bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inter-personal motor interaction is facilitated by hand pairing
Authors: Mojtahedi Keivan , Kiani Kimia , Santello Marco , Fu Qiushi 
Published: January 2022

AbstractThe extent to which hand dominance may influence how each agent contributes to inter-personal coordination remains unknown. In the present study, right-handed human participants performed object balancing tasks either in dyadic conditions with each agent using one hand (left or right), or in bimanual conditions where each agent performed the task individually with both hands. We found that object load was shared between two hands more asymmetrically in dyadic than single-agent conditions. However, hand dominance did not influence how two hands shared the object load. In contrast, hand dominance was a major factor in modulating hand vertical movement speed. Furthermore, the magnitude of internal force produced by two hands against each other correlated with the synchrony between the two hands’ movement in dyads. This finding supports the important role of internal force in haptic communication. Importantly, both internal force and movement synchrony were affected by hand dominance of the paired participants. Overall, these results demonstrate, for the first time, that pairing of one dominant and one non-dominant hand may promote asymmetrical roles within a dyad during joint physical interactions. This appears to enable the agent using the dominant hand to actively maintain effective haptic communication and task performance.
Generative adversarial network enables rapid and robust fluorescence lifetime image analysis in live cells
Authors: Chen Yuan-I , Chang Yin-Jui , Liao Shih-Chu , Nguyen Trung Duc , Yang Jianchen , Kuo Yu-An , Hong Soonwoo , Liu Yen-Liang , Rylander H. Grady , Santacruz Samantha R. , Yankeelov Thomas E. , Yeh Hsin-Chih 
Published: January 2022

AbstractFluorescence lifetime imaging microscopy (FLIM) is a powerful tool to quantify molecular compositions and study molecular states in complex cellular environment as the lifetime readings are not biased by fluorophore concentration or excitation power. However, the current methods to generate FLIM images are either computationally intensive or unreliable when the number of photons acquired at each pixel is low. Here we introduce a new deep learning-based method termedflimGANE(fluorescencelifetimeimaging based onGenerativeAdversarialNetworkEstimation) that can rapidly generate accurate and high-quality FLIM images even in the photon-starved conditions. We demonstrated our model is up to 2,800 times faster than the gold standard time-domain maximum likelihood estimation (TD_MLE) and thatflimGANEprovides a more accurate analysis of low-photon-count histograms in barcode identification, cellular structure visualization, Förster resonance energy transfer characterization, and metabolic state analysis in live cells. With its advantages in speed and reliability,flimGANEis particularly useful in fundamental biological research and clinical applications, where high-speed analysis is critical.
Advanced genomics identifies growth effectors for proteotoxic ER stress recovery in Arabidopsis thaliana
Authors: Ko Dae Kwan , Brandizzi Federica 
Published: January 2022

AbstractAdverse environmental and pathophysiological situations can overwhelm the biosynthetic capacity of the endoplasmic reticulum (ER), igniting a potentially lethal condition known as ER stress. ER stress hampers growth and triggers a conserved cytoprotective signaling cascade, the unfolded protein response (UPR) for ER homeostasis. As ER stress subsides, growth is resumed. Despite the pivotal role of the UPR in growth restoration, the underlying mechanisms for growth resumption are yet unknown. To discover these, we undertook a genomics approach in the model plant speciesArabidopsis thalianaand mined the gene reprogramming roles of the UPR modulators, basic leucine zipper28 (bZIP28) and bZIP60, in ER stress resolution. Through a network modeling and experimental validation, we identified key genes downstream of the UPR bZIP-transcription factors (bZIP-TFs), and demonstrated their functional roles. Our analyses have set up a critical pipeline for functional gene discovery in ER stress resolution with broad applicability across multicellular eukaryotes.
Attention modulates neural representation to render reconstructions according to subjective appearance
Authors: Horikawa Tomoyasu , Kamitani Yukiyasu 
Published: January 2022

AbstractStimulus images can be reconstructed from visual cortical activity. However, our perception of stimuli is shaped by both stimulus-induced and top-down processes, and it is unclear whether and how reconstructions reflect top-down aspects of perception. Here, we investigate the effect of attention on reconstructions using fMRI activity measured while subjects attend to one of two superimposed images. A state-of-the-art method is used for image reconstruction, in which brain activity is translated (decoded) to deep neural network (DNN) features of hierarchical layers then to an image. Reconstructions resemble the attended rather than unattended images. They can be modeled by superimposed images with biased contrasts, comparable to the appearance during attention. Attentional modulations are found in a broad range of hierarchical visual representations and mirror the brain–DNN correspondence. Our results demonstrate that top-down attention counters stimulus-induced responses, modulating neural representations to render reconstructions in accordance with subjective appearance.
Elevated microglial oxidative phosphorylation and phagocytosis stimulate post-stroke brain remodeling and cognitive function recovery in mice
Authors: Song Shanshan , Yu Lauren , Hasan Md Nabiul , Paruchuri Satya S. , Mullett Steven J. , Sullivan Mara L. G. , Fiesler Victoria M. , Young Cullen B. , Stolz Donna B. , Wendell Stacy G. , Sun Dandan 
Published: January 2022

AbstractNew research shows that disease-associated microglia in neurodegenerative brains present features of elevated phagocytosis, lysosomal functions, and lipid metabolism, which benefit brain repair. The underlying mechanisms remain poorly understood. Intracellular pH (pHi) is important for regulating aerobic glycolysis in microglia, where Na/H exchanger (NHE1) is a key pH regulator by extruding H+ in exchange of Na+ influx. We report here that post-stroke Cx3cr1-CreER+/−;Nhe1flox/flox (Nhe1 cKO) brains displayed stimulation of microglial transcriptomes of rate-limiting enzyme genes for glycolysis, tricarboxylic acid cycle, and oxidative phosphorylation. The other upregulated genes included genes for phagocytosis and LXR/RXR pathway activation as well as the disease-associated microglia hallmark genes (Apoe, Trem2, Spp1). The cKO microglia exhibited increased oxidative phosphorylation capacity, and higher phagocytic activity, which likely played a role in enhanced synaptic stripping and remodeling, oligodendrogenesis, and remyelination. This study reveals that genetic blockade of microglial NHE1 stimulated oxidative phosphorylation immunometabolism, and boosted phagocytosis function which is associated with tissue remodeling and post-stroke cognitive function recovery.
Trans cohort metabolic reprogramming towards glutaminolysis in long-term successfully treated HIV-infection
Authors: Mikaeloff Flora , Svensson Akusjärvi Sara , Ikomey George Mondinde , Krishnan Shuba , Sperk Maike , Gupta Soham , Magdaleno Gustavo Daniel Vega , Escós Alejandra , Lyonga Emilia , Okomo Marie Claire , Tagne Claude Tayou , Babu Hemalatha , Lorson Christian L. , Végvári Ákos , Banerjea Akhil C. , Kele Julianna , Hanna Luke Elizabeth , Singh Kamal , de Magalhães João Pedro , Benfeitas Rui , Neogi Ujjwal 
Published: January 2022

AbstractDespite successful combination antiretroviral therapy (cART), persistent low-grade immune activation together with inflammation and toxic antiretroviral drugs can lead to long-lasting metabolic flexibility and adaptation in people living with HIV (PLWH). Our study investigated alterations in the plasma metabolic profiles by comparing PLWH on long-term cART(>5 years) and matched HIV-negative controls (HC) in two cohorts from low- and middle-income countries (LMIC), Cameroon, and India, respectively, to understand the system-level dysregulation in HIV-infection. Using untargeted and targeted LC-MS/MS-based metabolic profiling and applying advanced system biology methods, an altered amino acid metabolism, more specifically to glutaminolysis in PLWH than HC were reported. A significantly lower level of neurosteroids was observed in both cohorts and could potentiate neurological impairments in PLWH. Further, modulation of cellular glutaminolysis promoted increased cell death and latency reversal in pre-monocytic HIV-1 latent cell model U1, which may be essential for the clearance of the inducible reservoir in HIV-integrated cells.
GSNOR regulates ganoderic acid content in Ganoderma lucidum under heat stress through S-nitrosylation of catalase
Authors: Liu Rui , Zhu Ting , Chen Xin , Wang Zi , Yang Zhengyan , Ren Ang , Shi Liang , Yu Hanshou , Zhao Mingwen 
Published: January 2022

AbstractAs a master regulator of the balance between NO signaling and protein S-nitrosylation, S-nitrosoglutathione (GSNO) reductase (GSNOR) is involved in various developmental processes and stress responses. However, the proteins and specific sites that can be S-nitrosylated, especially in microorganisms, and the physiological functions of S-nitrosylated proteins remain unclear. Herein, we show that the ganoderic acid (GA) content in GSNOR-silenced (GSNORi) strains is significantly lower (by 25%) than in wild type (WT) under heat stress (HS). Additionally, silencing GSNOR results in an 80% increase in catalase (CAT) activity, which consequently decreases GA accumulation via inhibition of ROS signaling. The mechanism of GSNOR-mediated control of CAT activity may be via protein S-nitrosylation. In support of this possibility, we show that CAT is S-nitrosylated (as shown via recombinant protein in vitro and via GSNORi strains in vivo). Additionally, Cys (cysteine) 401, Cys642 and Cys653 in CAT are S-nitrosylation sites (assayed via mass spectrometry analysis), and Cys401 may play a pivotal role in CAT activity. These findings indicate a mechanism by which GSNOR responds to stress and regulates secondary metabolite content through protein S-nitrosylation. Our results also define a new S-nitrosylation site and the function of an S-nitrosylated protein regulated by GSNOR in microorganisms.
The metabolic stress-activated checkpoint LKB1-MARK3 axis acts as a tumor suppressor in high-grade serous ovarian carcinoma
Authors: Machino Hidenori , Kaneko Syuzo , Komatsu Masaaki , Ikawa Noriko , Asada Ken , Nakato Ryuichiro , Shozu Kanto , Dozen Ai , Sone Kenbun , Yoshida Hiroshi , Kato Tomoyasu , Oda Katsutoshi , Osuga Yutaka , Fujii Tomoyuki , von Keudell Gottfried , Saloura Vassiliki , Hamamoto Ryuji 
Published: January 2022

AbstractHigh-grade serous ovarian carcinoma (HGSOC) is the most aggressive gynecological malignancy, resulting in approximately 70% of ovarian cancer deaths. However, it is still unclear how genetic dysregulations and biological processes generate the malignant subtype of HGSOC. Here we show that expression levels of microtubule affinity-regulating kinase 3 (MARK3) are downregulated in HGSOC, and that its downregulation significantly correlates with poor prognosis in HGSOC patients. MARK3 overexpression suppresses cell proliferation and angiogenesis of ovarian cancer cells. The LKB1-MARK3 axis is activated by metabolic stress, which leads to the phosphorylation of CDC25B and CDC25C, followed by induction of G2/M phase arrest. RNA-seq and ATAC-seq analyses indicate that MARK3 attenuates cell cycle progression and angiogenesis partly through downregulation of AP-1 and Hippo signaling target genes. The synthetic lethal therapy using metabolic stress inducers may be a promising therapeutic choice to treat the LKB1-MARK3 axis-dysregulated HGSOCs.
Thermal synthesis of conversion-type bismuth fluoride cathodes for high-energy-density Li-ion batteries
Authors: Baumgärtner Julian F. , Krumeich Frank , Wörle Michael , Kravchyk Kostiantyn V. , Kovalenko Maksym V. 
Published: January 2022

AbstractTowards enhancement of the energy density of Li-ion batteries, BiF3 has recently attracted considerable attention as a compelling conversion-type cathode material due to its high theoretical capacity of 302 mAh g−1, average discharge voltage of ca. 3.0 V vs. Li+/Li, the low theoretical volume change of ca. 1.7% upon lithiation, and an intrinsically high oxidative stability. Here we report a facile and scalable synthesis of phase-pure and highly crystalline orthorhombic BiF3via thermal decomposition of bismuth(III) trifluoroacetate at T = 300 °C under inert atmosphere. The electrochemical measurements of BiF3 in both carbonate (LiPF6-EC/DMC)- and ionic liquid-based (LiFSI-Pyr1,4TFSI) Li-ion electrolytes demonstrated that ionic liquids improve the cyclic stability of BiF3. In particular, BiF3 in 4.3 M LiFSI-Pyr1,4TFSI shows a high initial capacity of 208 mA g−1 and capacity retention of ca. 50% over at least 80 cycles at a current density of 30 mA g−1.
Unified energy law for fluctuating density wave orders in cuprate pseudogap phase
Authors: Li Rong , She Zhen-Su 
Published: January 2022

AbstractThe quantum origin of the cuprate pseudogap is a central conundrum of condensed matter physics. Although many symmetry-broken scenarios were previously proposed, universal quantitative relationships have been rarely studied. Here, we report a unified energy law underlying the pseudogap, which determines the scattering rate, pseudogap energy, and its onset temperature, with a quadratic scaling of the wavevector of density wave order (DWO). The law is validated by data from over one hundred samples, and a further prediction that the master order of pseudogap transforms from fluctuating spin to charge DWO is also confirmed. Furthermore, the energy law enables our derivation of the well-known linear scalings for the resistivity of the strange metal phase and the transition temperature of the superconducting phase. Finally, it is concluded that fluctuating orders provide a critical bridge linking microscopic spectra to macroscopic transport, showing promise for the quantification of other strongly correlated materials.
Non-zero Yarkovsky acceleration for near-Earth asteroid (99942) Apophis
Authors: Pérez-Hernández Jorge A. , Benet Luis 
Published: January 2022

AbstractThe leading source of uncertainty to predict the orbital motion of asteroid (99942) Apophis is a non-gravitational acceleration arising from the anisotropic thermal re-emission of absorbed radiation, known as the Yarkovsky effect. Previous attempts to obtain this parameter from astrometry for this object have only yielded marginally small values, without ruling out a pure gravitational interaction. Here we present an independent estimation of the Yarkovsky effect based on optical and radar astrometry which includes observations obtained during 2021. Our numerical approach exploits automatic differentiation techniques. We find a non-zero Yarkovsky parameter, A2 = (−2.899 ± 0.025) × 10−14 au d−2, with induced semi-major axis drift of (−199.0 ± 1.5) m yr−1 for Apophis. Our results provide definite collision probability predictions for the close approaches in 2029, 2036, and 2068.
Sustained coral reef growth in the critical wave dissipation zone of a Maldivian atoll
Authors: Kench Paul S. , Beetham Edward P. , Turner Tracey , Morgan Kyle M. , Owen Susan D. , McLean Roger. F. 
Published: January 2022

AbstractSea-level rise is expected to outpace the capacity of coral reefs to grow and maintain their wave protection function, exacerbating coastal flooding and erosion of adjacent shorelines and threatening coastal communities. Here we present a new method that yields highly-resolved direct measurements of contemporary reef accretion on a Maldivian atoll reef rim, the critical zone that induces wave breaking. Results incorporate the suite of physical and ecological processes that contribute to reef accumulation and show growth rates vary from 6.6 ± 12.5 mm.y−1 on the reef crest, and up to 3.1 ± 10.2 mm.y−1, and −0.5 ± 1.8 mm.yr−1 on the outer and central reef flat respectively. If these short-term results are maintained over decades, the reef crest could keep pace with current sea-level rise. Findings highlight the need to resolve contemporary reef accretion at the critical wave dissipation zone to improve predictions of future reef growth, and re-evaluate exposure of adjacent shorelines to coastal hazards.
Tailoring of a highly stable Mn1−x−y(CexLay)O2−δ pseudocapacitor thin-film and rare earth oxide nanospheres through selective purification of rare earth oxides derived from Ni–MH batteries
Authors: Maroufi Samane , Mofarah Sajjad S. , Khayyam Nekouei Rasoul , Sahajwalla Veena 
Published: January 2022

High-yield fabrication of two value-added functional nanostructures including a defect-rich Mn1−x−y(CexLay)O2−δ film and rare earth oxide (REO) nanospheres via selective purification of REO isolated from end-of-life nickel–metal hydride batteries.
Sensor fault detection for dynamic point‐the‐bit rotary steerable system via finite‐frequency domain observer and zonotope residual evaluation
Authors: Wang Weiliang , Geng Yanfeng , Cheng Minbiao , Sun Jian , Sheng Li 
Published: January 2022

AbstractIn this paper, the sensor fault detection (FD) problem is investigated for the dynamic point‐the‐bit rotary steerable system (DPRSS), which is known as state‐of‐the‐art oil drilling equipment. Firstly, the DPRSS dynamic is modelled as a linear system with drilling disturbances, which consists of model perturbations, measurement disturbances, and unknown inputs. Secondly, the finite‐frequency unknown input observer is proposed to generate the residual, which is sensitive to sensor faults and robust against drilling disturbances. Subsequently, considering model perturbations and measurement disturbances, the zonotope‐based residual evaluation method is presented, and the FD decision‐making logic is designed based on the calculated residual bounds. Finally, numerical simulations and prototype experiments are provided to illustrate the effectiveness of the proposed sensor FD mechanism.
Temporal‐enhanced graph convolution network for skeleton‐based action recognition
Authors: Xie Yulai , Zhang Yang , Ren Fang 
Published: January 2022

AbstractGraph convolution networks (GCNs) have drawn attention for skeleton‐based action recognition. They have achieved remarkable performance by adaptively learning spatial features of human action dynamics. However, the existing methods are limited in temporal sequence modelling of human actions. To give adequate consideration to temporal factors in action modelling, a novel temporal‐enhanced graph convolution network is presented. First, a Causal Convolution layer is introduced to ensure no future information leakage at each time step for keeping ordering information of inputs. Second, a novel cross‐spatial‐temporal graph convolution layer that extends an adaptive graph from the spatial to the temporal domain to capture local cross‐spatial‐temporal dependencies among joints is presented. Third, a temporal attention layer is designed to enhance the modelling capability of long‐range temporal dependencies, helping the network to directly focus on important time steps. Experimental results on three large‐scale datasets, NTU‐RGB + D, Kinetics‐Skeleton, and UAV‐Human, indicate that the authors’ network achieves accuracy improvement with better generalisation capability over previous methods. The authors’ code and data are available at https://github.com/xieyulai/TE‐GCN.
Electric theft detection in advanced metering infrastructure using Jaya optimized combined Kernel‐Tree boosting classifier—A novel sequentially executed supervised machine learning approach
Authors: Hussain Saddam , Mustafa Mohd. Wazir , Ateyeh Al‐Shqeerat Khalil Hamdi , Saleh Al‐rimy Bander Ali , Saeed Faisal 
Published: January 2022

AbstractThis paper presents a novel, sequentially executed supervised machine learning‐based electric theft detection framework using a Jaya‐optimized combined Kernel and Tree Boosting (KTBoost) classifier. It utilizes the intelligence of the XGBoost algorithm to estimate the missing values in the acquired dataset during the data pre‐processing phase. An oversampling algorithm based on the Robust‐SMOTE technique is utilized to avoid the unbalanced data class distribution issue. Afterward, with the aid of few very significant statistical, temporal, and spectral features extracted from the acquired kWh dataset, the complex underlying data patterns are comprehended to enhance the accuracy and detection rate of the classifier. For effectively classifying the consumers into “Honest” and “Fraudster,” the ensemble machine learning‐based classifier KTBoost, with Jaya algorithm optimized hyperparameters, is utilized. Finally, the developed model is re‐trained using a reduced set of highly important features to minimize the computational resources without compromising the performance of the developed model. The outcome of this study reveals that the proposed theft detection method achieves the highest accuracy (93.38%), precision (95%), and recall (93.18%) among all the studied methods, thus signifying its importance in the studied area of research.
Parallel electromagnetic transient simulation of power systems with a high proportion of renewable energy based on latency insertion method
Authors: Wang Qiguo , Xu Jin , Wang Keyou , Wu Pan , Chen Weiran , Li Zirun 
Published: January 2022

AbstractWith the interconnection of regional grids and the increasing penetration of renewable energy, the order of the power system model is getting higher and higher, which brings great challenges to the accuracy and real‐time performance of electromagnetic transient (EMT) simulation. The simulation of power systems with a high proportion of renewable energy requires a sharp increase in the performance of the hardware platform and the parallelism of the simulation algorithm. To solve this problem, the paper proposes a fine‐grained parallel modelling method for power systems with a high proportion of renewable energy, which is inspired by the latency insertion method used in the design of large‐scale integrated circuits. And this method is implemented on GPU to achieve the component‐level and device‐level parallelized simulation of power systems with a high proportion of renewable energy. Finally, the correctness of the proposed algorithm and the CPU‐GPU cooperative architecture is verified based on an improved 118‐bus case. The cascade system of the improved 9‐bus case is used as an example to verify the superiority of the proposed algorithm in terms of simulation efficiency.
Novel power electronic device for power angle stability control
Authors: Li Hui , Li Yifan , Huang Shaofeng , Li Huigen 
Published: January 2022

AbstractThis letter proposes a novel phase sequence exchange (PSE) device. When the generator loses synchronization and the power angle gradually increases, the primary side of the contact line is disconnected and quickly connected in a staggered phase using the power device with fast breaking characteristics. The three phases A, B, and C of the generator are connected to the systems C, A, and B. The power angle can be reduced by 120° instantaneously, thereby reducing system instability. First, the mechanism of the PSE device stability control is explained and the optimal PSE power angle threshold is calculated. After that, the structure and working process of the PSE device were proposed, the PSE prototype was manufactured, and an experimental platform was built for verification. Finally, a control method of the PSE device is proposed to reduce the impact and verified on the experimental platform.