bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quenched worst-case scenario for root deletion in targeted cutting of random recursive trees
Authors: Eslava Laura , López Sergio I. , Ortiz Marco L. 
Published: September 2024

AbstractWe propose a method for cutting down a random recursive tree that focuses on its higher-degree vertices. Enumerate the vertices of a random recursive tree of size n according to the decreasing order of their degrees; namely, let $(v^{(i)})_{i=1}^{n}$ be such that $\deg(v^{(1)}) \geq \cdots \geq \deg (v^{(n)})$. The targeted vertex-cutting process is performed by sequentially removing vertices $v^{(1)}, v^{(2)}, \ldots, v^{(n)}$ and keeping only the subtree containing the root after each removal. The algorithm ends when the root is picked to be removed. The total number of steps for this procedure, $K_n$, is upper bounded by $Z_{\geq D}$, which denotes the number of vertices that have degree at least as large as the degree of the root. We prove that $\ln Z_{\geq D}$ grows as $\ln n$ asymptotically and obtain its limiting behavior in probability. Moreover, we obtain that the kth moment of $\ln Z_{\geq D}$ is proportional to $(\!\ln n)^k$. As a consequence, we obtain that the first-order growth of $K_n$ is upper bounded by $n^{1-\ln 2}$, which is substantially smaller than the required number of removals if, instead, the vertices were selected uniformly at random.
Intraseasonal Variations and Extreme Occurrence in the Local Sea Level Along the Western Coast of India Remotely Controlled by a Basin‐Scale Climate Variability
Authors: Yamagami Y. , Suzuki T. , Tatebe H. 
Published: September 2024

AbstractThe equatorial Kelvin waves, remotely excited by basin‐scale climate modes, and subsequent coastal trapped waves significantly influence the intraseasonal variations, their low‐frequency modulations, and the frequency of extreme sea level events along the western coast of India. This study demonstrates that the frequency of extreme events are linked to the phase of the Indian Ocean Dipole mode. The temporal changes in the occurrence frequency of extremes are simulated in an eddy‐resolving ocean model consistently with observations. However, a non‐eddying model significantly underestimate the occurrence frequency of extreme sea level events, suggesting the importance of coastal trapped wave propagations regulated by the horizontal scale with the Rossby radius of deformation. This result implies that many state‐of‐the‐art climate models with a one‐degree ocean horizontal resolution may underestimate future coastal sea level variability and the frequency of extreme events under global warming and potential modulations of major internal climate modes.
Shadowgraph Measurements of Rotating Convective Planetary Core‐Style Flows
Authors: Abbate Jewel A. , Aurnou Jonathan M. 
Published: September 2024

AbstractThe local scale of rotating convection, ℓ, is a fundamental parameter in many turbulent geophysical and astrophysical fluid systems, yet it is often poorly constrained. Here we conduct rotating convection laboratory experiments analogous to convecting flows in planetary cores and subsurface oceans to obtain measurements of the local scales of motion. Utilizing silicone oil as the working fluid, we employ shadowgraph imagery to visualize the flow, from which we extract values of the characteristic cross‐axial scale of convective columns and plumes. These measurements are compared to the theoretical values of the critical onset length scale, ℓcrit, and the turbulent length scale, ℓturb. Our experimentally obtained length scale measurements simultaneously agree with both the onset and turbulent scale predictions across three orders of magnitude in convective supercriticality , a correlation that is consistent with inferences made in prior studies. We further explore the nature of this correlation and its implications for geophysical and astrophysical systems.
At the Junction Between Deep Learning and Statistics of Extremes: Formalizing the Landslide Hazard Definition
Authors: Dahal Ashok , Huser Raphaël , Lombardo Luigi 
Published: September 2024

AbstractThe most adopted definition of landslide hazard combines spatial information about landslide location (susceptibility), threat (intensity), and frequency (return period). Only the first two elements are usually considered and estimated when working over vast areas. Even then, separate models constitute the standard, with frequency being rarely investigated. Frequency and intensity are dependent on each other because larger events occur less frequently and vice versa. However, due to the lack of multi‐temporal inventories and joint statistical models, modeling such properties via a unified hazard model has always been challenging and has yet to be attempted. Here, we develop a unified model to estimate landslide hazard at the slope unit level to address such gaps. We employed deep learning, combined with extreme‐value theory to analyze an inventory of 30 years of observed rainfall‐triggered landslides in Nepal and assess landslide hazard for multiple return periods. We also use our model to further explore landslide hazard for the same return periods under different climate change scenarios up to the end of the century. Our model performs excellently (with an accuracy of 0.78 and an area under the curve of 0.86) and can be used to model landslide hazard in a unified manner. Geomorphologically, we find that under climate change scenarios (SSP245 and SSP585), landslide hazard is likely to increase up to two times on average in the lower Himalayan regions (Siwalik and lower Himalayas; ≈110–3,500 m) while remaining the same in the middle Himalayan region (≈3,500–5,000 m) whilst decreasing slightly in the upper Himalayan region (≳5,000 m) areas.
Evolution of West‐East Contrast in the Subarctic Pacific Gyre During the Plio‐Pleistocene Based on Palynological Evidence at ODP Sites 882 and 887
Authors: Zorzi C. , de Vernal A. 
Published: September 2024

AbstractFragmentary and contradictory evidence prevents a clear understanding of the possible role of the North Pacific Ocean surface on the ice‐sheet evolution. New palynological data encompassing the Pliocene and Pleistocene at Ocean Drilling Program Site 882 in the northwest Pacific document sea‐surface conditions from dinoflagellate cysts in addition to atmospheric trajectories from pollen grains and spores. The comparison of the Site 882 record with that of Site 887 from the northeast Pacific also permits documenting West to East contrasts across the subarctic North Pacific. The dinocyst assemblages at the two sites indicate strong temperature contrasts until 4.2 Ma, with much warmer conditions in the East. From 4.2 to 3.6 Ma, dinocyst assemblages of both sites are characterized by alternated dominance of the extinct taxa Habibacysta tectata and Impagidinium detroitense suggesting homogenous and cool conditions across the subarctic Pacific gyre. A major transition is recorded in the palynological assemblages at Site 882 around 2.7 Ma. It is marked by the highest occurrence of Habibacysta tectata and high percentages of Filisphaera microornata additionally to thermophilic taxa. Dinocyst record indicates high seasonality and warmer surface conditions due to reinforced stratification, which support the hypothesis of high evaporation at the origin of atmospheric moisture supply to high latitudes. During the last 1.2 Ma, the increase of Operculodinium centrocarpum relative to Nematosphaeropsis labyrinthus is tentatively interpreted as a reinforced influence of the subtropical waters. Hence, we suggest that the warm surface ocean fostered the inception and growth of northwestern North American ice‐sheets during the Pliocene and Pleistocene.
HIF1A-AS2 promotes the metabolic reprogramming and progression of colorectal cancer via miR-141-3p/FOXC1 axis
Authors: Zhong Xinyang , Wang Yaxian , He Xuefeng , He Xinxin , Hu Zijuan , Huang Huixia , Chen Jiayu , Chen Keji , Wei Ping , Zhao Senlin , Wang Yilin , Zhang Hong , Feng Bo , Li Dawei 
Published: September 2024

AbstractlncRNA can regulate tumorigenesis development and distant metastasis of colorectal cancer (CRC). However, the detailed molecular mechanisms are still largely unknown. Using RNA-sequencing data, RT-qPCR, and FISH assay, we found that HIF1A-AS2 was upregulated in CRC tissues and associated with poor prognosis. Functional experiments were performed to determine the roles of HIF1A-AS2 in tumor progression and we found that HIF1A-AS2 can promote the proliferation, metastasis, and aerobic glycolysis of CRC cells. Mechanistically, HIF1A-AS2 can promote FOXC1 expression by sponging miR-141-3p. SP1 can transcriptionally activate HIF1A-AS2. Further, HIF1A-AS2 can be packaged into exosomes and promote the malignant phenotype of recipient tumor cells. Taken together, we discovered that SP1-induced HIF1A-AS2 can promote the metabolic reprogramming and progression of CRC via miR-141-3p/FOXC1 axis. HIF1A-AS2 is a promising diagnostic marker and treatment target in CRC.
Tuning singlet oxygen generation with caged organic photosensitizers
Authors: Nestoros Eleni , de Moliner Fabio , Nadal-Bufi Ferran , Seah Deborah , Ortega-Liebana M. Carmen , Cheng Zhiming , Benson Sam , Adam Catherine , Maierhofer Larissa , Kozoriz Kostiantyn , Lee Jun-Seok , Unciti-Broceta Asier , Vendrell Marc 
Published: September 2024

AbstractControlling the succession of chemical processes with high specificity in complex systems is advantageous for widespread applications, from biomedical research to drug manufacturing. Despite synthetic advances in bioorthogonal and photochemical methodologies, there is a need for generic chemical approaches that can universally modulate photodynamic reactivity in organic photosensitizers. Herein we present a strategy to fine-tune the production of singlet oxygen in multiple photosensitive scaffolds under the activation of bioresponsive and bioorthogonal stimuli. We demonstrate that the photocatalytic activity of nitrobenzoselenadiazoles can be fully blocked by site-selective incorporation of electron-withdrawing carbamate moieties and restored on demand upon uncaging with a wide range of molecular triggers, including abiotic transition-metal catalysts. We also prove that this strategy can be expanded to most photosensitizers, including diverse structures and spectral properties. Finally, we show that such advanced control of singlet oxygen generation can be broadly applied to the photodynamic ablation of human cells as well as to regulate the release of singlet oxygen in the semi-synthesis of natural product drugs.
PMEL is involved in snake colour pattern transition from blotches to stripes
Authors: Tzika Athanasia C. , Ullate-Agote Asier , Helleboid Pierre-Yves , Kummrow Maya 
Published: September 2024

AbstractCorn snakes are emerging models for animal colouration studies. Here, we focus on the Terrazzo morph, whose skin pattern is characterized by stripes rather than blotches. Using genome mapping, we discover a disruptive mutation in the coding region of the Premelanosome protein (PMEL) gene. Our transcriptomic analyses reveal that PMEL expression is significantly downregulated in Terrazzo embryonic tissues. We produce corn snake PMEL knockouts, which present a comparable colouration phenotype to Terrazzo and the subcellular structure of their melanosomes and xanthosomes is also similarly impacted. Our single-cell expression analyses of wild-type embryonic dorsal skin demonstrate that all chromatophore progenitors express PMEL at varying levels. Finally, we show that in wild-type embryos PMEL-expressing cells are initially uniformly spread before forming aggregates and eventually blotches, as seen in the adults. In Terrazzo embryos, the aggregates fail to form. Our results provide insights into the mechanisms governing colouration patterning in reptiles.
A molecular mechanism to diversify Ca2+ signaling downstream of Gs protein-coupled receptors
Authors: Brands Julian , Bravo Sergi , Jürgenliemke Lars , Grätz Lukas , Schihada Hannes , Frechen Fabian , Alenfelder Judith , Pfeil Cy , Ohse Paul Georg , Hiratsuka Suzune , Kawakami Kouki , Schmacke Luna C. , Heycke Nina , Inoue Asuka , König Gabriele , Pfeifer Alexander , Wachten Dagmar , Schulte Gunnar , Steinmetzer Torsten , Watts Val J. , Gomeza Jesús , Simon Katharina , Kostenis Evi 
Published: September 2024

AbstractA long-held tenet in inositol-lipid signaling is that cleavage of membrane phosphoinositides by phospholipase Cβ (PLCβ) isozymes to increase cytosolic Ca2+ in living cells is exclusive to Gq- and Gi-sensitive G protein-coupled receptors (GPCRs). Here we extend this central tenet and show that Gs-GPCRs also partake in inositol-lipid signaling and thereby increase cytosolic Ca2+. By combining CRISPR/Cas9 genome editing to delete Gαs, the adenylyl cyclase isoforms 3 and 6, or the PLCβ1-4 isozymes, with pharmacological and genetic inhibition of Gq and G11, we pin down Gs-derived Gβγ as driver of a PLCβ2/3-mediated cytosolic Ca2+ release module. This module does not require but crosstalks with Gαs-dependent cAMP, demands Gαq to release PLCβ3 autoinhibition, but becomes Gq-independent with mutational disruption of the PLCβ3 autoinhibited state. Our findings uncover the key steps of a previously unappreciated mechanism utilized by mammalian cells to finetune their calcium signaling regulation through Gs-GPCRs.
Strong bottom currents in large, deep Lake Geneva generated by higher vertical-mode Poincaré waves
Authors: Reiss Rafael Sebastian , Lemmin Ulrich , Monin Claire , Barry David Andrew 
Published: September 2024

AbstractAlthough internal seiches are ubiquitous in large, deep lakes, little is known about the effect of higher vertical-mode seiches on deepwater dynamics. Here, by combining entire summer season current and temperature observations and 3D numerical modeling, we demonstrate that previously undetected vertical mode-two and mode-three Poincaré waves in 309-meter deep Lake Geneva (Switzerland/France) generate bottom-boundary layer currents up to 4 cm s−1. Poincaré wave amphidromic patterns revealed three strong cells excited simultaneously. Weak hypolimnetic stratification (N2 ≈ 10−6s−2), typical of deep lakes, significantly modified the wave structure by shifting the lower vertical node in the lake’s center from ~75-meter depth (without stratification) to ~150-meter depth (with stratification). This shift induces shear in the middle of the hypolimnion and strengthens bottom currents, with important implications for hypolimnetic mixing and sediment-water exchange. Our findings demonstrate that classical concepts based on constant temperature layers cannot correctly characterize higher vertical-mode Poincaré seiches in deep lakes.
Elucidating the assembly of gas vesicles by systematic protein-protein interaction analysis
Authors: Iburg Manuel , Anderson Andrew P , Wong Vivian T , Anton Erica D , He Art , Lu George J 
Published: September 2024

AbstractGas vesicles (GVs) are gas-filled microbial organelles formed by unique 3-nm thick, amphipathic, force-bearing protein shells, which can withstand multiple atmospheric pressures and maintain a physically stable air bubble with megapascal surface tension. However, the molecular process of GV assembly remains elusive. To begin understanding this process, we have devised a high-throughput in vivo assay to determine the interactions of all 11 proteins in the pNL29 GV operon. Complete or partial deletions of the operon establish interdependent relationships among GV proteins during assembly. We also examine the tolerance of the GV assembly process to protein mutations and the cellular burdens caused by GV proteins. Clusters of GV protein interactions are revealed, proposing plausible protein complexes that are important for GV assembly. We anticipate our findings will set the stage for designing GVs that efficiently assemble in heterologous hosts during biomedical applications.
Event‐triggered anti‐disturbance control for switched singular systems based on the uncertainty and disturbance estimator
Authors: Yang Anqing , Ma Shuping 
Published: September 2024

AbstractThis article studies the event‐triggered anti‐disturbance control problem for switched singular systems (SSSs) based on the uncertainty and disturbance estimator (UDE). First, a composite controller consisting of feedback control and anti‐disturbance control based on UDE is proposed. By constructing the multiple Lyapunov functions and using the average dwell time (ADT) method, sufficient conditions are given to ensure that the closed‐loop system is regular, impulse‐free and globally uniformly asymptotically stable (GUAS). Further, in order to save resources, the event‐triggered control method is introduced into the feedback control, and a novel hybrid event‐triggered mechanism (ETM) is proposed, which guarantees that asynchronous switching and Zeno behavior are excluded. And the solvable conditions in terms of linear matrix inequalities (LMIs) are given. Finally, the validity of the proposed results is verified by the simulations.
Network control based load frequency control considering the transmission delay
Authors: Zhang Boming , Iu Herbert , Zhang Xinan , Chau Tat Kei 
Published: September 2024

AbstractThis study introduces a network‐based controller to regulate frequency within power systems. The primary objective of this investigation is to ensure the stability of power systems experiencing delays in control signal transmission. Initially, a modified networked predictor is proposed to anticipate future signals within a decentralized load frequency control framework. Subsequently, a timestamp technique is employed to actively compensate for the impact of transmission delays. Additionally, an event trigger mechanism is incorporated to complement the extended state observer and optimize signal transmission resource usage. The outcomes of the study indicate that the proposed method effectively mitigates delay effects while maintaining superior performance. Moreover, the proposed method remarkably reduces the required transmission resources.
Online demand peak shaving with machine‐learned advice in digital twins
Authors: Feng Minxi , Li Wei , Qin Boyu , Zomaya Albert Y. 
Published: September 2024

AbstractAs the use of physical instruments grows, control algorithms are being increasingly deployed to enhance efficiency and reliability through digital twin technology. Demand load management is central to energy systems within digital twins, which significantly impacts operational costs. Peak demand loads can lead to substantial monthly utility expenses without proper management. AMPAMOD, a randomised online algorithm incorporating machine‐learned insights is introduced to optimise battery operations and mitigate peak demand loads. AMPAMOD leverages limited‐bit information from machine learning models to inform its online decision‐making process for cost‐effective load management. We provide theoretical evidence demonstrating that AMPAMOD maintains minimal advice complexity, has a linear computational cost, and achieves a bounded competitive ratio. Extensive trace‐driven experiments with real‐world household data reveal that AMPAMOD successfully reduces peak loads by over 90%, outperforming other benchmarks by at least 50%. These experimental findings align with our theoretical assertions, showcasing the effectiveness of AMPAMOD.
Determination of electron‐hole pair creation energy in Cd0.9Zn0.1Te0.98Se0.02 quaternary semiconductor for room‐temperature gamma‐ray detection
Authors: Chaudhuri Sandeep K. , Nag Ritwik , Roy Utpal N. , James Ralph B. , Mandal Krishna C. 
Published: September 2024

AbstractWe report the first‐time measurement of the electron‐hole pair (ehp) creation energy (Wehp) in novel Cd0.9Zn0.1Te0.98Se0.02 (CZTS) quaternary semiconductor. CZTS in single crystalline form is poised to be the future of large‐volume room‐temperature gamma‐ray detectors due to its excellent compositional homogeneity with highly reduced defects, high‐Z (atomic number) constituents, wide bandgap (1.6 eV), and superior charge transport properties. Despite a great deal of study of the material and device properties since its inception, the Wehp in CZTS has not been measured experimentally. Accurate determination of Wehp is essential for calibration of the spectrometer and other theoretical calculations. In this study we have used an absolute calibration approach, which is based on an iterative approach that yields the Wehp as the best‐fit parameter. Using a 241Am alpha emitting radioisotope and a planar CZTS detector, the Wehp in CZTS was calculated to be 4.47 eV. The obtained value has been validated by accurately predicting the peak energy for gamma rays emitted by a 137Cs source and read by a CZTS detector with different dimensions. The dependences of the calculated Wehp value on the detector dimensions, type of interaction, and effect of charge trapping are also discussed.
A NoisyNet deep reinforcement learning method for frequency regulation in power systems
Authors: Zhang Boming , Iu Herbert , Zhang Xinan , Chau Tat Kei 
Published: September 2024

AbstractThis study thoroughly investigates the NoisyNet Deep Deterministic Policy Gradient (DDPG) for frequency regulation. Compared with the conventional DDPG method, the suggested method can provide several benefits. First, the parameter noise will explore different strategies more thoroughly and can potentially discover better policies that it might miss if only action noise were used, which helps the actor achieve an optimal control strategy, resulting in enhanced dynamic response. Second, by employing the delayed policy update policy work with the proposed framework, the training process exhibits faster convergence, enabling rapid adaptation to changing disturbances. To substantiate its efficacy, the scheme is subjected to simulation tests on both an IEEE three‐area power system, an IEEE 39 bus power system, and an IEEE 68 bus system. A comprehensive performance comparison was performed against other DDPG‐based methods to validate and evaluate the performance of the proposed LFC scheme.
Automatic classification of bird species related to power line faults using deep convolution features and ECOC‐SVM model
Authors: Qiu Zhibin , Zhou Zhibiao , Wan Zhoutao 
Published: September 2024

AbstractBird‐related outages greatly threaten the safety of overhead transmission and distribution lines, while electrocution and collisions of birds with power lines, especially endangered species, are significant environmental concerns. Automatic bird recognition can be helpful to mitigate this contradiction. This paper proposes a method for automatic classification of bird species related to power line faults combining deep convolution features with error‐correcting output codes support vector machine (ECOC‐SVM). An image dataset of about 20 high‐risk and 20 low‐risk bird species was constructed, and the feed‐forward denoising convolutional neural network was used for image preprocessing. The deep convolution features of bird images were extracted by DarkNet‐53, and taken as inputs of the ECOC‐SVM for model training and bird species classification. The gradient‐weighted class activation mapping was used for visual explanations of the model decision region. The experimental results indicate that the average accuracy of the proposed method can reach 94.39%, and its performance was better than other models using different feature extraction networks and classification algorithms.