bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distributed fixed‐time sliding mode formation control for unmanned aerial‐ground vehicle (UAV‐UGV) heterogeneous system
Authors: Guo Xing , Li Qing , Yao Qijia , Lu Xiaoya 
Published: November 2024

AbstractThis study proposes a distributed fixed‐time sliding mode formation control (FTSMFC) method to address formation control problem for unmanned aerial‐ground vehicle (UAV‐UGV) heterogeneous system under the directed topology and subject to external disturbances. First, a distributed fixed‐time state observer (FTSO) is introduced to provide state estimation of the leader UAV, which overcomes the limitation of partial information availability among followers. Then, a novel fixed‐time disturbance observer (FTDO) is presented to enhance the system's anti‐disturbance ability by estimating and compensating external disturbances within a fixed time. Furthermore, by integrating sliding mode techniques and the information from the FTSO and FTDO, a distributed FTSMFC is developed to enforce the system to achieve predefined formation configuration within a fixed time independent of initial states of the system. Finally, a simulation comparison with the other controllers is carried out to show the validity and superiority of the proposed formation control law.
Accelerating Brain MR Imaging With Multisequence and Convolutional Neural Networks
Authors: Mo Zhanhao , Sui He , Lv Zhongwen , Huang Xiaoqian , Li Guobin , Shen Dinggang , Liu Lin , Liao Shu 
Published: November 2024

ABSTRACTPurposeMagnetic resonance imaging (MRI) refers to one of the critical image modalities for diagnosis, whereas its long acquisition time limits its application. In this study, the aim was to investigate whether deep learning–based techniques are capable of using the common information in different MRI sequences to reduce the scan time of the most time‐consuming sequences while maintaining the image quality.MethodFully sampled T1‐FLAIR, T2‐FLAIR, and T2WI brain MRI raw data originated from 217 patients and 105 healthy subjects. The T1‐FLAIR and T2‐FLAIR sequences were subsampled using Cartesian masks based on four different acceleration factors. The fully sampled T1/T2‐FLAIR images were predicted from undersampled T1/T2‐FLAIR images and T2WI images through deep learning–based reconstruction. They were qualitatively assessed by two senior radiologists in accordance with the diagnosis decision and a four‐point scale image quality score. Furthermore, the images were quantitatively assessed based on regional signal‐to‐noise ratios (SNRs) and contrast‐to‐noise ratios (CNRs). The chi‐square test was performed, where p < 0.05 indicated a difference with statistical significance.ResultsThe diagnosis decisions from two senior radiologists remained unchanged in accordance with the accelerated and fully sampled images. There were no significant differences in the regional SNRs and CNRs of most assessed regions (p > 0.05) between the accelerated and fully sampled images. Moreover, no significant difference was identified in the image quality assessed by two senior radiologists (p > 0.05).ConclusionDeep learning–based image reconstruction is capable of significantly expediting the brain MR imaging process and producing acceptable image quality without affecting diagnosis decisions.
Establishment of a Novel Risk Stratification System Integrating Clinical and Pathological Parameters for Prognostication and Clinical Decision‐Making in Early‐Stage Cervical Cancer
Authors: Wu Haiying , Huang Lin , Chen Xiangtong , OuYang Yi , Li JunYun , Chen Kai , Huang Xiaodan , Chen Foping , Cao XinPing 
Published: November 2024

ABSTRACTBackgroundHighly heterogeneity and inconsistency in terms of prognosis are widely identified for early‐stage cervical cancer (esCC). Herein, we aim to investigate for an intuitional risk stratification model for better prognostication and decision‐making in combination with clinical and pathological variables.MethodsWe enrolled 2071 CC patients with preoperative biopsy‐confirmed and clinically diagnosed with FIGO stage IA‐IIA who received radical hysterectomy from 2013 to 2018. Patients were randomly assigned to the training set (n = 1450) and internal validation set (n = 621), in a ratio of 7:3. We used recursive partitioning analysis (RPA) to develop a risk stratification model and assessed the ability of discrimination and calibration of the RPA‐derived model. The performances of the model were compared with the conventional FIGO 2018 and 9th edition T or N stage classifications.ResultsRPA divided patients into four risk groups with distinct survival: 5‐year OS for RPA I to IV were 98%, 95%, 85.5%, and 64.2%, respectively, in training cohort; and 99.5%, 93.2%, 85%, and 68.3% in internal validation cohort (log‐rank p < 0.001). Calibration curves confirmed that the RPA‐predicted survivals were in good agreement with the actual survivals. The RPA model outperformed the existing staging systems, with highest AUC for OS (training: 0.778 vs. 0.6–0.717; internal validation: 0.772 vs. 0.595–0.704; all p < 0.05), and C‐index for OS (training: 0.768 vs. 0.598–0.707; internal validation: 0.741 vs. 0.583–0.676; all p < 0.05). Importantly, there were associations between RPA groups and the efficacy of treatment regimens. No obvious discrepancy was observed among different treatment modalities in RPA I (p = 0.922), whereas significant survival improvements were identified in patients who received adjuvant chemoradiotherapy in RPA II–IV (p value were 0.028, 0.036, and 0.024, respectively).ConclusionWe presented a validated novel clinicopathological risk stratification signature for robust prognostication of esCC, which may be used for streamlining treatment strategies.
Rapid Detection of Stabilizer Content in Double‐Base Propellant Based on Artificial Neural Network Combined With Near‐Infrared Spectroscopy
Authors: Ouyang Dihua , Cui Tianyu , Zhang Qiantao , Dai Haoxiang , Qin Xiaowen , Hu Yaoli 
Published: November 2024

ABSTRACTDuring long‐term storage, double‐base propellants are prone to chemical decomposition of internal nitrate esters, leading to decreased burn rate, reduced strength, and degraded ballistic performance. Adding an appropriate amount of Centralite‐II is crucial for ensuring storage safety. This study proposes a novel method combining near‐infrared spectroscopy (NIRS) with artificial intelligence to rapidly and non‐destructively detect the content of Centralite‐II in double‐base propellants. The optimal modeling wavelength ranges of 4000–4600 cm−1 and 5700–6100 cm−1 were identified, and the raw spectral data were preprocessed using standard normal variate (SNV) transformation to improve the signal‐to‐noise ratio. Principal component analysis (PCA) was then applied to reduce data dimensionality, and the first three principal components were used as inputs for a backpropagation (BP‐ANN) neural network. The resulting PCA‐BP‐ANN model showed excellent performance on the training set, with an
of 0.9830 and an
of 0.0376%. During independent validation, the model demonstrated strong generalization ability, achieving an
of 0.9824 and an
of 0.3179%, comparative analysis with other models, including BP, PLS, ELM, SVR, and LSTM, indicated that the PCA‐BP‐ANN model exhibited superior prediction accuracy and generalization capability. This method provides a rapid and non‐destructive approach for assessing the stabilizer content in double‐base propellants and expands the application of NIRS and AI techniques in the field of energetic materials.
Detecting EPO in Microvolumetric Capillary Serum Shipped at Ambient Temperature for Antidoping Testing
Authors: Miller Geoffrey D. , Goodrum Jenna M. , Flores America K. , Crouch Andre K. , Eichner Daniel 
Published: November 2024

ABSTRACTErythropoietin receptor agonist (ERA) testing for antidoping can be achieved in both urine and blood samples. Recent published work showed the comparability between the two matrices and focused on detectability in microvolumetric capillary serum samples collected using the Tasso+ device. Currently, in the antidoping field, blood samples are required to be shipped under cold, temperature‐controlled conditions. However, due to the suggested greater stability of EPO in blood compared to urine, it is believed that blood samples should be viable for ERA analysis if shipped under the ambient, not cold temperature‐controlled conditions to which urine samples are subjected. In this collaborative study with the Ultimate Fighting Championship, microvolumetric capillary serum samples were collected in the field and shipped under ambient conditions to the laboratory for ERA analysis. Resulting data showed that endogenous EPO was detectable in 100% of these samples, showing no loss in detectability despite shipping under non‐controlled conditions. Further, ERA analyses were conducted in the laboratory on additional in‐house collected samples and post‐EPO administration samples subjected to various storage and shipping conditions, also showing reliable endogenous and recombinant EPO detectability in all samples except those experiencing extreme temperature (50°C) conditions. Taken together, these data highlight the stability of EPO in blood samples and show that ERA blood samples can be collected in the field and shipped without costly temperature‐controlled shipping methods and without a loss in detectability.
Engaged Onlooking: How Organisational Identification Shapes Public Condoning of Corporate Corruption
Authors: Neville Fergus G. , Haslam S. Alexander , Homan Maaike , Reicher Stephen D. , Steffens Niklas K. 
Published: November 2024

ABSTRACTWe examine how social identity processes shape condoning of organisational corruption among onlookers. Two studies examined the willingness of outside observers to condone, or else condemn, corrupt actions of real organisations, a process we call ‘engaged onlookership’ building on the social identity approach to engaged followership. In both Study 1 (cross‐sectional) and Study 2 (experimental), we found that identification with a company guilty of malfeasance and identification with the monitoring agency who uncovered their scandal independently predicted opposing effects on condoning corruption, even while controlling for moral identity and demographic factors. These findings were then replicated and extended in Study 3 that made several methodological improvements upon previous studies. Results provided additional evidence of an indirect effect of the manipulation on condoning corruption through company identification. These findings provide support for an engaged onlookership model of corruption which posits that onlookers are more likely to endorse morally problematic behaviour when they believe it is performed by, and in the interests of, an organisation with which they identify.
Exploration of Hydrogen Storage Exhibited by Rh‐Decorated Pristine and Defective Graphenes: A First‐Principles Study
Authors: Ramchiary Amit , Mondal Paritosh 
Published: November 2024

ABSTRACTWe utilized density functional theory (DFT) to ascertain the storage of hydrogen in Rh‐decorated pristine (PG) and defective graphenes, primarily graphitic‐N (GNG) and pyridinic‐N (PNG). The binding energy of a single Rh atom on PG, GNG, and PNG was found to be −1.87, −2.18, and −4.01 eV, respectively. PG exhibits a weak adsorption energy of hydrogen molecules (−0.06 eV/H2). On the other hand, Rh‐decorated pristine and defective graphenes show incredibly higher hydrogen adsorption energy. As per the latest guidelines of the U.S. Department of Energy (DOE), the Rh‐decorated GNG (Rh@GNG) is found to be the best hydrogen storage material out of the three systems investigated here. The single Rh atom‐decorated GNG adsorbs up to 4H2. Uniform decoration of graphene surfaces with Rh atoms is necessary to improve hydrogen storage performance. Both sides of GNG surfaces are decorated with 8Rh atoms, which can adsorb up to 24H2 molecules, with an average adsorption energy of −0.33 eV/H2. The mechanism of H2 adsorption on the host system has been explored based on DFT‐evaluated deformation of charge density, partial density of states (PDOS), and non‐covalent interaction (NCI) plots. For a better understanding of the adsorption process, the diffusion energy barrier of Rh metal is computed using the climbing image nudged elastic band (CI‐NEB) method, and the thermal stability has been evaluated through ab initio molecular dynamics (AIMD) simulations.
An Updated Review on the Mechanisms, Pre‐Clinical and Clinical Comparisons of Nicotinamide Mononucleotide (NMN) and Nicotinamide Riboside (NR)
Authors: Yang Xu , Lu Anni , Guan Xiao , Ying Tianlei , Pan Jingrong , Tan Mingqian , Lu Jun 
Published: November 2024

ABSTRACTThe study of nicotinamide adenine dinucleotide (NAD+) biology has gained popularity recently. Research discovered that two NAD+ biosynthesis intermediates, nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN), are biosynthetic precursors of NAD+, an essential chemical for metabolism. Many studies show that NAD+ levels fall considerably with aging, with NAD+ regeneration in aging animals increasing longevity and enhancing health. According to research on the two molecules, NMN and NR, supplementation with either raises NAD+ levels during aging. The objective of this review is to highlight current developments in the biology of NAD+ in relation to NR or NMN supplement. This review highlightings significant discoveries about NR and NMN supplementation in relation to NAD+ biological activities and health benefits.
Prediction of intrapartum cesarean delivery among women with obesity: A retrospective cohort study
Authors: Gabbai Daniel , Gilboa Itamar , Attali Emmanuel , Yogev Yariv , Lavie Anat 
Published: November 2024

AbstractObjectiveTo determine risk factors and design a clinically based predictive model for the risk of intrapartum cesarean delivery (CD) in women with obesity.MethodsA retrospective cohort study was conducted in a single tertiary medical center between 2012 and 2022 and included all consecutive women with a pre‐gestational body mass index (BMI) ≥30 who planned a trial of labor. Uni‐ and multivariate analyses compared maternal and neonatal characteristics of women who delivered vaginally to those who underwent intrapartum CD. A specific risk prediction score was developed in accordance with the relative risk to predict the need for intrapartum CD.ResultsOf the 5663 women with obesity included in the study cohort, 424 (7.5%) underwent intrapartum CD and 5239 (92.5%) delivered vaginally. The independent risk factors for CD were maternal age >35 years, pre‐gestational BMI category (BMI 35–40 and BMI >40), nulliparity, epidural anesthesia, induction of labor, antibiotic administration during labor, multiple gestation, previous uterine scar, and pre‐eclampsia. The intrapartum CD prediction score model demonstrated predictive performance with 85% sensitivity and 70% specificity.ConclusionScore model for intrapartum CD can be used by caregivers to offer a more informed consultation to women with obesity facing the decision of mode of delivery.
Limited Sampling Strategy for Predicting the Area under Plasma Concentration–Time Curve of Nadolol in Healthy Subjects
Authors: Misaka Shingen , Maejima Yuko , Shimomura Kenju 
Published: November 2024

AbstractNadolol is a hydrophilic β‐adrenoceptor blocker with a relatively long half‐life and negligible metabolism. It is a substrate of P‐glycoprotein and organic anion transporting polypeptide 1A2, and may serve as an in vivo probe drug for the assessment of drug–drug and food–drug interactions mediated by these transporters. In the present study, we aimed to develop limited sampling strategy (LSS) models for predicting the area under the plasma concentration–time curve (AUC0‐∞) of nadolol. Plasma concentration data (Ct) in healthy volunteers reported in four previous studies were randomly divided into a training dataset for model development (n = 15) and a test dataset for model validation (n = 16). By multiple linear regression analysis, we confirmed that four out of the eight models using two time points and all models using three time points met the acceptable criteria. In particular, the three time point models using (C3, C6, and C24) and (C4, C8, and C24) showed better predictive performances with r2 values of 0.983 and 0.980, respectively. In drug interaction studies of nadolol with itraconazole, rifampicin, grapefruit juice, and green tea extract, both LSS models accurately predicted the AUC0‐∞ with percent mean absolute error ≤11% and percent root mean square error ≤12%. In addition, using digitized pharmacokinetic data of nadolol, both LSS models were further validated by predicting the AUC0‐∞ in different doses. The results suggest that the LSS models using three time points allow a reliable prediction of AUC0‐∞ of nadolol in healthy individuals.
Advancing an integrated understanding of land–ocean connections in shaping the marine ecosystems of coastal temperate rainforest ecoregions
Authors: Hunt Brian P. V. , Alin Simone , Bidlack Allison , Diefenderfer Heida L. , Jackson Jennifer M. , Kellogg Colleen T. E. , Kiffney Peter , St. Pierre Kyra A. , Carmack Eddy , Floyd William C. , Hood Eran , Horner‐Devine Alexander R. , Levings Colin , Vargas Cristian A. 
Published: November 2024

AbstractLand and ocean ecosystems are strongly connected and mutually interactive. As climate changes and other anthropogenic stressors intensify, the complex pathways that link these systems will strengthen or weaken in ways that are currently beyond reliable prediction. In this review we offer a framework of land–ocean couplings and their role in shaping marine ecosystems in coastal temperate rainforest (CTR) ecoregions, where high freshwater and materials flux result in particularly strong land–ocean connections. Using the largest contiguous expanse of CTR on Earth—the Northeast Pacific CTR (NPCTR)—as a case study, we integrate current understanding of the spatial and temporal scales of interacting processes across the land–ocean continuum, and examine how these processes structure and are defining features of marine ecosystems from nearshore to offshore domains. We look ahead to the potential effects of climate and other anthropogenic changes on the coupled land–ocean meta‐ecosystem. Finally, we review key data gaps and provide research recommendations for an integrated, transdisciplinary approach with the intent to guide future evaluations of and management recommendations for ongoing impacts to marine ecosystems of the NPCTR and other CTRs globally. In the light of extreme events including heatwaves, fire, and flooding, which are occurring almost annually, this integrative agenda is not only necessary but urgent.
Plasma Carbonization of Sustainable Lignin Fiber‐Derived Papers for Supercapacitor Electrodes
Authors: Schuster Philipp A. , Mirle Chinmaya , Kuske Lisa , Schmidt Frank , Buchmeiser Michael R. , Rohrbach Felix , Bansmann Joachim , Terbrack Stefan , Heuermann Holger , Frank Erik , Kuehne Alexander J. C. 
Published: November 2024

AbstractThe majority of carbon materials on the market are produced from polyacrylonitrile precursor fibers using high‐temperature oven processes. Despite approaches for green carbon fiber precursors, current stabilization and carbonization processes require large amounts of energy and render carbon materials costly and environmentally not sustainable. Here, a plasma carbonization treatment is employed for papers made from lignin/polyvinylpyrrolidone precursor fibers. The process provides carbonization within a timeframe of a few seconds, while the degrees of porosity, conductivity, and hydrophobicity can be tuned. It is shown that the properties of these carbonized papers are suitable for application as supercapacitor electrodes with capacitances in the range of 40 mF g−1 with very good cycling stability dropping by less than 20% over 4000 cycles.
Zinc Finger Protein 263 Augments Autophagy and Promotes Intrahepatic Cholangiocarcinoma Proliferation
Authors: Yan Zaihua , Du Yadan , Chen Yawen , Yang Jian , Zhang Haoyang , Da Mingxu 
Published: November 2024

ABSTRACTIntrahepatic cholangiocarcinoma (ICC) is an aggressive cancer characterized by a poor prognosis. Despite Zinc finger proteins (ZNFs) importance in tumor development and progression, it is unknown how dysregulated ZNF263 contributes to intrahepatic cholangiocarcinoma. This study aimed to determine whether ZNF263 plays an oncogenic role in ICC progression. The microarray of tumor tissues from clinical intrahepatic cholangiocarcinoma was immunohistochemically analyzed for ZNF263. Based on plate colony formation, CCK8, and tumor xenograft models, ZNF263 was assessed for its biological function. Mechanistically, CUT&Tag, RNA‐seq, CHIP‐PCR, Dual luciferase reporter assay, Western blotting, transmission electron microscopy (TEM), and immunohistochemical staining were employed. ZNF263 expression was elevated in intrahepatic cholangiocarcinoma tissues compared to nontumor tissues, which negatively impacted patient outcomes. Notably, ZNF263 overexpression promoted ICC cells proliferation via enhancing autophagy, whereas ZNF263 knockdown inhibited ICC cells proliferation. Furthermore, ZNF263 binds to the enhancer region of ULK1 and mediates its expression. ULK1 over‐expressing ameliorated ZNF263 knockdown‐induced inhibition of CRC proliferation. By activating the ULK1‐autophagy axis, ZNF263 promotes proliferation of ICC and is potentially a prognostic or therapeutic target of ICC.
MR‐zero meets FLASH – controlling the transient signal decay in gradient‐ and RF‐spoiled gradient echo sequences
Authors: Weinmüller Simon , Endres Jonathan , Dang Nam , Stollberger Rudolf , Zaiss Moritz 
Published: November 2024

AbstractPurposeThe complex signal decay during the transient FLASH MRI readout can lead to artifacts in magnitude and phase images. We show that target‐driven optimization of individual RF flip angles and phases can realize near‐ideal signal behavior and mitigate artifacts.MethodsThe differentiable end‐to‐end optimization framework MR‐zero is used to optimize RF trains of the FLASH sequence. We focus herein on minimizing deviations from the ideally spoiled signal by using a mono‐exponential Look–Locker target. We first obtain the transient FLASH signal decay substructure, and then minimize the deviation to the Look–Locker decay by optimizing the individual (i) flip angles, (ii) RF phases, and (iii) flip angles and RF phases. Comparison between measurement and simulation is performed using Pulseq in 1D and 2D.ResultsWe were able to reproduce the complex substructure of the transient FLASH signal decay. All three optimization objectives can bring the real FLASH signal closer to the ideal case, with best results when both flip angles and RF phases are adjusted jointly. This solution outperformed all tested conventional quadratic RF cyclings in terms of (i) matching the Look–Locker target signal, (ii) phase stability, (iii) point spread functions ideality, (iv) robustness against parameter changes, and (v) magnitude and phase image quality. Other target functions for the signal could as well be realized, yet their response is not as general as for the Look–Locker target and needs to be optimized for a specific context.ConclusionIndividual flip angle and RF phase optimization improves the transient signal decay of FLASH MRI sequences.