bluuebunny/crossref_metadata_2025_split huggingface dataset:
Selective enrichment of plasma cell-free messenger RNA in cancer-associated extracellular vesicles
Authors: Kim Hyun Ji , Rames Matthew J. , Goncalves Florian , Kirschbaum C. Ward , Roskams-Hieter Breeshey , Spiliotopoulos Elias , Briand Josephine , Doe Aaron , Estabrook Joseph , Wagner Josiah T. , Demir Emek , Mills Gordon , Ngo Thuy T. M. 
Published: August 2023

AbstractExtracellular vesicles (EVs) have been shown as key mediators of extracellular small RNA transport. However, carriers of cell-free messenger RNA (cf-mRNA) in human biofluids and their association with cancer remain poorly understood. Here, we performed a transcriptomic analysis of size-fractionated plasma from lung cancer, liver cancer, multiple myeloma, and healthy donors. Morphology and size distribution analysis showed the successful separation of large and medium particles from other soluble plasma protein fractions. We developed a strategy to purify and sequence ultra-low amounts of cf-mRNA from particle and protein enriched subpopulations with the implementation of RNA spike-ins to control for technical variability and to normalize for intrinsic drastic differences in cf-mRNA amount carried in each plasma fraction. We found that the majority of cf-mRNA was enriched and protected in EVs with remarkable stability in RNase-rich environments. We observed specific enrichment patterns of cancer-associated cf-mRNA in each particle and protein enriched subpopulation. The EV-enriched differentiating genes were associated with specific biological pathways, such as immune systems, liver function, and toxic substance regulation in lung cancer, liver cancer, and multiple myeloma, respectively. Our results suggest that dissecting the complexity of EV subpopulations illuminates their biological significance and offers a promising liquid biopsy approach.
Reduced ADP off-rate by the yeast CCT2 double mutation T394P/R510H which causes Leber congenital amaurosis in humans
Authors: Roy Mousam , Fleisher Rachel C. , Alexandrov Alexander I. , Horovitz Amnon 
Published: August 2023

AbstractThe CCT/TRiC chaperonin is found in the cytosol of all eukaryotic cells and assists protein folding in an ATP-dependent manner. The heterozygous double mutation T400P and R516H in subunit CCT2 is known to cause Leber congenital amaurosis (LCA), a hereditary congenital retinopathy. This double mutation also renders the function of subunit CCT2, when it is outside of the CCT/TRiC complex, to be defective in promoting autophagy. Here, we show using steady-state and transient kinetic analysis that the corresponding double mutation in subunit CCT2 from Saccharomyces cerevisiae reduces the off-rate of ADP during ATP hydrolysis by CCT/TRiC. We also report that the ATPase activity of CCT/TRiC is stimulated by a non-folded substrate. Our results suggest that the closed state of CCT/TRiC is stabilized by the double mutation owing to the slower off-rate of ADP, thereby impeding the exit of CCT2 from the complex that is required for its function in autophagy.
A G1528C Hadha knock-in mouse model recapitulates aspects of human clinical phenotypes for long-chain 3-hydroxyacyl-CoA dehydrogenase deficiency
Authors: Gaston Garen , Babcock Shannon , Ryals Renee , Elizondo Gabriela , DeVine Tiffany , Wafai Dahlia , Packwood William , Holden Sarah , Raber Jacob , Lindner Jonathan R. , Pennesi Mark E. , Harding Cary O. , Gillingham Melanie B. 
Published: August 2023

AbstractLong chain 3-hydroxyacyl-CoA dehydrogenase deficiency (LCHADD) is a fatty acid oxidation disorder (FAOD) caused by a pathogenic variant, c.1528 G > C, in HADHA encoding the alpha subunit of trifunctional protein (TFPα). Individuals with LCHADD develop chorioretinopathy and peripheral neuropathy not observed in other FAODs in addition to the more ubiquitous symptoms of hypoketotic hypoglycemia, rhabdomyolysis and cardiomyopathy. We report a CRISPR/Cas9 generated knock-in murine model of G1528C in Hadha that recapitulates aspects of the human LCHADD phenotype. Homozygous pups are less numerous than expected from Mendelian probability, but survivors exhibit similar viability with wildtype (WT) littermates. Tissues of LCHADD homozygotes express TFPα protein, but LCHADD mice oxidize less fat and accumulate plasma 3-hydroxyacylcarnitines compared to WT mice. LCHADD mice exhibit lower ketones with fasting, exhaust earlier during treadmill exercise and develop a dilated cardiomyopathy compared to WT mice. In addition, LCHADD mice exhibit decreased visual performance, decreased cone function, and disruption of retinal pigment epithelium. Neurological function is affected, with impaired motor function during wire hang test and reduced open field activity. The G1528C knock-in mouse exhibits a phenotype similar to that observed in human patients; this model will be useful to explore pathophysiology and treatments for LCHADD in the future.
Atomistic modeling of liquid-liquid phase equilibrium explains dependence of critical temperature on γ-crystallin sequence
Authors: Qin Sanbo , Zhou Huan-Xiang 
Published: August 2023

AbstractLiquid-liquid phase separation of protein solutions has regained heightened attention for its biological importance and pathogenic relevance. Coarse-grained models are limited when explaining residue-level effects on phase equilibrium. Here we report phase diagrams for γ-crystallins using atomistic modeling. The calculations were made possible by combining our FMAP method for computing chemical potentials and Brownian dynamics simulations for configurational sampling of dense protein solutions, yielding the binodal and critic temperature (Tc). We obtain a higher Tc for a known high-Tc γ-crystallin, γF, than for a low-Tc paralog, γB. The difference in Tc is corroborated by a gap in second virial coefficient. Decomposition of inter-protein interactions reveals one amino-acid substitution between γB and γF, from Ser to Trp at position 130, as the major contributor to the difference in Tc. This type of analysis enables us to link phase equilibrium to amino-acid sequence and to design mutations for altering phase equilibrium.
Field-tuned quantum renormalization of spin dynamics in the honeycomb lattice Heisenberg antiferromagnet YbCl3
Authors: Sala Gabriele , Stone Matthew B. , Halász Gábor B. , Lumsden Mark D. , May Andrew F. , Pajerowski Daniel M. , Ohira-Kawamura Seiko , Kaneko Koji , Mazzone Daniel G. , Simutis Gediminas , Lass Jakob , Kato Yasuyuki , Do Seung-Hwan , Lin Jiao Y. Y. , Christianson Andrew D. 
Published: August 2023

AbstractThe basis for our understanding of quantum magnetism has been the study of elegantly simple model systems. However, even for the antiferromagnetic honeycomb lattice with isotropic spin interactions–one of the simplest model systems–a detailed understanding of quantum effects is still lacking. Here, using inelastic neutron scattering measurements of the honeycomb lattice material YbCl3, we elucidate how quantum effects renormalize the single-magnon and multimagnon excitations and how this renormalization can be tuned and ultimately driven to the classical limit by applying a magnetic field. Additionally, our work reveals that the quantum effects tuned by the magnetic field not only renormalize the magnetic excitations but also induce a distinctive sharp feature inside the multimagnon continuum. From a more general perspective, this result demonstrates that structures within magnetic continua can occur over a wide experimental parameter space and can be used as a reliable means of identifying quantum phenomena.
Neural Correlates of Morphosyntactic Processing in Spanish–English Bilingual Children: A Functional Near-Infrared Spectroscopy Study
Authors: Baron Alisa , Wagley Neelima , Hu Xiaosu , Kovelman Ioulia 
Published: August 2023

Purpose:The aim of this study was to examine the effects of early bilingual exposure on Spanish–English bilingual children's neural organization of English morphosyntactic structures. This study examines how children's age and language experiences are related to morphosyntactic processing at the neural level.Method:Eighty-one children (ages 6–11 years) completed an auditory sentence judgment task during functional near-infrared spectroscopy neuroimaging. The measure tapped into children's processing of early-acquired (present progressive –ing) and later-acquired (past tense –edand third-person singular –s) English morphosyntactic structures, the primary language of academic instruction.Results:We observed effects of syntactic structure and age. Early-acquired morphemic structures elicited activation in the left inferior frontal gyrus, while the later-acquired structures elicited additional activations in the left middle temporal gyrus and superior temporal gyrus (STG). Younger children had a more distributed neural response, whereas older children had a more focal neural response. Finally, there was a trending association between children's English language use and left STG activation for later-acquired structures.Conclusion:The findings inform theories of language and brain development by highlighting the mechanisms by which age and language experiences influence bilingual children's neural architecture for morphosyntactic processing.
A latent topic‐aware network for dense video captioning
Authors: Xu Tao , Cui Yuanyuan , He Xinyu , Liu Caihua 
Published: August 2023

AbstractMultiple events in a long untrimmed video possess the characteristics of similarity and continuity. These characteristics can be considered as a kind of topic semantic information, which probably behaves as same sports, similar scenes, same objects etc. Inspired by this, a novel latent topic‐aware network (LTNet) is proposed in this article. The LTNet explores potential themes within videos and generates more continuous captions. Firstly, a global visual topic finder is employed to detect the similarity among events and obtain latent topic‐level features. Secondly, a latent topic‐oriented relation learner is designed to further enhance the topic‐level representations by capturing the relationship between each event and the video themes. Benefiting from the finder and the learner, the caption generator is capable of predicting more accurate and coherent descriptions. The effectiveness of our proposed method is demonstrated on ActivityNet Captions and YouCook2 datasets, where LTNet shows a relative performance of over 3.03% and 0.50% in CIDEr score respectively.
Cross‐domain extendable gesture recognition system using WiFi signals
Authors: Qin Yuxi , Pan Su , Li Zibo 
Published: August 2023

AbstractThis letter proposes a cross‐domain WiFi‐based gesture recognition system (WiCross) based on a dynamically weighted multi‐label generative adversarial network. Most existing WiFi‐based gesture recognition systems are user, orientation, and environment sensitive, which limits the application of WiFi sensing. Compared with the influence of users and environments on WiFi sensing systems, the influence of orientation on WiFi sensing systems is more difficult to remove. To alleviate the confusion caused by the orientation more effectively, we arrange the transmitting and receiving antennas according to the characteristics of the Fresnel region. It is proposed to dynamically weight different links according to users' orientations and use a multi‐label generative adversarial network to obtain domain‐independent features. More importantly, WiCross can use domain‐independent features to classify some unknown gestures without modifying any code or dataset. Lightweight computing resource consumption allows WiCross to respond in real time. The experimental results show that WiCross can achieve an in‐domain recognition accuracy of 93.54% and a cross‐domain recognition accuracy of 93.11%.
How to select the electronic target for robot trajectory tracking Lyapunov‐based controllers: Comparative study and experimental results
Authors: Losada‐Gutiérrez Cristina , Rodríguez‐Ascariz José M. , Espinosa Felipe 
Published: August 2023

AbstractThe proper sizing of the electronic target to implement complex controllers is barely tackled at engineering schools. An incorrect selection leads, at best, to inefficient use of resources and unnecessarily high costs. In this work, the criteria to implement the electronic Lyapunov‐based controller for non‐linear trajectory tracking of a P3‐DX robot is focused on. After comparing pros and cons of the four alternatives, test results are shown with two of them: NUC8i5INH microcomputer and STM32F767 single chip board.
Robust optimisation of electricity‐heating integrated energy system based on data‐driven PV interval estimation
Authors: Xu Tao , Liu Zuozheng , Guo Lingxu , Meng He , Wang Rujing , Li Mengchao , Cai Shuqi 
Published: August 2023

AbstractShort‐term interval estimation can effectively and precisely quantify the uncertainties of renewable energy, accurately represent the range of fluctuations of uncertain variables in robust optimisation of electricity‐heating integrated energy system (EHIES) and it is getting crucial for reliable and flexible operation of renewable dominated new energy systems. The authors present a multivariate data‐driven short‐term PV power interval prediction model that consists of multiple layers, including one‐dimensional convolutional layer, ultra‐lightweight subspace attention mechanism (ULSAM), bidirectional long and short‐term memory (BiLSTM), quantile regression (QR) and kernel density estimation (KDE). The one‐dimensional convolutional layer and ULSAM can extract sequential features and highlight key information from the data; the BiLSTM processes time series data in both directions and conveys historical information; the QR and KDE models generate interval prediction with a given confidence level. Based on the proposed interval estimation, a refined PV uncertainty set can be established and adopted by robust optimal scheduling of EHIES utilising min‐max‐min algorithm. The simulation results have demonstrated the estimation accuracy and adaptability to various weather scenarios.
Multidimensional coupled structure‐activity relationship models for replacement of SF6
Authors: Zhang Mi , Hou Hua , Wang Baoshan 
Published: August 2023

AbstractComputational screening of single gases to replace SF6 for electrical insulation has been challenged by the difficulty in combining various mutually exclusive properties especially for dielectric performance with liquefaction and environmental properties. To reveal the inherent correlations between dielectric strength (Er), boiling point (Tb), and global warming potential (GWP) of dielectric materials, a coupled structure‐activity relationship (CSAR) model has been proposed for the first time. By means of the generic descriptors, as deduced from the electrostatic potentials, and the specific descriptors, as introduced from the respective microscopic mechanisms, the complex interdependence between Er, Tb, and GWP of the insulation gases is quantitatively characterised by the 3‐D coupling matrix. The coupling mechanism for the right balance of properties is uncovered in terms of the first‐principle descriptors. The CSAR model outperforms the previous SAR models in predicting Er, Tb, and GWP simultaneously in a self‐consistent manner. More importantly, the concept of CSAR could be extended readily to any multidimensional macroscopic properties. Novel replacement compounds have been identified tentatively to be the promising candidates to replace SF6 using the CSAR model.
Evaluating efficiency of railway transportation based on cross‐efficiency evaluation method and relative entropy evaluation method in China
Authors: Zhang Liangliang , Hua Xiukun 
Published: August 2023

AbstractRailway transportation system is one of the most important components of the integrated transportation system. A functional and efficient railway transportation system can be conducive to sustainable development of society and economy, thus highlighting the importance of studies on railway transportation efficiency. Therefore, this research proposes the cross‐efficiency evaluation method based on the relative entropy evaluation method (CERE) to evaluate railway transportation efficiency in China. Firstly, the research constructs an evaluation indicators system for railway transportation efficiency from the perspective of input‐output. Secondly, the paper obtains cross‐efficiency matrix by using the cross‐efficiency evaluation method (CE). Then, the study takes the obtained the cross‐efficiency matrix as the decision matrix of multiple criteria decision‐making (MCDM) problem, and applies the relative entropy evaluation method to evaluate the efficiency of railway transportation. Finally, the empirical analysis of the efficiency evaluation results for 18 railway transportation companies shows that, in 2019, Taiyuan Railway Transportation Company has the highest efficiency score, owing probably to a greater coal railway transportation demand and an advanced railway heavy haul transportation technology; railway transportation companies in the Eastern China typically have the highest efficiency scores, owing probably to a greater regional railway transportation demand.
Probabilistic optimal power flow in wind energy integrated power system based on the K‐medoids data clustering method considering correlated uncertain variables
Authors: Badoozadeh Saeed , Nikdel Nazila , Galvani Sadjad , Farhadi‐Kangarlu Mohammad 
Published: August 2023

AbstractRenewable energy sources have increasingly been integrated into power systems because of their superior environmental, technical, and economic advantages. However, the uncertainty of these sources besides load fluctuations and equipment outages brings new challenges to power system operating and planning studies. Also, the correlation between uncertain variables makes operational decisions more and more complicated. Probabilistic assessment of power systems is essential to evaluate uncertainties’ effects and make reasonable decisions. Methods with high accuracy and low computational burden are efficient for online and fast requirements such as optimal power flow (OPF) problems. A clustering method based on the K‐medoids technique is used for the probabilistic assessment of the power system in the OPF problem. Unlike other clustering techniques the K‐medoids method can manage discrete variables such as equipment outages besides other continuous variables such as load and wind generation. This paper presents an OPF problem considering the uncertainty of renewable energy sources, load fluctuations, and transmission lines outage as well as the correlation among them. The probabilistic assessment is conducted by the K‐medoids method and the optimization problem is solved by the cooperation search algorithm (CSA) as an efficient evolutionary algorithm. Numerical results using the IEEE standard 30 and 118 bus test systems show the efficiency of the proposed method in terms of accuracy and computational burden.
Proposed sub‐synchronous resonance damping controller for large‐scale wind farms
Authors: Moradi‐Shahrbabak Zahra 
Published: August 2023

AbstractThis paper deals with the mitigation of sub‐synchronous resonance (SSR) in doubly‐fed induction generator (DFIG)‐based wind farms using a sub‐synchronous resonance damping controller (SSRDC). The performance of the SSRDC depends on its input control signal and the location of its output control signals. Hence, this paper presents an algorithm to select the best location for applying the SSRDC. The DFIG parameters are used as the inputs of this algorithm. Also, the participation factors analysis is employed as this algorithm's main core. The output of this algorithm determines that the control signal of SSRDC can be applied either in the grid‐side converter (GSC) and/or in the rotor‐side converter (RSC). The best input location in the GSC is the DC‐link voltage and the best input location in the RSC is the q‐component of the rotor voltage. The accuracy of this algorithm was evaluated by investigating the effect of various input signal locations on the SSR using the eigenvalue analysis. This analysis indicated that the dc‐link voltage and the q‐components of the rotor voltage are the most effective signals on the sub‐synchronous oscillatory modes. Moreover, this paper introduces a new SSRDC using these two signals. The performance of this controller is validated through the eigenvalue analysis and a time domain simulation.
Business model innovation and export performance
Authors: Najafi-Tavani Zhaleh , Zantidou Eleni , Leonidou Constantinos N. , Zeriti Athina 
Published: August 2023

AbstractAlthough business model innovation (BMI) is generally beneficial for firms, few studies have investigated whether and under what conditions BMI benefits materialize in foreign markets. This research applies two complementary theoretical perspectives to understand the role of BMI in helping firms achieve enhanced performance in export markets. We argue that the effectiveness of the two types of BMI (novelty- and efficiency-centered) is influenced by factors such as relational embeddedness, international experience, and competitive intensity. Using primary data from 263 managers and CEOs from 194 exporting firms, we find that novelty- and efficiency-centered BMI boosts performance by strengthening exporters’ differentiation and cost advantages, respectively. We also show that for firms operating in mildly competitive environments and in a narrow set of countries, novelty-centered BMI is more likely to lead to a differentiation advantage. At the same time, exporters can attain greater cost advantages from efficiency-centered BMI if they have established strong relationships with their export customers/buyers and have been internationally active for a long time. Managers might need to pay close attention to the level of competition, as it can have both positive and negative implications for advantage-driven export performance outcomes.
Weaving the algorithm: participatory subjectivities amongst food delivery riders
Authors: Allen-Perkins Diego , Cañedo-Rodríguez Montserrat 
Published: August 2023

AbstractThe platform economy is an ecosystem of algorithmically-organised social–technical relationships. In the specific area of home food delivery via digital platforms, algorithmic mediation motivates agents to act in specific ways based on algorithmic logic, creating a distinct form of subjectivity. Based on an ethnography carried out with delivery riders in the City of Madrid (Spain) between 2021 and 2023, in this paper we explore the concept of participatory subjectivity, proposing a distinction between three categories: (a) systems in which the delivery worker seeks algorithmic recognition, (b) systems in which users act in such a way as to be ignored by the algorithm and (c) systems in which it is the design of the algorithms themselves that fosters participation by users. We believe that the concept of participatory subjectivity contributes to the debate on algorithmic mediation in the platform economy, while also affording new perspectives on its effects on workers.