bluuebunny/crossref_metadata_2025_split huggingface dataset:
Algorithms for optimal min hop and foremost paths in interval temporal graphs
Authors: Jain Anuj , Sahni Sartaj K. 
Published: August 2022

AbstractPath problems are fundamental to the study of graphs. Temporal graphs are graphs in which the edges connecting the vertices change with time. Min hop paths problem in a temporal graph is the problem of finding time respecting paths from source vertex to every destination vertex such that the path goes through minimum number of edges. Foremost paths problem in a temporal graph requires to find time respecting paths that arrive at the destination vertices at earliest possible time. In this paper we present algorithms to find min hop paths and foremost paths in interval temporal graphs. These algorithms are benchmarked against the fastest algorithms known for foremost and min-hop paths by Wu et al. (IEEE Trans Knowl Data Eng 28(11):2927–2942, 2016a. https://doi.org/10.1109/TKDE.2016.2594065) that work on contact sequence temporal graph model. On the available test data, our foremost path algorithm provides a speedup of up to 1800 over the fastest algorithm for contact sequence graphs; the speedup for our min-hop algorithm is up to 6700. We also demonstrate that interval temporal graph model on which our algorithms work represents a superset of contact sequence temporal graphs. We show that path problems exist that are NP-hard in interval temporal graph model but polynomial in the contact sequence temporal graph model in terms of the number of vertices and edges in the input graph. This is due to the fact that the contact sequence graph model may require much larger number of edges than the corresponding interval temporal graph to represent a given temporal graph.
Seismic fragility analysis of concrete pile-supported wharves based on single-degree-of-freedom model
Authors: Feng Yunfen , Gao Shufei 
Published: August 2022

AbstractThis study proposes a new procedure to predict the seismic fragility curves of concrete pile-supported wharf based on an equivalent single-degree-of-freedom (SDOF) model. The SDOF model is utilized to substitute the practical wharf structure during probabilistic seismic demand analysis for reducing the computational cost and complexity. The trilinear backbone cure and Pivot hysteresis model, whose parameters are determined by the pushover analysis of actual wharf, are incorporated in the SDOF model to represent hysteresis characteristics and strength degradation of wharf. To validate the reasonability of the proposed procedure, two case studies are conducted by comparing the difference of fragility curves developed from actual wharf and its equivalent SDOF model based on the cloud method. The results show that the curves are located very closely on the graph, and the curve of SDOF model is generally above that of actual wharf, which indicates that the SDOF model may provide a conservative assessment for fragility analysis of wharf.
The grasshopper and the ant: Chinese teenagers and their representation of Italian people
Authors: Berti Chiara , Potì Silvia , Passini Stefano , Di Fabio Fiorinda 
Published: August 2022

AbstractThe aim of this exploratory study is to provide a better understanding of the representation shared by Chinese teenagers in Italy about Italian people. As research into migrants’ attitudes toward the host culture and society is rare, this study aims to bridge this gap. In 2016, 22 low-income first and second-generation Chinese teenagers living in an Italian city were interviewed. Analysis of their narratives, performed with T-Lab, a text mining software, produced three thematic clusters: “value differences”, the most relevant, which highlights the contrast between the perceived Chinese ethics of sacrifice versus the Italian propensity for leisure; “peer relationships and school life” which points at difficulties and opportunities in the integration process; while in the “stereotypes and prejudices” cluster, a kaleidoscopic vision of others as enemies emerges.
Negative Learning Ant Colony Optimization for MaxSAT
Authors: Nurcahyadi Teddy , Blum Christian , Manyà Felip 
Published: August 2022

AbstractRecently, a new negative learning variant of ant colony optimization (ACO) has been used to successfully tackle a range of combinatorial optimization problems. For providing stronger evidence of the general applicability of negative learning ACO, we investigate how it can be adapted to solve the Maximum Satisfiability problem (MaxSAT). The structure of MaxSAT is different from the problems considered to date and there exists only a few ACO approaches for MaxSAT. In this paper, we describe three negative learning ACO variants. They differ in the way in which sub-instances are solved at each algorithm iteration to provide negative feedback to the main ACO algorithm. In addition to using IBM ILOG CPLEX, two of these variants use existing MaxSAT solvers for this purpose. The experimental results show that the proposed negative learning ACO variants significantly outperform the baseline ACO as well as IBM ILOG CPLEX and the two MaxSAT solvers. This result is of special interest because it shows that negative learning ACO can be used to improve over the results of existing solvers by internally using them to solve smaller sub-instances.
Deep Learning of Detecting Ionospheric Precursors Associated With M ≥ 6.0 Earthquakes in Taiwan
Authors: Tsai T. C. , Jhuang H. K. , Ho Y. Y. , Lee L. C. , Su W. C. , Hung S. L. , Lee K. H. , Fu C. C. , Lin H. C. , Kuo C. L. 
Published: August 2022

AbstractA short‐term (30 days before an earthquake) prediction of an earthquake is a big challenge in seismology. As a first step, we apply deep learning to the ionospheric total electron content (TEC) data between 2003 and 2014 to detect the seismo‐ionospheric precursors of M ≥ 6.0 earthquakes in Taiwan. The bidirectional Long Short‐Term Memory (Bi‐LSTM) network is employed to use observed input data (features) to obtain the sequential TEC variations. The five input features are sequential vectors of TEC, the geomagnetic index Dst, the solar activity index F10.7, sunspot number (SSN), and solar emission index Lyman‐α. The daily values of F10.7, SSN, and Lyman‐α are converted into hourly values, depending on the solar elevation angle. The calculated hourly TEC variations can be more precisely predicted with this data conversion. We calculate the normalized difference of errors between two 15‐day adjacent stages as the “relative error”. Three trained models with the best discrimination between the relative errors of earthquake and no‐earthquake cases are chosen as classifiers. These three classifiers are then used to have a majority vote to declare whether the 30‐day period is related to the preparation of an earthquake or not. The results show that all 22 positive cases (earthquakes) are successfully predicted, giving a true positive rate of 100%. Among the 19 negative cases (normal cases), 10 of them are true negative.” Overall, a high accuracy of 78.05% is obtained.
A Case Study of Midlatitude Noctilucent Clouds and Its Relationship to the Secondary‐Generation Gravity Waves Over Tropopause Inversion Layer
Authors: Miao Jiaxuan , Gao Haiyang , Kou Leilei , Zhang Yehui , Li Yan , Chu Zhigang , Bu Lingbing , Wang Zhen 
Published: August 2022

AbstractA sporadic case of noctilucent clouds (NLCs) was observed unexpectedly on the night of the 6–7 July 2020 in Beijing (40°2′N, 115°30′E). The noticeable wavy structures and observed ambient temperature (135.54K at the mesosphere and lower thermosphere [MLT]), both indicated that the increase in temperature oscillations could be the cold phase of gravity waves (GWs). The reasons for NLC formation were analyzed based on the observations and model data sets in our study. The real‐time synoptic analysis revealed that there were GWs originally generated by a squall line in the troposphere. Due to the blocked effect of a stable tropopause inversion layer (TIL), the GWs broke, leading to strong energy dissipation near the TIL. The reverse ray tracing analysis between the TIL and NLCs' layer revealed the travel distance (206.88 km) and time (49.91 min) of GWs. These findings show that the turbulence over the TIL (at approximately 14.64 km) excited secondary GWs, which propagated upwards toward the mesosphere and probably interacted with diurnal and semi‐diurnal tides. The cold phase of the larger‐amplitude waves can provide optimal conditions for NLCs forming. Our study highlights the significance of dynamic coupling mechanisms regarding the effects from troposphere to MLT thermal conditions and offers a case study for the increasing occurrences of NLCs at midlatitudes.
Endothelial PDGF-BB/PDGFR-β signaling promotes osteoarthritis by enhancing angiogenesis-dependent abnormal subchondral bone formation
Authors: Cui Zhuang , Wu Hangtian , Xiao Ye , Xu Ting , Jia Junjie , Lin Hancheng , Lin Rongmin , Chen Kun , Lin Yihuang , Li Kaiqun , Wu Xiaohu , Li Changjun , Yu Bin 
Published: August 2022

AbstractThe mechanisms that coordinate the shift from joint homeostasis to osteoarthritis (OA) remain unknown. No pharmacological intervention can currently prevent the progression of osteoarthritis. Accumulating evidence has shown that subchondral bone deterioration is a primary trigger for overlying cartilage degeneration. We previously found that H-type vessels modulate aberrant subchondral bone formation during the pathogenesis of OA. However, the mechanism responsible for the elevation of H-type vessels in OA is still unclear. Here, we found that PDGFR-β expression, predominantly in the CD31hiEmcnhi endothelium, was substantially elevated in subchondral bones from OA patients and rodent OA models. A mouse model of OA with deletion of PDGFR-β in endothelial cells (ECs) exhibited fewer H-type vessels, ameliorated subchondral bone deterioration and alleviated overlying cartilage degeneration. Endothelial PDGFR-β promotes angiogenesis through the formation of the PDGFR-β/talin1/FAK complex. Notably, endothelium-specific inhibition of PDGFR-β by local injection of AAV9 in subchondral bone effectively attenuated the pathogenesis of OA compared with that of the vehicle-treated controls. Based on the results from this study, targeting PDGFR-β is a novel and promising approach for the prevention or early treatment of OA.
Multi-target action of β-alanine protects cerebellar tissue from ischemic damage
Authors: Kopach Olga , Rusakov Dmitri A. , Sylantyev Sergiy 
Published: August 2022

AbstractBrain ischemic stroke is among the leading causes of death and long-term disability. New treatments that alleviate brain cell damage until blood supply is restored are urgently required. The emerging focus of anti-stroke strategies has been on blood-brain-barrier permeable drugs that exhibit multiple sites of action. Here, we combine single-cell electrophysiology with live-cell imaging to find that β-Alanine (β-Ala) protects key physiological functions of brain cells that are exposed to acute stroke-mimicking conditions in ex vivo brain preparations. β-Ala exerts its neuroprotective action through several distinct pharmacological mechanisms, none of which alone could reproduce the neuroprotective effect. Since β-Ala crosses the blood-brain barrier and is part of a normal human diet, we suggest that it has a strong potential for acute stroke treatment and facilitation of recovery.
Long noncoding RNA LINC00239 inhibits ferroptosis in colorectal cancer by binding to Keap1 to stabilize Nrf2
Authors: Han Yuying , Gao Xiaoliang , Wu Nan , Jin Yirong , Zhou He , Wang Weijie , Liu Hao , Chu Yi , Cao Jiayi , Jiang Mingzuo , Yang Suzhen , Shi Yanting , Xie Xin , Chen Fulin , Han Ying , Qin Wen , Xu Bing , Liang Jie 
Published: August 2022

AbstractFerroptosis, a novel regulated cell death induced by iron-dependent lipid peroxidation, plays an important role in tumor development and drug resistance. Long noncoding RNAs (lncRNAs) are associated with various types of cancer. However, the precise roles of many lncRNAs in tumorigenesis remain elusive. Here we explored the transcriptomic profiles of lncRNAs in primary CRC tissues and corresponding paired adjacent non-tumor tissues by RNA-seq and found that LINC00239 was significantly overexpressed in colorectal cancer tissues. Abnormally high expression of LINC00239 predicts poorer survival and prognosis in colorectal cancer patients. Concurrently, we elucidated the role of LINC00239 as a tumor-promoting factor in CRC through in vitro functional studies and in vivo tumor xenograft models. Importantly, overexpression of LINC00239 decreased the anti-tumor activity of erastin and RSL3 by inhibiting ferroptosis. Collectively, these data suggest that LINC00239 plays a novel and indispensable role in ferroptosis by nucleotides 1–315 of LINC00239 to interact with the Kelch domain (Nrf2-binding site) of Keap1, inhibiting Nrf2 ubiquitination and increasing Nrf2 protein stability. Considering the recurrence and chemoresistance constitute the leading cause of death in colorectal cancer (CRC), ferroptosis induction may be a promising therapeutic strategy for CRC patients with low LINC00239 expression.
Deep learning image segmentation reveals patterns of UV reflectance evolution in passerine birds
Authors: He Yichen , Varley Zoë K. , Nouri Lara O. , Moody Christopher J. A. , Jardine Michael D. , Maddock Steve , Thomas Gavin H. , Cooney Christopher R. 
Published: August 2022

AbstractUltraviolet colouration is thought to be an important form of signalling in many bird species, yet broad insights regarding the prevalence of ultraviolet plumage colouration and the factors promoting its evolution are currently lacking. In this paper, we develop a image segmentation pipeline based on deep learning that considerably outperforms classical (i.e. non deep learning) segmentation methods, and use this to extract accurate information on whole-body plumage colouration from photographs of >24,000 museum specimens covering >4500 species of passerine birds. Our results demonstrate that ultraviolet reflectance, particularly as a component of other colours, is widespread across the passerine radiation but is strongly phylogenetically conserved. We also find clear evidence in support of the role of light environment in promoting the evolution of ultraviolet plumage colouration, and a weak trend towards higher ultraviolet plumage reflectance among bird species with ultraviolet rather than violet-sensitive visual systems. Overall, our study provides important broad-scale insight into an enigmatic component of avian colouration, as well as demonstrating that deep learning has considerable promise for allowing new data to be brought to bear on long-standing questions in ecology and evolution.
Degenerate boundaries for multiple-alternative decisions
Authors: Baker Sophie-Anne , Griffith Thom , Lepora Nathan F. 
Published: August 2022

AbstractIntegration-to-threshold models of two-choice perceptual decision making have guided our understanding of human and animal behavior and neural processing. Although such models seem to extend naturally to multiple-choice decision making, consensus on a normative framework has yet to emerge, and hence the implications of threshold characteristics for multiple choices have only been partially explored. Here we consider sequential Bayesian inference and a conceptualisation of decision making as a particle diffusing in n-dimensions. We show by simulation that, within a parameterised subset of time-independent boundaries, the optimal decision boundaries comprise a degenerate family of nonlinear structures that jointly depend on the state of multiple accumulators and speed-accuracy trade-offs. This degeneracy is contrary to current 2-choice results where there is a single optimal threshold. Such boundaries support both stationary and collapsing thresholds as optimal strategies for decision-making, both of which result from stationary representations of nonlinear boundaries. Our findings point towards a normative theory of multiple-choice decision making, provide a characterisation of optimal decision thresholds under this framework, and inform the debate between stationary and dynamic decision boundaries for optimal decision making.
Atomic partial wave meter by attosecond coincidence metrology
Authors: Jiang Wenyu , Armstrong Gregory S. J. , Tong Jihong , Xu Yidan , Zuo Zitan , Qiang Junjie , Lu Peifen , Clarke Daniel D. A. , Benda Jakub , Fleischer Avner , Ni Hongcheng , Ueda Kiyoshi , van der Hart Hugo W. , Brown Andrew C. , Gong Xiaochun , Wu Jian 
Published: August 2022

AbstractAttosecond chronoscopy is central to the understanding of ultrafast electron dynamics in matter from gas to the condensed phase with attosecond temporal resolution. It has, however, not yet been possible to determine the timing of individual partial waves, and steering their contribution has been a substantial challenge. Here, we develop a polarization-skewed attosecond chronoscopy serving as a partial wave meter to reveal the role of each partial wave from the angle-resolved photoionization phase shifts in rare gas atoms. We steer the relative ratio between different partial waves and realize a magnetic-sublevel-resolved atomic phase shift measurement. Our experimental observations are well supported by time-dependent R-matrix numerical simulations and analytical soft-photon approximation analysis. The symmetry-resolved, partial-wave analysis identifies the transition rate and phase shift property in the attosecond photoelectron emission dynamics. Our findings provide critical insights into the ubiquitous attosecond optical timer and the underlying attosecond photoionization dynamics.
Revealing the spatiotemporal complexity of the magnitude distribution and b-value during an earthquake sequence
Authors: Herrmann Marcus , Piegari Ester , Marzocchi Warner 
Published: August 2022

AbstractThe Magnitude–Frequency-Distribution (MFD) of earthquakes is typically modeled with the (tapered) Gutenberg–Richter relation. The main parameter of this relation, theb-value, controls the relative rate of small and large earthquakes. Resolving spatiotemporal variations of theb-value is critical to understanding the earthquake occurrence process and improving earthquake forecasting. However, this variation is not well understood. Here we present remarkable MFD variability during the complex 2016/17 central Italy sequence using a high-resolution earthquake catalog. Isolating seismically active volumes (‘clusters’) reveals that the MFD differed in nearby clusters, varied or remained constant in time depending on the cluster, and increased inb-value in the cluster where the largest earthquake eventually occurred. These findings suggest that the fault system’s heterogeneity and complexity influence the MFD. Our findings raise the question “b-value of what?”: interpreting and using MFD variability needs a spatiotemporal scale that is physically meaningful, like the one proposed here.
Proteolytic processing induces a conformational switch required for antibacterial toxin delivery
Authors: Bartelli Nicholas L. , Passanisi Victor J. , Michalska Karolina , Song Kiho , Nhan Dinh Q. , Zhou Hongjun , Cuthbert Bonnie J. , Stols Lucy M. , Eschenfeldt William H. , Wilson Nicholas G. , Basra Jesse S. , Cortes Ricardo , Noorsher Zainab , Gabraiel Youssef , Poonen-Honig Isaac , Seacord Elizabeth C. , Goulding Celia W. , Low David A. , Joachimiak Andrzej , Dahlquist Frederick W. , Hayes Christopher S. 
Published: August 2022

AbstractMany Gram-negative bacteria use CdiA effector proteins to inhibit the growth of neighboring competitors. CdiA transfers its toxic CdiA-CT region into the periplasm of target cells, where it is released through proteolytic cleavage. The N-terminal cytoplasm-entry domain of the CdiA-CT then mediates translocation across the inner membrane to deliver the C-terminal toxin domain into the cytosol. Here, we show that proteolysis not only liberates the CdiA-CT for delivery, but is also required to activate the entry domain for membrane translocation. Translocation function depends on precise cleavage after a conserved VENN peptide sequence, and the processed ∆VENN entry domain exhibits distinct biophysical and thermodynamic properties. By contrast, imprecisely processed CdiA-CT fragments do not undergo this transition and fail to translocate to the cytoplasm. These findings suggest that CdiA-CT processing induces a critical structural switch that converts the entry domain into a membrane-translocation competent conformation.
A brainstem monosynaptic excitatory pathway that drives locomotor activities and sympathetic cardiovascular responses
Authors: Koba Satoshi , Kumada Nao , Narai Emi , Kataoka Naoya , Nakamura Kazuhiro , Watanabe Tatsuo 
Published: August 2022

AbstractExercise including locomotion requires appropriate autonomic cardiovascular adjustments to meet the metabolic demands of contracting muscles, yet the functional brain architecture underlying these adjustments remains unknown. Here, we demonstrate brainstem circuitry that plays an essential role in relaying volitional motor signals, i.e., central command, to drive locomotor activities and sympathetic cardiovascular responses. Mesencephalic locomotor neurons in rats transmit central command-driven excitatory signals onto the rostral ventrolateral medulla at least partially via glutamatergic processes, to activate both somatomotor and sympathetic nervous systems. Optogenetic excitation of this monosynaptic pathway elicits locomotor and cardiovascular responses as seen during running exercise, whereas pathway inhibition suppresses the locomotor activities and blood pressure elevation during voluntary running without affecting basal cardiovascular homeostasis. These results demonstrate an important subcortical pathway that transmits central command signals, providing a key insight into the central circuit mechanism required for the physiological conditioning essential to maximize exercise performance.
High-entropy intermetallics on ceria as efficient catalysts for the oxidative dehydrogenation of propane using CO2
Authors: Xing Feilong , Ma Jiamin , Shimizu Ken-ichi , Furukawa Shinya 
Published: August 2022

AbstractThe oxidative dehydrogenation of propane using CO2 (CO2-ODP) is a promising technique for high-yield propylene production and CO2 utilization. The development of a highly efficient catalyst for CO2-ODP is of great interest and benefit to the chemical industry as well as net zero emissions. Here, we report a unique catalyst material and design concept based on high-entropy intermetallics for this challenging chemistry. A senary (PtCoNi)(SnInGa) catalyst supported on CeO2 with a PtSn intermetallic structure exhibits a considerably higher catalytic activity, C3H6 selectivity, long-term stability, and CO2 utilization efficiency at 600 °C than previously reported. Multi-metallization of the Pt and Sn sites by Co/Ni and In/Ga, respectively, greatly enhances propylene selectivity, CO2 activation ability, thermal stability, and regenerable ability. The results obtained in this study can promote carbon-neutralization of industrial processes for light alkane conversion.