bluuebunny/crossref_metadata_2025_split huggingface dataset:
Flag Hilbert–Poincaré series and Igusa zeta functions of hyperplane arrangements
Authors: Maglione Joshua , Voll Christopher 
Published: August 2024

AbstractWe introduce and study a class of multivariate rational functions associated with hyperplane arrangements, called flag Hilbert–Poincaré series. These series are intimately connected with Igusa local zeta functions of products of linear polynomials, and their motivic and topological relatives. Our main results include a self-reciprocity result for central arrangements defined over fields of characteristic zero. We also prove combinatorial formulae for a specialization of the flag Hilbert–Poincaré series for irreducible Coxeter arrangements of types A, B, and D in terms of total partitions of the respective types. We show that a different specialization of the flag Hilbert–Poincaré series, which we call the coarse flag Hilbert–Poincaré series, exhibits intriguing nonnegativity features and—in the case of Coxeter arrangements—connections with Eulerian polynomials. For numerous classes and examples of hyperplane arrangements, we determine their (coarse) flag Hilbert–Poincaré series. Some computations were aided by a SageMath package we developed.
Proximal evolutionary strategy: improving deep reinforcement learning through evolutionary policy optimization
Authors: Peng Yiming , Chen Gang , Zhang Mengjie , Xue Bing 
Published: August 2024

AbstractEvolutionary Algorithms (EAs), including Evolutionary Strategies (ES) and Genetic Algorithms (GAs), have been widely accepted as competitive alternatives to Policy Gradient techniques for Deep Reinforcement Learning (DRL). However, they remain eclipsed by cutting-edge DRL algorithms in terms of time efficiency, sample complexity, and learning effectiveness. In this paper, aiming at advancing evolutionary DRL research, we develop an evolutionary policy optimization algorithm with three key technical improvements. First, we design an efficient layer-wise strategy for training DNNs through Covariance Matrix Adaptation Evolutionary Strategies (CMA-ES) in a highly scalable manner. Second, we establish a surrogate model based on proximal performance lower bound for fitness evaluations with low sample complexity. Third, we embed a gradient-based local search technique within the evolutionary policy optimization process to further improve the learning effectiveness. The three technical innovations jointly forge a new EA for DRL method named Proximal Evolutionary Strategies (PES). Our experiments on ten continuous control problems show that PES with layer-wise training can be more computationally efficient than CMA-ES; our surrogate model can remarkably reduce the sample complexity of PES in comparison to latest EAs for DRL including CMA-ES, OpenAI-ES, and Uber-GA; PES with gradient-based local search can significantly outperform several promising DRL algorithms including TRPO, AKCTR, PPO, OpenAI-ES, and Uber-GA.
Immune Checkpoint Inhibitor-Related Cerebellar Toxicity: Clinical Features and Comparison with Paraneoplastic Cerebellar Ataxia
Authors: Dentoni Marta , Florean Irene , Farina Antonio , Joubert Bastien , Do Le-Duy , Honnorat Jérôme , Damato Valentina , Fabris Martina , Gigli Gian Luigi , Valente Mariarosaria , Vogrig Alberto 
Published: August 2024

﻿AbstractImmune checkpoint inhibitors (ICIs) have revolutionized cancer therapy, and the association with immune-related adverse events (irAEs) is well-established. However, cerebellar irAEs are poorly defined and their relationship with paraneoplastic disorders remains unclear. Our aim was (i) to characterize cerebellar irAE; (ii) to compare it with paraneoplastic cerebellar ataxia (PCA). We performed a multicenter, retrospective, cohort study of patients developing new-onset, immune-mediated, isolated/predominant cerebellar dysfunction after ICI administration. In addition, a systematic review following PRISMA guidelines was performed. Cerebellar irAE cases were compared with a consecutive cohort of patients with PCA. Overall, 35 patients were included, of whom 12 were original cases (males: 25/35 (71%), median age: 65 [range: 20–82]). The most frequent tumor was non-small cell lung cancer (12/35, 34%). Anti-PD1 were adopted in 19/35 (54%). Symptoms developed at a median of 11 weeks after ICI onset. Neuronal antibodies were detected in 15/31 patients tested (48%). Cerebrospinal fluid was inflammatory in 25/30 (83%). Magnetic resonance imaging showed cerebellar hyperintensities in 8/35 (23%). Immunotherapy was applied in 33/35 cases (94%), and most patients improved with residual disability (16/35, 46%). When compared with a series of PCA (n = 15), the cerebellar irAE group was significantly more associated with male sex, lung cancer (rather than gynecological/breast cancers), isolated ataxia, and a better outcome. We provide a detailed characterization of cerebellar irAE. Compared to PCA, differences exist in terms of tumor association, clinical features, and outcome. Clinical presentation-antibody-tumor triad in the ICI group only partially reflects the associations described in paraneoplastic disorders.
Chemical Composition and Carbohydrate Characterization of Beach-Cast Marine Macrophytes from the Mexican Caribbean: Implications for Potential Bioethanol Production
Authors: Yolanda Freile-Pelegrín , Daniel Robledo , Cresencia Chávez-Quintal , Vázquez-Delfín Erika , Hugo Pliego-Cortés , Gilles Bedoux , Nathalie Bourgougnon 
Published: August 2024

Abstract
Marine macrophytes are considered promising biomass for bioethanol production. The increases in anthropogenic nutrients and climate change have caused unprecedented blooming of ‘sargasso’ across the Atlantic since 2011. This biomass reaches the Caribbean Sea, stranding in large amounts along shorelines, and creating a serious waste management problem. The knowledge of its chemical composition is important to assess whether this material could serve as feedstock for third-generation bioethanol. The beach-cast marine macrophytes collected on the Mexican Caribbean coast in December 2018 were composed of brown seaweeds and a seagrass (23.5 and 76.5% relative abundance, respectively) including Sargassum fluitans, Sargassum natans I, Sargassum natans VIII, Turbinaria turbinata, and the angiosperm Syringodium filiforme. For valorization purposes, glucans, non-glucans carbohydrates and lignin were determined. Besides its abundance, underutilization, and low-cost this whole biomass may have potential as a promising raw material for third-generation bioethanol because it contains easily fermentable glucose such as mannitol (36.3% in whole biomass and 56% in the Sargassum species) and cellulose (36.3% on average). Other specific carbohydrates such as alginate (20–31%) and fucoidan (9.1–8.2%) were present in smaller amounts but they can also be converted to fermentable sugars with the proper methodology. Some advantages and limitations for the potential production of third-generation bioethanol from this biomass are discussed.
Leveraging deep learning techniques for condition assessment of stormwater pipe network
Authors: Yussuf Abdulgani Nur , Weerasinghe Nilmini Pradeepika , Chen Haosen , Hou Lei , Herath Damayanthi , Rashid Mohammad , Zhang Guomin , Setunge Sujeeva 
Published: August 2024

AbstractInspections and condition monitoring of the stormwater pipe networks have become increasingly crucial due to their vast geographical span and complex structure. Unmanaged pipelines present significant risks, such as water leakage and flooding, posing threats to urban infrastructure. However, only a small percentage of pipelines undergo annual inspections. The current practice of CCTV inspections is labor-intensive, time-consuming, and lacks consistency in judgment. Therefore, this study aims to propose a cost-effective and efficient semi-automated approach that integrates computer vision technology with Deep Learning (DL) algorithms. A DL model is developed using YOLOv8 with instance segmentation to identify six types of defects as described in Water Services Association (WSA) Code of Australia. CCTV footage from Banyule City Council was incorporated into the model, achieving a mean average precision (mAP@0.5) of 0.92 for bounding boxes and 0.90 for masks. A cost–benefit analysis is conducted to assess the economic viability of the proposed approach. Despite the high initial development costs, it was observed that the ongoing annual costs decreased by 50%. This model allowed for faster, more accurate, and consistent results, enabling the inspection of additional pipelines each year. This model serves as a tool for every local council to conduct condition monitoring assessments for stormwater pipeline work in Australia, ultimately enhancing resilient and safe infrastructure asset management.
CFD Validation of Forced and Natural Convection for the Open Phase of IAEA Benchmark CRP-I31038
Authors: Batta Abdalla , Class Andreas G. 
Published: August 2024

AbstractThe goal of the IAEA Coordinated Research Project “Benchmark of Transition from Forced to Natural Circulation Experiment with Heavy Liquid Metal Loop” (CRP—I31038) is to develop Member State advanced fast reactor analytical capabilities for simulation and design using system, CFD, and subchannel analysis codes. Here, CFD validation employing the commercial CFD code Star CCM + applied to the fuel pin simulator for forced and natural convection cases in the open phase is presented. Experimental data are provided in the benchmark specification provided by ENEA (Italian National Agency for New Technologies, Energy and Sustainable Economic Development) for the NACIE-UP facility (NAtural CIrculation Experiment-UPgrade). Considered is the fuel pin simulator with 19 pins, each consisting of a preheated lower section and heated upper sections, respectively. Three configurations: (i) all pins heated, (ii) inner 7 pins heated and (iii) asymmetric heating, are studied. For each heating configuration data for forced and natural convection are provided. Here, case (i) is studied. Temperatures at three planes are measured near the inlet, in the middle and near the end of the heated section, respectively. In addition, the axial temperature along the wall of one fuel pin simulator (in second row) is measured so that in total 67 thermocouples measure fluid and wall temperatures for validation purposes. The validation confirms that the thermohydraulic inside the fuel pin simulator can be simulated with a good accuracy. Applied is a polyhedral mesh with 2 prism layers, the k-omega SST model with all all-wall treatment and order unity y + values. Moreover, a grid-sensitivity, the importance of conjugate heat transfer inside the fuel pin simulators and the wrapper are studied. The studies indicate that it is possible to implement further simplifications without corrupting the accuracy of the simulation to reduce computational effort.
A Well-Structured Metaheuristic Optimization Technique for Magnetic Data Inversion of 2D Dipping Dyke-like Geological Structures Using the Cuckoo Optimization Algorithm
Authors: Toushmalani Reza , Essa Khalid S. , Ibraheem Ismael M. 
Published: August 2024

AbstractThis study applies the cuckoo optimization algorithm (COA), inspired by the brood reproduction technique of cuckoo birds, to interpret magnetic anomalies of 2D dipping dyke-like structures. The primary issue addressed is the need for accurate delineation and explanation of dyke parameters, which are crucial for visualizing dyke propagation (important for volcanic hazard assessment), tracing mineralized zones associated with dykes, and understanding their geodynamic significance. Our method identifies dyke parameters at the minimum value of the suggested objective function, ensuring the best fit. The proposed COA method was tested on both noise-free numerical magnetic datasets and datasets with varying levels of random noise (5%, 10%, and 20%), as well as real-case datasets from China and the UK. A comparative analysis with particle swarm optimization (PSO) and genetic algorithm (GA) methods was conducted to evaluate the efficiency and consistency of COA. The results demonstrate that COA aligns well with existing geological and geophysical information, offering superior accuracy and robustness compared to traditional techniques. This study provides a novel and effective approach for subsurface characterization, advancing the precision of geological and geophysical interpretations.
Simple and effective: Superlubricity behaviour of the G-quadruplex hydrogel with high selectivity for K+ ions based on the ocular environment
Authors: Wang Hongdong , Wu Jian , Wang Kunpeng , Su Yunjuan , Zhang Xiacong , Liu Yuhong , Zhang Jianhua 
Published: August 2024

AbstractHydrogels have been the subject of significant research in the field of friction due to their exceptional lubricating properties. In this study, the G-quadruplex hydrogel with high selectivity for K+ ions was formed by introducing a mixture of G, 2-formylphenylboronic acid, and polyethylene glycol diamine into simulated artificial tears solution with high transparency, and an ultra-low coefficient of friction (COF) of about 0.004 was obtained based on the simulated ocular environment, thus achieving macroscopic superlubricity. In friction pairs simulating the ocular environment, to assess the frictional performance of the G-quadruplex hydrogel as both a lubricant and a friction pair based on the simulated ocular environment, we conducted experiments considering various factors such as concentration, sliding speed, and stress. Through these experiments, it was found that superlubricity was achieved when the G-quadruplex hydrogel was applied as lubricant or friction pair. This effect was attributed to the three-dimensional network structure and hydrophilicity of the hydrogel, which facilitated the formation of a highly bearing and flowing hydration layer, promoting macroscopic superlubricity. Compared to the G-quadruplex hydrogel with low concentration, the high concentration hydrogel (75 mM) exhibited increased mechanical strength and robustness in superlubricity. Combined with biocompatibility experiments, our synthesized G-quadruplex hydrogel has excellent biocompatibility and offers a novel approach to achieve superlubricity in ocular drug delivery.
Hydrodynamic Response of Channel Flow Confluence to the Tributary Floodplain Topography
Authors: Yan Guanghui , Yuan Saiyu , Tang Hongwu , Xu Dong , Liu Mengyang , Whittaker Colin , Gualtieri Carlo 
Published: August 2024

AbstractRiver confluences with a compound‐channel tributary are common in large river networks, for example, the Yangtze River basin and the Amazon basin. They affect the confluence hydrodynamics, nutrient depletion and fish migration in the network, due to the seasonal exposure and submergence of the tributary floodplain. The corresponding influencing mechanisms are critical but poorly understood. This study investigated the hydrodynamic response of channel flow confluence to the tributary floodplain, that is, various widths and heights of the floodplain. Two kinds of secondary circulations were identified: One was due to the tributary streamline curvature, and the other produced by flow separation in the floodplain step. An increase in the floodplain size enhanced the strength of the secondary circulation in the compound tributary channel, but it disappeared near the junction because of the effects of the main channel. The decreased tributary cross‐sectional area amplified the flow momentum, resulting in a larger separation zone near the tributary‐side wall. The strength of floodplain‐induced secondary circulation increased as the floodplain width increased, and it moved toward the tributary‐side bank destroying the separation zone. Moreover, strong upwelling in the secondary circulation caused the rising water surface in the separation zone, which was supposed to be a region of falling water surface caused by energy loss and negative pressure. A conceptual model was proposed to summarize the hydrodynamics of confluence with different tributary floodplain topography. Our results provided a comprehensive knowledge of the confluence hydrodynamics, which have important implication for the flood management and ecological restoration of river basin.
Snowdrift‐Permitting Simulations of Seasonal Snowpack Processes Over Large Mountain Extents
Authors: Marsh Christopher B. , Lv Zhibang , Vionnet Vincent , Harder Phillip , Spiteri Raymond J. , Pomeroy John W. 
Published: August 2024

AbstractThe melt of seasonal snowpack in mountain regions provides downstream river basins with a critical supply of freshwater. Snowdrift‐permitting models have been proposed as a way to accurately simulate snowpack heterogeneity that stems from differences in energy inputs, over winter redistribution, sublimation, melt, and variations in precipitation. However, these spatial scales can be computationally intractable for large extents. In this work, the multiscale Canadian Hydrological Model (CHM) was applied to simulate snowpacks at snowdrift‐permitting scales (≈50 m) across the Canadian Cordillera and adjacent regions (1.37 million km2) forced by downscaled atmospheric data. The use of a multiscale land surface representation resulted in a reduction of computational elements of 98% while preserving land‐surface heterogeneity. CHM includes complex terrain windflow and radiative transfer calculations, lapses temperature, humidity, and precipitation with elevation, redistributes snow by avalanching, wind transport and forest canopy interception and calculates the energetics of canopy and surface snowpacks. Model outputs were compared to a set of multiscale observations including snow‐covered area (SCA) from Sentinel and Landsat imagery, snow depth from uncrewed aerial system lidar, and point surface observations of depth and density. Including snow redistribution and sublimation processes improved the summer SCA r2 from 0.7 to 0.9. At larger scales, inclusion of snow redistribution processes delayed full snowpack ablation by an average of 33 days, demonstrating process emergence with scale. These simulations show how multiscale modeling can improve snowpack predictions to support prediction of water supply, droughts, and floods.
Spinal cord injury in high-risk complex adult spinal deformity surgery: review of incidence and outcomes from the Scoli-RISK-1 study
Authors: Jiang Fan , Joshi Hetshree , Badhiwala Jetan H. , Wilson Jamie R. F. , Lenke Lawrence G. , Shaffrey Christopher I. , Cheung Kenneth M. C. , Carreon Leah Y. , Dekutoski Mark B. , Schwab Frank J. , Boachie-Adjei Oheneba , Kebaish Khaled M. , Ames Christopher P. , Berven Sigurd H. , Qiu Yong , Matsuyama Yukihiro , Dahl Benny T. , Mehdian Hossein , Pellisé Ferran , Lewis Stephen J. , Fehlings Michael G. 
Published: August 2024

Abstract
Study design
Clinical case series.

Objective
To describe the cause, treatment and outcome of 6 cases of perioperative spinal cord injury (SCI) in high-risk adult deformity surgery.

Setting
Adult spinal deformity patients were enrolled in the multi-center Scoli-RISK-1 cohort study.

Methods
A total of 272 patients who underwent complex adult deformity surgery were enrolled in the prospective, multi-center Scoli-RISK-1 cohort study. Clinical follow up data were available up to a maximum of 2 years after index surgery. Cases of perioperative SCI were identified and an extensive case review was performed.

Results
Six individuals with SCI were identified from the Scoli-RISK-1 database (2.2%). Two cases occurred intraoperatively and four cases occurred postoperatively. The first case was an incomplete SCI due to a direct intraoperative insult and was treated postoperatively with Riluzole. The second SCI case was caused by a compression injury due to overcorrection of the deformity. Three cases of incomplete SCI occurred; one case of postoperative hematoma, one case of proximal junctional kyphosis (PJK) and one case of adjacent segment disc herniation. All cases of post-operative incomplete SCI were managed with revision decompression and resulted in excellent clinical recovery. One case of incomplete SCI resulted from infection and PJK. The patient’s treatment was complicated by a delay in revision and the patient suffered persistent neurological deficits up to six weeks following the onset of SCI.

Conclusion
Despite the low incidence in high-risk adult deformity surgeries, perioperative SCI can result in devastating consequences. Thus, appropriate postoperative care, follow up and timely management of SCI are essential.
TLR9 activation in large wound induces tissue repair and hair follicle regeneration via γδT cells
Authors: Li Xinhui , An Tiantian , Yang Yang , Xu Zhaoyu , Chen Shuaidong , Yi Zumu , Deng Chen , Zhou Feng , Man Yi , Hu Chen 
Published: August 2024

AbstractThe mechanisms underlying tissue repair in response to damage have been one of main subjects of investigation. Here we leverage the wound-induced hair neogenesis (WIHN) models in adult mice to explore the correlation between degree of damage and the healing process and outcome. The multimodal analysis, in combination with single-cell RNA sequencing help to explore the difference in wounds of gentle and heavy damage degrees, identifying the potential role of toll-like receptor 9 (TLR9) in sensing the injury and regulating the immune reaction by promoting the migration of γδT cells. The TLR9 deficient mice or wounds injected with TLR9 antagonist have greatly impaired healing and lower WIHN levels. Inhibiting the migration of γδT cells or knockout of γδT cells also suppress the wound healing and regeneration, which can’t be rescued by TLR9agonist. Finally, the amphiregulin (AREG) is shown as one of most important effectors secreted by γδT cells and keratinocytes both in silicon or in the laboratory, whose expression influences WIHN levels and the expression of stem cell markers. In total, our findings reveal a previously unrecognized role for TLR9 in sensing skin injury and influencing the tissue repair and regeneration by modulation of the migration of γδT cells, and identify the TLR9-γδT cells-areg axis as new potential targets for enhancing tissue regeneration.
Prediction-error signals in anterior cingulate cortex drive task-switching
Authors: Cole Nicholas , Harvey Matthew , Myers-Joseph Dylan , Gilra Aditya , Khan Adil G. 
Published: August 2024

AbstractTask-switching is a fundamental cognitive ability that allows animals to update their knowledge of current rules or contexts. Detecting discrepancies between predicted and observed events is essential for this process. However, little is known about how the brain computes cognitive prediction-errors and whether neural prediction-error signals are causally related to task-switching behaviours. Here we trained mice to use a prediction-error to switch, in a single trial, between responding to the same stimuli using two distinct rules. Optogenetic silencing and un-silencing, together with widefield and two-photon calcium imaging revealed that the anterior cingulate cortex (ACC) was specifically required for this rapid task-switching, but only when it exhibited neural prediction-error signals. These prediction-error signals were projection-target dependent and were larger preceding successful behavioural transitions. An all-optical approach revealed a disinhibitory interneuron circuit required for successful prediction-error computation. These results reveal a circuit mechanism for computing prediction-errors and transitioning between distinct cognitive states.