to infection.
Superstrength permanent magnets with iron-based superconductors by data- and researcher-driven process design
Authors: Yamamoto Akiyasu , Tokuta Shinnosuke , Ishii Akimitsu , Yamanaka Akinori , Shimada Yusuke , Ainslie Mark D. 
Published: June 2024

Abstract
Iron-based high-temperature (high-T
c) superconductors have good potential to serve as materials in next-generation superstrength quasipermanent magnets owing to their distinctive topological and superconducting properties. However, their unconventional high-T
c superconductivity paradoxically associates with anisotropic pairing and short coherence lengths, causing challenges by inhibiting supercurrent transport at grain boundaries in polycrystalline materials. In this study, we employ machine learning to manipulate intricate polycrystalline microstructures through a process design that integrates researcher- and data-driven approaches via tailored software. Our approach results in a bulk Ba0.6K0.4Fe2As2 permanent magnet with a magnetic field that is 2.7 times stronger than that previously reported. Additionally, we demonstrate magnetic field stability exceeding 0.1 ppm/h for a practical 1.5 T permanent magnet, which is a vital aspect of medical magnetic resonance imaging. Nanostructural analysis reveals contrasting outcomes from data- and researcher-driven processes, showing that high-density defects and bipolarized grain boundary spacing distributions are primary contributors to the magnet’s exceptional strength and stability.
Developmental origin of oligodendrocytes determines their function in the adult brain
Authors: Foerster Sarah , Floriddia Elisa M. , van Bruggen David , Kukanja Petra , Hervé Bastien , Cheng Shangli , Kim Eosu , Phillips Benjamin U. , Heath Christopher J. , Tripathi Richa B. , Call Cody , Bartels Theresa , Ridley Katherine , Neumann Björn , López-Cruz Laura , Crawford Abbe H. , Lynch Cian J. , Serrano Manuel , Saksida Lisa , Rowitch David H. , Möbius Wiebke , Nave Klaus-Armin , Rasband Matthew N. , Bergles Dwight E. , Kessaris Nicoletta , Richardson William D. , Bussey Timothy J. , Zhao Chao , Castelo-Branco Gonçalo , Franklin Robin J. M. 
Published: June 2024

AbstractIn the mouse embryonic forebrain, developmentally distinct oligodendrocyte progenitor cell populations and their progeny, oligodendrocytes, emerge from three distinct regions in a spatiotemporal gradient from ventral to dorsal. However, the functional importance of this oligodendrocyte developmental heterogeneity is unknown. Using a genetic strategy to ablate dorsally derived oligodendrocyte lineage cells (OLCs), we show here that the areas in which dorsally derived OLCs normally reside in the adult central nervous system become populated and myelinated by OLCs of ventral origin. These ectopic oligodendrocytes (eOLs) have a distinctive gene expression profile as well as subtle myelination abnormalities. The failure of eOLs to fully assume the role of the original dorsally derived cells results in locomotor and cognitive deficits in the adult animal. This study reveals the importance of developmental heterogeneity within the oligodendrocyte lineage and its importance for homeostatic brain function.
Distinct origin and region-dependent contribution of stromal fibroblasts to fibrosis following traumatic injury in mice
Authors: Holl Daniel , Hau Wing Fung , Julien Anais , Banitalebi Shervin , Kalkitsas Jannis , Savant Soniya , Llorens-Bobadilla Enric , Herault Yann , Pavlovic Guillaume , Amiry-Moghaddam Mahmood , Dias David Oliveira , Göritz Christian 
Published: June 2024

AbstractFibrotic scar tissue formation occurs in humans and mice. The fibrotic scar impairs tissue regeneration and functional recovery. However, the origin of scar-forming fibroblasts is unclear. Here, we show that stromal fibroblasts forming the fibrotic scar derive from two populations of perivascular cells after spinal cord injury (SCI) in adult mice of both sexes. We anatomically and transcriptionally identify the two cell populations as pericytes and perivascular fibroblasts. Fibroblasts and pericytes are enriched in the white and gray matter regions of the spinal cord, respectively. Both cell populations are recruited in response to SCI and inflammation. However, their contribution to fibrotic scar tissue depends on the location of the lesion. Upon injury, pericytes and perivascular fibroblasts become activated and transcriptionally converge on the generation of stromal myofibroblasts. Our results show that pericytes and perivascular fibroblasts contribute to the fibrotic scar in a region-dependent manner.
A materials terminology knowledge graph automatically constructed from text corpus
Authors: Zhang Yuwei , Chen Fangyi , Liu Zeyi , Ju Yunzhuo , Cui Dongliang , Zhu Jinyi , Jiang Xue , Guo Xi , He Jie , Zhang Lei , Zhang Xiaotong , Su Yanjing 
Published: June 2024

AbstractA scalable, reusable, and broad-coverage unified material knowledge representation shows its importance and will bring great benefits to data sharing among materials communities. A knowledge graph (KG) for materials terminology, which is a formal collection of term entities and relationships, is conceptually important to achieve this goal. In this work, we propose a KG for materials terminology, named Materials Genome Engineering Database Knowledge Graph (MGED-KG), which is automatically constructed from text corpus via natural language processing. MGED-KG is the most comprehensive KG for materials terminology in both Chinese and English languages, consisting of 8,660 terms and their explanations. It encompasses 11 principal categories, such as Metals, Composites, Nanomaterials, each with two or three levels of subcategories, resulting in a total of 235 distinct category labels. For further application, a knowledge web system based on MGED-KG is developed and shows its great power in improving data sharing efficiency from the aspects of query expansion, term, and data recommendation.