bluuebunny/crossref_metadata_2025_split huggingface dataset:
Different hierarchical reconfigurations in the brain by psilocybin and escitalopram for depression
Authors: Deco Gustavo , Sanz Perl Yonatan , Johnson Samuel , Bourke Niamh , Carhart-Harris Robin L. , Kringelbach Morten L. 
Published: August 2024

AbstractEffective interventions for neuropsychiatric disorders may work by rebalancing the brain’s functional hierarchical organization. Here we directly investigated the effects of two different serotonergic pharmacological interventions on functional brain hierarchy in major depressive disorder in a two-arm double-blind phase II randomized controlled trial comparing psilocybin therapy (22 patients) with escitalopram (20 patients). Patients with major depressive disorder received either 2 × 25 mg of oral psilocybin, three weeks apart, plus six weeks of daily placebo (‘psilocybin arm’) or 2 × 1 mg of oral psilocybin, three weeks apart, plus six weeks of daily escitalopram (10–20 mg; ‘escitalopram arm’). Resting-state functional magnetic resonance imaging scans were acquired at baseline and three weeks after the second psilocybin dose (NCT03429075). The brain mechanisms were captured by generative effective connectivity, estimated from whole-brain modeling of resting state for each session and patient. Hierarchy was determined for each of these sessions using measures of directedness and trophic levels on the effective connectivity, which captures cycle structure, stability and percolation. The results showed that the two pharmacological interventions created significantly different hierarchical reconfigurations of whole-brain dynamics with differential, opposite statistical effect responses. Furthermore, the use of machine learning revealed significant differential reorganization of brain hierarchy before and after the two treatments. Machine learning was also able to predict treatment response with an accuracy of 0.85 ± 0.04. Overall, the results demonstrate that psilocybin and escitalopram work in different ways for rebalancing brain dynamics in depression. This suggests the hypothesis that neuropsychiatric disorders could be closely linked to the breakdown in regions orchestrating brain dynamics from the top of the hierarchy.
PQBP3 prevents senescence by suppressing PSME3-mediated proteasomal Lamin B1 degradation
Authors: Yoshioka Yuki , Huang Yong , Jin Xiaocen , Ngo Kien Xuan , Kumaki Tomohiro , Jin Meihua , Toyoda Saori , Takayama Sumire , Inotsume Maiko , Fujita Kyota , Homma Hidenori , Ando Toshio , Tanaka Hikari , Okazawa Hitoshi 
Published: August 2024

AbstractSenescence of nondividing neurons remains an immature concept, with especially the regulatory molecular mechanisms of senescence-like phenotypes and the role of proteins associated with neurodegenerative diseases in triggering neuronal senescence remaining poorly explored. In this study, we reveal that the nucleolar polyglutamine binding protein 3 (PQBP3; also termed NOL7), which has been linked to polyQ neurodegenerative diseases, regulates senescence as a gatekeeper of cytoplasmic DNA leakage. PQBP3 directly binds PSME3 (proteasome activator complex subunit 3), a subunit of the 11S proteasome regulator complex, decreasing PSME3 interaction with Lamin B1 and thereby preventing Lamin B1 degradation and senescence. Depletion of endogenous PQBP3 causes nuclear membrane instability and release of genomic DNA from the nucleus to the cytosol. Among multiple tested polyQ proteins, ataxin-1 (ATXN1) partially sequesters PQBP3 to inclusion bodies, reducing nucleolar PQBP3 levels. Consistently, knock-in mice expressing mutant Atxn1 exhibit decreased nuclear PQBP3 and a senescence phenotype in Purkinje cells of the cerebellum. Collectively, these results suggest homologous roles of the nucleolar protein PQBP3 in cellular senescence and neurodegeneration.
Support vector machine‐based handover scheme for heterogeneous ultra dense network of high‐speed railway
Authors: Wang Siling , Zhang Li 
Published: August 2024

AbstractIn order to meet the growing demands and extend network coverage for high‐speed railway (HSR) system, the dense deployment of a large number of small cells (SCs) is considered for 5G networks. However, the deployment of dense SCs and the high speed of trains result in challenging problems such as interference, frequent handovers (HOs), increased HO failure rate, and consequently the deteriorated overall quality of service (QoS). In order to address the challenges in handover, an improved handover decision strategy is proposed based on Support Vector Machine (SVM). The HO decision making is considered as a classification problem taking into account available states that they may have in the HSR network. From the simulation results, it is observed that the proposed scheme is capable of decreasing the number of HO, HO failure rate and enhancing the network performance remarkably.
Digital twin intelligent transportation system (DT‐ITS)—A systematic review
Authors: Ge Chenyu , Qin Shengfeng 
Published: August 2024

AbstractDigital twin (DT) has attracted much attention from the transportation community over the past 6 years. Combining the DT with intelligent transportation system (ITS) forms a digital twin intelligent transportation system (DT‐ITS), which stands as one of the most effective solutions for addressing current complex traffic problems. Due to the rapid advancements in this field and a lack of recent literature reviews, this paper first reviews relevant literature on DT‐ITS architecture design, to comprehend its core structure, methods, potential services and stakeholders, and implementation challenges, and then discusses DT‐ITS core considerations, aiming to provide a general configuration model of DT‐ITS for future development. Second, this paper focuses on reviewing the existing progress of DT‐ITS services within the 32 categories of ITS services, adopting the service‐centred point of view, to explore the potential DT‐ITS services, proposed delivery methods, challenges, and opportunities for various stakeholders. Third, key enabling technologies supporting DT‐ITS are reviewed and discussed, such as data fusion, cooperative perception, multi‐access edge computing (MEC) (including computing offloading and service caching), federated learning, edge‐cloud collaboration, secure and efficient communication (including Blockchain [BC], 5G), virtual modelling, and eXtended reality (XR). Finally, the paper identifies development trends and provides recommendations for future advancements.
A recursive framework of vehicle trajectory planning at mixed‐traffic signalized intersections
Authors: Yang Menglin , Yu Hao , Liu Pan 
Published: August 2024

AbstractThis study aims to introduce a new strategy for anticipating the behaviour of human‐driven vehicles (HDVs) and designing trajectories for connected and automated vehicles (CAVs) at signalized intersections under mixed traffic scenarios. To tackle the challenge of unreliable HDV trajectory predictions stemming from driving unpredictability, a recursive framework is developed. This framework integrates real‐time tracking data from both traffic detectors and CAVs, continuously updating HDV predictions. The proposed approach employs the updated predictions to formulate optimal control problems recursively to optimize or adjust CAV trajectories, enhancing travel and energy efficiency. Besides, the recomputing of CAV trajectories will only be conducted when the variation in predictions rises to a certain threshold, balancing efficiency and computing consumption, inspired and modified based on MPC methods. The application of the Pontryagin maximum principle aids in finding solutions efficiently by transforming necessary conditions into a system of equations and consolidating elementary unconstrained and constrained arcs. Numerical simulations were carried out to evaluate the performance of the proposed recursive framework, revealing its superiority over the one‐time approach, particularly in isolated intersections with high traffic demands. Additionally, the recursive framework exhibited more robust and effective enhancements throughout the road network.
Research on TOGI‐EFLL flux observer for IPMSM sensorless control
Authors: Hao Xue , Luo Yutao 
Published: August 2024

AbstractFor the purpose of enhancing the performance of interior permanent magnet synchronous motors (IPMSMs) sensorless control, a flux observer based on a third‐order generalized integrator with enhanced frequency‐locked loop (TOGI‐EFLL) is introduced in this paper. Compared with the traditional second‐order generalized integrator with frequency‐locked loop (SOGI‐FLL), the proposed TOGI‐EFLL can effectively mitigate the direct current (DC) bias stemming from non‐ideal factors, such as the inverter non‐linearities and detection errors, without introducing additional parameters. Initially, the active flux observer model and the limitations of the conventional SOGI‐FLL are presented. Subsequently, the proposed flux observer based on TOGI‐EFLL has been intensively investigated. Furthermore, the design of the damping factor and the digital implementation of the algorithm are developed to ensure seamless integration into digital systems. Finally, the effectiveness of the proposed sensorless control strategy is validated through the comprehensive experimental results.
Rotating machine bearing health prognosis using a data driven approach based on KS‐density and BiLSTM
Authors: Habbouche Houssem , Benkedjouh Tarak , Amirat Yassine , Benbouzid Mohamed 
Published: August 2024

AbstractRolling element bearings are vital components within rotating machinery, making them a central focus of maintenance in the prognostics and health management sector. This involves closely monitoring their condition to accurately predict the remaining useful life, increasing reliability while minimizing unexpected breakdowns, thereby enabling cost savings through planned maintenance, and enhancing operational stability and security. To achieve this goal, it is necessary to build an online intelligent system for degradation monitoring and failure prognosis by the construction of a robust health indicator and making quantitative measure for bearing degradation. In this paper, an efficient and reliable approach is proposed to estimate the remaining useful life of bearing. A new prediction method is presented by the combination of kernel smoothing density (KS‐density) and bidirectional long short‐term memory (BiLSTM). Firstly, KS‐density smoothens the preliminarily estimated probability distribution function using machinery degradation data. Secondly, the obtained KS‐density is used in feed deep learning technique based on BiLSTM models. On this basis, the variation of the signal distribution models between the current faulty state and the normal conditions state is quantified for bearing health assessment. The effective recognition of bearing degradation by the proposed Weibull‐based health index is demonstrated through experimental validations utilizing run‐to‐failure datasets, provided by the centre for intelligent maintenance systems. The comparison with the literature's review show that the prediction results of the proposed approach are more accurate.
Machine learning for exoplanet detection in high-contrast spectroscopy
Authors: Garvin Emily O. , Bonse Markus J. , Hayoz Jean , Cugno Gabriele , Spiller Jonas , Patapis Polychronis A. , dit de la Roche Dominique Petit , Nath-Ranga Rakesh , Absil Olivier , Meinshausen Nicolai F. , Quanz Sascha P. 
Published: August 2024

Context. The new generation of observatories and instruments (VLT/ERIS, JWST, ELT) motivate the development of robust methods to detect and characterise faint and close-in exoplanets. Molecular mapping and cross-correlation for spectroscopy use molecular templates to isolate a planet’s spectrum from its host star. However, reliance on signal-to-noise ratio metrics can lead to missed discoveries, due to strong assumptions of Gaussian-independent and identically distributed noise.Aims. We introduce machine learning for cross-correlation spectroscopy (MLCCS). The aim of this method is to leverage weak assumptions on exoplanet characterisation, such as the presence of specific molecules in atmospheres, to improve detection sensitivity for exoplanets.Methods. The MLCCS methods, including a perceptron and unidimensional convolutional neural networks, operate in the cross-correlated spectral dimension, in which patterns from molecules can be identified. The methods flexibly detect a diversity of planets by taking an agnostic approach towards unknown atmospheric characteristics. The MLCCS approach is implemented to be adaptable for a variety of instruments and modes. We tested this approach on mock datasets of synthetic planets inserted into real noise from SINFONI at theK-band.Results. The results from MLCCS show outstanding improvements. The outcome on a grid of faint synthetic gas giants shows that for a false discovery rate up to 5%, a perceptron can detect about 26 times the amount of planets compared to an S/N metric. This factor increases up to 77 times with convolutional neural networks, with a statistical sensitivity (completeness) shift from 0.7 to 55.5%. In addition, MLCCS methods show a drastic improvement in detection confidence and conspicuity on imaging spectroscopy.Conclusions. Once trained, MLCCS methods offer sensitive and rapid detection of exoplanets and their molecular species in the spectral dimension. They handle systematic noise and challenging seeing conditions, can adapt to many spectroscopic instruments and modes, and are versatile regarding planet characteristics, enabling the identification of various planets in archival and future data.
Dependence of coronal mass ejections on the morphology and toroidal flux of their source magnetic flux ropes
Authors: Guo J. H. , Linan L. , Poedts S. , Guo Y. , Schmieder B. , Lani A. , Ni Y. W. , Brchnelova M. , Perri B. , Baratashvili T. , Li S. T. , Chen P. F. 
Published: August 2024

Context. Coronal mass ejections (CMEs) stand as intense eruptions of magnetized plasma from the Sun, and they play a pivotal role in driving significant changes of the heliospheric environment. Deducing the properties of CMEs from their progenitors in solar source regions is crucial for space weather forecasting.
Aims. The primary objective of this paper is to establish a connection between CMEs and their progenitors in solar source regions, enabling us to infer the magnetic structures of CMEs before their full development.
Methods. We created a dataset comprising a magnetic flux rope series with varying projection shapes (S-, Z-, and toroid-shaped), sizes, and toroidal fluxes using the Regularized Biot-Savart Laws (RBSL). These flux ropes were inserted into solar quiet regions with the aim of imitating the eruptions of quiescent filaments. Thereafter, we simulated the propagation of these flux ropes from the solar surface to a distance of 25 R⊙ with our global coronal magnetohydrodynamic (MHD) model COCONUT.
Results. Our parametric survey revealed significant impacts of source flux ropes on the consequent CMEs. Regarding the flux-rope morphology, we find that the projection shape (e.g., sigmoid or torus) can influence the magnetic structures of CMEs at 20 R⊙, albeit with minimal impacts on the propagation speed. However, these impacts diminish as source flux ropes become fat. In terms of toroidal flux, our simulation results demonstrate a pronounced correlation with the propagation speed of CMEs as well as the successfulness in erupting.
Conclusions. This work builds the bridge between the CMEs in the outer corona and their progenitors in solar source regions. Our parametric survey suggests that the projection shape, cross-section radius, and toroidal flux of source flux ropes are crucial parameters in predicting magnetic structures and the propagation speed of CMEs, providing valuable insights for space weather prediction. On the one hand, the conclusion drawn here could be instructive in identifying the high-risk eruptions with the potential to induce stronger geomagnetic effects (Bz and propagation speed). On the other hand, our findings hold practical significance for refining the parameter settings of launched CMEs at 21.5 R⊙ in heliospheric simulations, such as with EUHFORIA, based on observations for their progenitors in solar source regions.
Dehydrosilylation of Alcohols Using Gold Nanoparticles Deposited on Citric Acid Modified Fibrillated Cellulose
Authors: Sakurai Hidehiro , Suwattananuruk Butsaratip , Uetake Yuta 
Published: August 2024

AbstractThe development of an effective catalytic system for the dehydrogenative coupling of hydrosilanes with alcohols remains an ongoing challenge, particularly for alcohol protection applications. In this study, we report the development and optimization of a highly efficient gold catalyst supported on fibrillated cellulose modified with citric acid. The catalyst exhibited remarkable catalytic activity under mild conditions with 0.01–0.05 mol% of Au loading, facilitating the formation of silyl ethers with excellent yield. Notably, our catalytic system overcomes the need for excess alcohol, typically required in such reactions, making it highly practical for alcohol protection applications. This work represents a significant advancement in the field of dehydrosilylation catalysis, offering a sustainable, efficient, and environmentally friendly approach for the synthesis of functional silanol-based materials and alcohol protection applications. The scope of substrates and the utility of the catalyst have been thoroughly studied.
Chiral π-Conjugated Double Helical Aminyl Diradical with the Triplet Ground State
Authors: Guo Haoxin , Rajca Andrzej 
Published: August 2024

AbstractWe describe effective development of the highly diastereoselective synthesis of double helical tetraamine 2-H2-C2 and propose a mechanism for its formation. The resolution of 2-H2-C2 is facilitated by a high racemization barrier of 43 kcal mol–1 and it is implemented via either a chiral auxiliary or preparative supercritical fluid chromatography. This enables preparation of the first high-spin neutral diradical, with spin density delocalized within an enantiomeric double helical π-system. The presence of two effective 3-electron C–N bonds in the diradical leads to: (1) the triplet (S = 1) high-spin ground state with a singlet-triplet energy gap of 0.4 kcal mol–1 and (2) the long half-life of up to 6 days in 2-MeTHF at room temperature. The diradical possesses a racemization barrier of at least 26 kcal mol–1 in 2-MeTHF at 293 K and chiroptical properties, with an absorption anisotropy factor |g| ≈ 0.005 at 548 nm. These unique magnetic and optical properties of our diradical form the basis for the development of next-generation spintronic devices.1	Introduction2	Synthesis and Resolution of the C
2-Symmetric Double Helical Tetraamine 2-H2-C
2
3	Synthesis and Characterization of Neutral High-Spin Aminyl Diradical 22•
-C
2
4	Conclusion
Evaluating the Diagnostic Role of ACR-TIRADS and Bethesda
Classifications in Thyroid Nodules Highlighted by Cyto-Histopathological
Studies
Authors: Eissa Marwa S. , Sabry Rania M. , Abdellateif Mona S. 
Published: August 2024

Abstract
Objective To evaluate the accuracy of thyroid imaging reporting and data
system (ACR-TIRADS) and the Bethesda system for reporting cytopathology (TBSRCP)
classifications for identifying or ruling out thyroid malignancy in relation to
the gold standard (post-surgical pathology).
Methods This cross-sectional study included 573 patients with single or
multiple thyroid nodules. Patients were evaluated using the TIRADS and the
TBSRCP classification. The data from a cohort of patients who underwent surgery
(77/573, 13.4%) were correlated with post-operative pathology and the relevant
clinical features of the patients.
Results Of 573 patients, 545 (95.1%) were euthyroid, 24 (4.1%) were
hypothyroid, and 4 (0.8%) were hyperthyroid; 419 (73.1%) had benign nodules
(Bethesda II), 115 (20.1%) had intermediate (Bethesda III, IV), and 39 (6.8%)
had Bethesda V and VI nodules. Four-hundred twenty (73.3%) patients were
categorized as TIRADS 2,3, and 153 (26.7%) were categorized as TIRADS 4,5. The
Bethesda and TIRADS classifications concorded significantly in thyroid nodule
diagnosis (K=14.9%, P<0.001).Thyroid malignancy was significantly associated with microcalcification and
interrupted halo, while benign nodules were significantly associated with
macrocalcification and complete halo type (P=0.041, P=0.005, respectively). The TBSRCP could significantly detect malignant thyroid nodules with a
sensitivity, specificity, PPV, and NPV of 64.1%, 98.1%, 85.0%, and 94.1%,
respectively (K=88.2%, P<0.001), while the respective values for the TIRADS
classification were 63.5%, 76.0%, 84.6%, and 50.0% (K=34.8%, P=0.001).
Conclusion The TIRADS and TBSRCP are essential primary steps for
evaluating thyroid nodules and both are complimentary. Hence, each patient with
thyroid nodules should be evaluated by both approaches before opting for
surgery. Highly suspicious TIRADS categories TR4 and TR5 need further evaluation
by fine needle aspiration cytology.
Direct Multicomponent Synthesis of C3-Arylated Pyrroles under Catalyst-Free Conditions
Authors: Kumar Indresh , Pawar Amol Prakash , Jangir Reena , Dolas Atul Jankiram , Nagare Yadav Kacharu , Rangan Krishnan , Iype Eldhose 
Published: August 2024

AbstractAn operationally simple catalyst-free protocol for the direct regiospecific synthesis of C3-arylated/alkenylated pyrroles has been developed. The enamine-intermediate, in situ generated from succinaldehyde and a primary amine, was trapped with activated carbonyls before the Paal–Knorr reaction in a direct multicomponent ‘just-mix’ protocol to furnish pyrroles in good yields. Several C3-substituted N-alkylpyrroles have been prepared under open-flask conditions, avoiding protection-deprotection chemistry.
Oxidation of Eugenol Derivatives with KMnO4 and CrO3
Authors: Abdou Achraf , Dakir Mohamed , Maaghloud Fatima Ezzahra , Tumanov Nikolay , Wouters Johan , JamalEddine Jamal , Elmakssoudi Abdelhakim 
Published: August 2024

AbstractThis study aims to delineate the synthesis of eugenol derivatives, starting with hydroxyl group protection and then the subsequent oxidation stages. Initially, eugenol underwent conversion into acetyleugenol and benzyleugenol during the protection phase. Subsequently, a kinetic oxidation of acetyleugenol with KMnO4 via GC-MS analysis resulted in the identification of four compounds. The kinetic investigation indicated the primary formation of diolacetyleugenol, succeeded by aldehyde eugenol, which further gets converted into its respective carboxylic acid. Additionally, acetyleugenol and benzyleugenol underwent oxidation with CrO3, yielding the corresponding carboxylic acids.
Exploring the Role of Homeopathic Intervention in Post-COVID Functional Gastrointestinal Disorders: A Case Series of 12 Patient Profiles
Authors: Ponnam Hima Bindu , Chirravuri Siva Subrahmanyam , Konduru Shanmukha Priya , Jammalamadaka Swathi 
Published: August 2024

Abstract
Background In the last 2 years of the pandemic, a wide range of cases of post-COVID functional gastrointestinal disorders (PC-FGIDs) has been reported.
Aim This case series aimed to investigate the role of homeopathic intervention in the treatment of PC-FGIDs.
Methods This is a retrospective analysis of the clinical data of individuals who had suffered from PC-FGIDs that were diagnosed based on clinical symptoms using the Gastrointestinal Symptoms Rating Scale (GSRS) and treated exclusively with individualized homeopathic medicines. Cases that had undergone regular monthly assessment using the GSRS and had a Post-COVID-19 Functional Status (PCFS) score for up to 3 months were considered.
Results Thirty cases were screened and twelve were included according to the study criteria. The mean age of seven women and five men was 36 years. GSRS and PCFS scores showed marked improvement in each of 10 cases within the 3-month treatment period.
Conclusion Homeopathic intervention proved beneficial in 10 of 12 patients with PC-FGIDs. The findings may help researchers plan future controlled clinical studies in this field.