bluuebunny/crossref_metadata_2025 huggingface dataset:
Fiber Elastomer Modified Asphalt for the Development of Resilient Porous Asphalt Mixtures
Authors: Saudy Maram , Khedr Safwan , El-Badawy Sherif
Published: August 2024

Heavy rain is one of the extreme weather events which pose a variety of serious risks on transportation infrastructures. Porous asphalt pavement can be used as a sustainable solution to mitigate the effects of such heavy rains. The objective of this study was to study the potential of using fiber elastomer modifier (FEM) to produce porous asphalt mixtures of high quality and enhanced performance. This was done through an experimental program composed of three different phases. The first phase was the development and the rheological, chemical, and microstructural characterization of the FEM modified asphalt. The second phase focused on using FEM to produce porous asphalt mixtures using different techniques. The third phase was the characterization of the porous asphalt mixtures to study their anticipated performance. The FEM asphalt performance grade, PG (76-22), proved enhanced rheological properties in terms of better rutting resistance indicated by higher G*/sin δ over a wide range of temperatures and lower Jnr3.2 value of about 19% compared to the virgin asphalt and an enhanced fatigue cracking resistance manifested by the significant reduction in the fatigue cracking indicator G* sin δ with about 94%. Finally, porous asphalt mixtures were produced of an enhanced performance based on the dynamic modulus. Higher E* values at higher temperatures/lower frequencies and lower E* values at lower temperatures/higher frequencies were reported for the FEM porous asphalt mixture in reference to the, control dense-graded HMA mixture, promising an enhanced both rutting and fatigue resistances of the produced porous asphalt mixtures.
Developing quality community connections through a regional preservice teacher placement program
Authors: Murphy Steve , Acquaro Daniela , Baxter Lindy , Miles-Keogh Rebecca , Cuervo Hernan , Walker-Gibbs Bernadette
Published: August 2024

The recruitment and retention of teachers in regional, rural and remote areas of Australia remains a persistent challenge. Greater awareness of and experience in regional, rural and remote schools is a common strategy adopted by initial teacher education providers to mediate this challenge. This paper examines the quality of connection between preservice teachers and a regional community developed through a multi-university placement program. The program adopted a multi-faceted approach to building quality community connections—fostering preservice teacher connections to a cohort of preservice teachers, to regional schools, and to a regional area. Findings suggest this tripartite approach enhanced the quality of all connections, positioning the program as a useful model for developing a pipeline of preservice teachers to regional schools struggling to find teaching staff.
Schools and the city: workforce distribution, housing and city schools
Authors: Eacott Scott , Gilbert Catherine , MacDonald Katrina
Published: August 2024

Attracting and retaining a stable supply of effective teachers is critical to the provision of schooling that meets international commitments to equity, excellence, and inclusion. Initiatives targeting school staff are predicated on the accessibility of schools for the workforce. To this point, the empirical impact of housing and transportation costs on the school education workforce has been relatively poorly understood. Based on a novel approach describing workforce distribution, our analysis of the Greater Sydney statistical area in Australia found that not only is the city unaffordable for the school education workforce, but unobserved characteristics (e.g., intergenerational wealth, housing assets, high income housemates) fill the income to cost gap. De-centring the individual, we show that the sustainability of the Sydney school education workforce is fragile and should it collapse, the consequences would be sudden and acute.
Robust asymptotic insurance-finance arbitrage
Authors: Oberpriller Katharina , Ritter Moritz , Schmidt Thorsten
Published: August 2024

This paper studies the valuation of insurance contracts linked to financial markets, for example through interest rates or in equity-linked insurance products. We build upon the concept of insurance-finance arbitrage as introduced by Artzner et al. (Math Financ, 2024), extending their work by incorporating model uncertainty. This is achieved by introducing statistical uncertainty in the underlying dynamics to be represented by a set of priors $${{\mathscr {P}}}$$
P
. Within this framework we propose the notion of robust asymptotic insurance-finance arbitrage (RIFA) and characterize the absence of such strategies in terms of the new concept of $${Q}{{\mathscr {P}}}$$

Q
P

-evaluations. This nonlinear two-step evaluation ensures absence of RIFA. Moreover, it dominates all two-step evaluations, as long as we agree on the set of priors $${{\mathscr {P}}}$$
P
. Our analysis highlights the role of $${Q}{{\mathscr {P}}}$$

Q
P

-evaluations in terms of showing that all two-step evaluations are free of RIFA. Furthermore, we introduce a doubly stochastic model to address uncertainty for surrender and survival, utilizing copulas to define conditional dependence. This setting illustrates how the $${Q}{{\mathscr {P}}}$$

Q
P

-evaluation can be applied for the pricing of hybrid insurance products, highlighting the flexibility and potential of the proposed approach.
Real-Time Tunable Gas Sensing Platform Based on SnO2 Nanoparticles Activated by Blue Micro-Light-Emitting Diodes
Authors: Nam Gi Baek , Ryu Jung-El , Eom Tae Hoon , Kim Seung Ju , Suh Jun Min , Lee Seungmin , Choi Sungkyun , Moon Cheon Woo , Park Seon Ju , Lee Soo Min , Kim Byungsoo , Park Sung Hyuk , Yang Jin Wook , Min Sangjin , Park Sohyeon , Cho Sung Hwan , Kim Hyuk Jin , Jun Sang Eon , Lee Tae Hyung , Kim Yeong Jae , Kim Jae Young , Hong Young Joon , Shim Jong-In , Byun Hyung-Gi , Park Yongjo , Park Inkyu , Ryu Sang-Wan , Jang Ho Won
Published: August 2024

Micro-light-emitting diodes (μLEDs) have gained significant interest as an activation source for gas sensors owing to their advantages, including room temperature operation and low power consumption. However, despite these benefits, challenges still exist such as a limited range of detectable gases and slow response. In this study, we present a blue μLED-integrated light-activated gas sensor array based on SnO2 nanoparticles (NPs) that exhibit excellent sensitivity, tunable selectivity, and rapid detection with micro-watt level power consumption. The optimal power for μLED is observed at the highest gas response, supported by finite-difference time-domain simulation. Additionally, we first report the visible light-activated selective detection of reducing gases using noble metal-decorated SnO2 NPs. The noble metals induce catalytic interaction with reducing gases, clearly distinguishing NH3, H2, and C2H5OH. Real-time gas monitoring based on a fully hardware-implemented light-activated sensing array was demonstrated, opening up new avenues for advancements in light-activated electronic nose technologies.
Glass edges in the building industry: examination method and design approaches
Authors: Bukieda Paulina , Meyer Katharina , Engelmann Michael , Weller Bernhard
Published: August 2024

In the building industry, different types of glass edges are used depending on their application and function. A widespread assumption is that the edge strength increases with the degree of optical finishing. This corresponds with the European standardisation, which targets an adjustment of the bending strength in form of edge finishing factors. Thereby the highest edge strength is set with polished edges. This article presents research which shows that the recommended edge finishing factors of annealed glass can be insufficient, particularly for the polished edge. Comparison with previous scientific studies confirms a high scatter in the edge strengths of different manufacturers. However, there are no generally valid grinding process parameters that can be associated with a high edge strength. Consequently, general edge strength values have to be questioned, as they potentially lead to safety concerns. Thus, the processes have to be investigated individually. For this purpose, an examination method with fracture tests and a microscopic defect analysis for process optimisation is introduced. Based on the results of two different edge grinding machines, the formation of defects is presented and their potential of causing early breakage is discussed. In an overall evaluation, approaches are proposed on how the manufacturing of glass edges with high edge strength can be verified and included in the design.
Unravelling superior photodegradation ability and key photoactive structures of hydrochar particle to typical emerging contaminant than corresponding bulk hydrochar from food waste
Authors: Guo Wenjing , Zhang Zhiyong , Feng Yanfang , Fang Guodong , He Shiying , Rong Shaopeng
Published: August 2024

Hydrochar from waste biomass is a promising material for removing emerging contaminants (e.g., antibiotics) in water/soil environment. Abundant small-sized hydrochar particles (HPs) with a high content of reactive functional groups and high mobility are easily released into ecosystems through hydrochar applications. However, the photodegradation ability and corresponding structures of HPs are largely unknown, which hinder accurate estimation of the remediation effect of hydrochar in ecosystems. Herein, photodegradation performance of HP towards targeted norfloxacin (NOR, a typical antibiotic) under light irradiation (visible and UV light) were investigated after adsorption processes upon release into soil/water, and its reactive species and photoactive structures were clarified and compared with those of residual bulk hydrochar (BH) comprehensively. The results showed that: (1) photodegradation percentages of HPs were 4.02 and 4.48 times higher than those of BHs under UV and visible light, in which reactive species of both HPs and BHs were ·OH and ·O2−; (2) density functional theory (DFT) results identified that the main photoactive structure of graphitic-N decreased the energy gap (Eg) of HPs, and C=O, COOH groups improved electron donating ability of BHs; (3) well-developed graphitization structure of HP resulted from higher polymerization reaction was an significant photoactive structure involving its superior photodegradation ability relative to that of BH. The distinct heterogeneities of photodegradation ability in HP and BH and underlying photoactive structures provide an in-depth understanding of hydrochar application for removing emerging contaminants in soil/water environment. Identifying photoactive structures is helpful to predict photodegradation ability of hydrochar according to their abundance.

Graphical Abstract
Effects of Five Serial Apnoeas Prior to a Running Time Trial in Competitive Athletes
Authors: Barlow Matthew John , Ross Catherine , Cockrell Remmie , Rubie Morgan , Cahill Harry , Robertson Craig , French Jamie , Elia Antonis
Published: August 2024

Purpose

This study aimed to determine whether a series of repeated maximal voluntary apnoeas is effective in improving subsequent time trial performance in competitive level track and field athletes.

Methods

Seventeen competitive runners volunteered for this study and based on their preferred competitive distance they were placed either in the 200 m (5 male, 4 female) or 1000 m group (3 male, 5 female). On two separate occasions (≤ 7 days apart), the participants performed a running time-trial that was preceded either by: (i) a standardised warm up (WO) or (ii) a standardised warm up succeeded by five repeated maximal dry static apnoeas (WA). Splenic volume, haematology and cardiovascular parameters were monitor at rest, before and after each time-trial.

Results

WA resulted in a significantly faster performance (27.51 ± 3.49 s;P = 0.009) compared with WO (27.96 ± 3.34 s) in the 200 m group, whereas no differences were observed in the 1000 m group (WA, 211.10 ± 26.18 s; WO, 215.82 ± 25.13 s,P = 0.120). No differences were noted in splenic volume between WO and WA in either group (P ≥ 0.081). Haemoglobin was significantly elevated after breath-holding in the 200 m (+ 7 g/dL,P = 0.041) but not 1000 m group.

Conclusion

This study demonstrates that five repeated maximal apnoeas are capable of significantly improving a 200 m but not a 1000 m time-trial performance in competitive track and field athletes.
Dynamic Mutation Strategy Selection in Differential Evolution Using Perturbed Adaptive Pursuit
Authors: Bajpai Prathu , Anicho Ogbonnaya , Nagar Atulya K. , Bansal Jagdish Chand
Published: August 2024

Diverse mutant vectors play a significant role in the performance of the Differential Evolution (DE). A mutant vector is generated using a stochastic mathematical equation, known as mutation strategy. Many mutation strategies have been proposed in the literature. Utilizing multiple mutation strategies with the help of an adaptive operator selection (AOS) technique can improve the quality of the mutant vector. In this research, one popular AOS technique known as perturbation adaptive pursuit (PAP) is integrated with the DE algorithm for managing a pool of mutation strategies. A community-based reward criterion is proposed that rewards the cumulative performance of the whole population. The proposed approach is called ‘Dynamic Mutation Strategy Selection in Differential Evolution using Perturbed Adaptive Pursuit (dmss-DE-pap)’. The performance of dmss-DE-pap is evaluated over the 30D and 50D optimization problems of the CEC 2014 benchmark test suite. Results are competitive when compared with other state-of-the-art evolutionary algorithms and some recent DE variants.
DiRecNetV2: A Transformer-Enhanced Network for Aerial Disaster Recognition
Authors: Shianios Demetris , Kolios Panayiotis S. , Kyrkou Christos
Published: August 2024

The integration of Unmanned Aerial Vehicles (UAVs) with artificial intelligence (AI) models for aerial imagery processing in disaster assessment, necessitates models that demonstrate exceptional accuracy, computational efficiency, and real-time processing capabilities. Traditionally Convolutional Neural Networks (CNNs), demonstrate efficiency in local feature extraction but are limited by their potential for global context interpretation. On the other hand, Vision Transformers (ViTs) show promise for improved global context interpretation through the use of attention mechanisms, although they still remain underinvestigated in UAV-based disaster response applications. Bridging this research gap, we introduce DiRecNetV2, an improved hybrid model that utilizes convolutional and transformer layers. It merges the inductive biases of CNNs for robust feature extraction with the global context understanding of Transformers, maintaining a low computational load ideal for UAV applications. Additionally, we introduce a new, compact multi-label dataset of disasters, to set an initial benchmark for future research, exploring how models trained on single-label data perform in a multi-label test set. The study assesses lightweight CNNs and ViTs on the AIDERSv2 dataset, based on the frames per second (FPS) for efficiency and the weighted F1 scores for classification performance. DiRecNetV2 not only achieves a weighted F1 score of 0.964 on a single-label test set but also demonstrates adaptability, with a score of 0.614 on a complex multi-label test set, while functioning at 176.13 FPS on the Nvidia Orin Jetson device.
Investigating the drivers of urban cover-collapse sinkholes in shanghai: analyzing dominant factors and proposing mitigation strategies
Authors: Li Bing , Wang Hanmei , Tang Hang
Published: August 2024

Urban cover-collapse sinkholes pose a significant global challenge due to their destructive impacts. Previous studies have identified groundwater fluctuations, subsurface soil conditions, pipeline leakage, precipitation, and subterranean construction activities as key contributors to these phenomena. However, unique geological settings across different urban environments lead to variations in the primary factors influencing sinkhole formation. This study focuses on Shanghai, a city notable for its extensive urbanization and rich historical context, to explore the dynamics of sinkholes within urbanized areas worldwide. We employ spatial analysis and statistical methods to examine data on sinkholes recorded in the past two decades in Shanghai, correlating these events with the city’s shallow sand layer, ground elevation, and proximity to surface water. Our goal is to identify the dominant factors governing sinkhole occurrence in Shanghai and to lay the groundwork for their effective scientific management and prevention. Key findings indicate that most sinkholes in the area are associated with a thin shallow sand layer, low to moderate ground elevations, and the absence of nearby rivers. Additionally, many sinkholes correlate with subterranean voids within the confined aquifer beneath the cohesive soil layer. The lack of historical river channels, obscured by urban development, also indirectly contributes to sinkhole formation. We recommend enhancing urban river management and drainage systems to mitigate potential damage from water accumulation.
Global Environmental Constraints on Magnetic Reconnection at the Magnetopause From In Situ Measurements
Authors: Michotte de Welle B. , Aunai N. , Lavraud B. , Génot V. , Nguyen G. , Ghisalberti A. , Smets R. , Jeandet A.
Published: August 2024

Progress in locating the X‐line on the magnetopause beyond the atypical due south interplanetary magnetic field (IMF) condition is hampered by the fact that the global plasma and field spatial distributions constraining where reconnection could develop on the magnetopause are poorly known. This work presents global maps of the magnetic shear, current density and reconnection rate, on the global dayside magnetopause, reconstructed from two decades of measurements from Cluster, Double Star, THEMIS and MMS missions. These maps, generated for various IMF and dipole tilt angles, offer a unique comparison point for models and observations. The magnetic shear obtained from vacuum magnetostatic draping is shown to be inconsistent with observed shear maps for IMF cone angles in 12.5° ± 2.5° ≤ |θco| ≤ 45° ± 5°. Modeled maximum magnetic shear lines fail to incline toward the equator as the IMF clock angle increases, in contrast to those from observations and MHD models. Reconnection rate and current density maps are closer together than they are from the shear maps, but this similarity vanishes for increasingly radial IMF orientations. The X‐lines maximizing the magnetic shear are the only ones to sharply turns toward and follow the anti‐parallel ridge at high latitude. We show the behavior of X‐lines with varying IMF clock and dipole tilt angles to be different as the IMF cone angle varies. Finally, we discuss a fundamental disagreement between X‐lines maximizing a given quantity on the magnetopause and predictions of local X‐line orientations.
Soil Microbial Community in 47 Chinese Forest Sites: Biogeographic Patterns and Links With Soil Dissolved Organic Matter
Authors: Zhang Zongxiao , Zhang Qiang , Wang Yinghui , Zhang Peng , Deng Guisen , Sun Guodong , Yang Yuanxi , Jiang Ke , Jiao Shuo , Guo Xue , Wang Junjian
Published: August 2024

Soils in forested ecosystems are extremely heterogeneous and represent a critical component of terrestrial ecosystems. Despite their substantial ecological value, the geographic characteristics, ecological processes, and coexistence of microbial communities in forest soils remain poorly understood. Here, we investigated the biodiversity dynamics, environmental influences, community assembly, and co‐occurrence patterns of bacterial and fungal communities in surface and subsurface soils across 47 Chinese forest sites. The biogeographic characteristics determined using high‐throughput sequencing data sets revealed evident spatial patterns of bacterial and fungal α and β diversity, assembly processes, and co‐occurrence relationship, with greater variation in the bacterial than in fungal communities. Both fungal and bacterial communities showed significant spatial separations regulated by community assembly processes, co‐occurrence patterns, and soil variables. The microbial dissimilarity was lower in high latitudes than in low latitudes, which was consistent with the lower deterministic processes and relatively higher co‐occurrence associations in high latitudes than in low latitudes. Additionally, there were significant associations of soil dissolved organic matter (DOM) characteristics (e.g., its content, aromaticity, and molecular weight) with biodiversity dissimilarities, microbial assembly process balances, and microbial co‐occurrence relationships in bacterial and fungal communities; they clearly indicate the key role of DOM in regulating microbial biogeographic patterns in forest soil ecosystems. Collectively, our study enhances the understanding of biogeographic patterns and coexistence theories in forest soil microbial ecosystems.
A Machine Learning Bias Correction on Large‐Scale Environment of High‐Impact Weather Systems in E3SM Atmosphere Model
Authors: Zhang Shixuan , Harrop Bryce , Leung L. Ruby , Charalampopoulos Alexis‐Tzianni , Barthel Sorensen Benedikt , Xu Wenwei , Sapsis Themistoklis
Published: August 2024

Large‐scale dynamical and thermodynamical processes are common environmental drivers of high‐impact weather systems causing extreme weather events. However, such large‐scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating high‐impact weather systems and extreme weather events. In this paper, a machine learning (ML) approach was employed to bias correct the large‐scale wind, temperature, and humidity simulated by the atmospheric component of the Energy Exascale Earth System Model (E3SM) at ∼1° resolution. The usefulness of the ML approach for extreme weather analysis was demonstrated with a focus on three high‐impact weather systems, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large‐scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve water vapor transport associated with ARs, and representations of thermodynamical flows associated with ETCs. When the bias‐corrected large‐scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large‐scale storm environments as well as the occurrence and intensity of three weather systems. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large‐scale storm environments simulated by low‐resolution climate models.
Data Assimilation in Chaotic Systems Using Deep Reinforcement Learning
Authors: Hammoud Mohamad Abed El Rahman , Raboudi Naila , Titi Edriss S. , Knio Omar , Hoteit Ibrahim
Published: August 2024

Data assimilation (DA) plays a pivotal role in diverse applications, ranging from weather forecasting to trajectory planning for autonomous vehicles. A prime example is the widely used ensemble Kalman filter (EnKF), which relies on the Kalman filter's linear update equation to correct each of the ensemble forecast member's state with incoming observations. Recent advancements have witnessed the emergence of deep learning approaches in this domain, primarily within a supervised learning framework. However, the adaptability of such models to untrained scenarios remains a challenge. In this study, we introduce a new DA strategy that utilizes reinforcement learning (RL) to apply state corrections using full or partial observations of the state variables. Our investigation focuses on demonstrating this approach to the chaotic Lorenz 63 and 96 systems, where the agent's objective is to maximize the geometric series with terms that are proportional to the negative root‐mean‐squared error (RMSE) between the observations and corresponding forecast states. Consequently, the agent develops a correction strategy, enhancing model forecasts based on available observations. Our strategy employs a stochastic action policy, enabling a Monte Carlo‐based DA framework that relies on randomly sampling the policy to generate an ensemble of assimilated realizations. Numerical results demonstrate that the developed RL algorithm performs favorably when compared to the EnKF. Additionally, we illustrate the agent's capability to assimilate non‐Gaussian observations, addressing one of the limitations of the EnKF.
Block Rotations in NW Iran in Response to the Arabia‐Eurasia Collision Constrained by Paleomagnetism
Authors: Niknam Ali , van der Boon Annique , Rezaeian Mahnaz , Kaymakcı Nuretdin , Langereis Cor
Published: August 2024

Northwest Iran is a seismically active region dominated by NW‐SE trending strike‐slip faults, such as the North Tabriz and Qosha Dagh faults, and smaller NNE‐SSW striking faults. The Bozgush Mountains are shaped by these faults and divided into two domains that show a difference in strike. To quantify rotational tectonic deformation in NW Iran, we performed a paleomagnetic study along three transects of the Bozgush and Qosha Dagh Mountains with 127 sites. Our large new paleomagnetic data set shows that the Bozgush Mountains did not rotate as a single rigid block. In the western domain of the Bozgush Mountains, we find evidence for clockwise vertical axis rotations of ∼40°, while the eastern domain has rotated up to ∼80° clockwise. Declinations of the western Bozgush domain fit well with observed declinations in the Qosha Dagh Mountains. Fault patterns show that the eastern domain of the Bozgush Mountains is divided by a set of NNE‐SSW striking sinistral strike‐slip faults, which created domino‐style blocks that accommodated the additional 40° of rotation. We estimate that these extra rotations have resulted in around 4 km of N‐S shortening and more than 1.5 km of differential uplift.
An Evaluation of Low‐Cost Terrestrial Lidar Sensors for Assessing Hydrogeomorphic Change
Authors: Perks M. T. , Pitman S. J. , Bainbridge R. , Díaz‐Moreno A. , Dunning S. A.
Published: August 2024

Accurate topographic data acquired at appropriate spatio‐temporal resolution is often the cornerstone of geomorphic research. Recent decades have seen advances in our ability to generate highly accurate topographic data, primarily through the application of remote sensing techniques. Structure from Motion‐Multi View Stereo (SfM‐MVS) and lidar have revolutionised the spatial resolution of surveys across large spatial extents. Technological developments have led to commercialisation of small form factor (SFF) 3D lidar sensors that are suited to deployment on both mobile (e.g., uncrewed aerial systems), and in fixed semi‐permanent installations. Whilst the former has been adopted, the potential for the latter to generate data suitable for geomorphic investigations has yet to be assessed. We address this gap here in the context of a 3‐month deployment where channel change is assessed in an adjusting fluvial system. We find that SFF 3D lidar sensors generate change detection products comparable to those generated using a conventional lidar system. Areas of no geomorphic change are characterised as such (mean 3D change of 0.014 m compared with 0.0014 m for the Riegl VZ‐4000), with differences in median change in eroding sections of between 0.02 and 0.04 m. We illustrate that this data enables: (a) accurate characterisation of river channel adjustments through extraction of bank long‐profiles; (b) the assessment of bank retreat patterns which help elucidate failure mechanics; and (c) the extraction of water surface elevations. The deployment of this technology will enable a better understanding of processes across a variety of geomorphic systems, as data can be captured in 4D with near real‐time processing.
Improving Sentinel‐3 Altimetry Data With GPD+ Wet Tropospheric Corrections
Authors: Fernandes M. J. , Vieira T. , Lázaro C. , Vasconcellos B. , Aguiar P.
Published: August 2024

The provision of accurate wet tropospheric corrections (WTC), accounting for the delay of the radar pulses caused mostly by the atmospheric water vapor in the altimeter‐range observations, is pivotal for the full exploitation of altimeter‐derived surface heights. The WTC is best retrieved by measurements from Microwave Radiometers (MWR) on board the same altimeter mission. However, these instruments fail to provide valid WTC over land and ice and under rainy conditions. The GNSS‐derived Path Delay Plus (GPD+) algorithm has been designed to provide WTC over these surfaces where the onboard MWR WTC is invalid. This study focuses on the estimation of enhanced GPD+ WTC for the Copernicus Sentinel‐3A and Sentinel‐3B satellites, for the latest Baseline Collection 005.02 (BC005.2), spanning the period since the beginning of the missions until March 2023. GPD+ corrections are being provided operationally since 2022 and have been adopted as the default WTC in the calculation of the sea level anomaly (SLA). Compared to previous versions, the BC005.2 GPD+ WTC features improved data combination procedures, possesses a larger percentage of points estimated from observations, a better intermission alignment and reduced systematic differences among ascending and descending passes. Overall, GPD+ WTC are consistent, calibrated corrections, valid over all points present in the Non Time Critical marine product, allowing to recover, on average, about 17% of the altimeter observations with valid SLA, which otherwise, most of them would be rejected. Impacts of these WTC are most significant over coastal and inland water regions, at high latitudes and during rain events.
How Energy Dissipation Mode Controls the Evolution of Multiple Plane‐Strain Hydraulic Fractures Under Isotropic Stresses
Authors: Cheng Shaoyi , Wu Bisheng , Zhang Xi , Huppert Herbert E. , Jeffrey Robert G.
Published: August 2024

The geometrical prediction of multiple hydraulic fractures fed from a single fluid source is a major challenge due to transient stress interference among fractures and nonlinear coupling between rock deformation and fluid flow. Here we find that the evolution of multiple hydraulic fractures under isotropic stresses is controlled by a dimensionless toughness, which measures the ratio of the energy dissipated in rock fracturing to that dissipated in viscous fluid flow. The existence of a relation between the dimensionless toughness and the dimensionless length of the arrested fractures is demonstrated by using a bifurcation analysis. The numerical results show that the fractures tend to grow simultaneously in the viscosity‐dominated regime, and the scaling remains effective when the number of fractures varies. This study provides a quantitative and efficient tool for predicting the fracture pattern in engineered and natural fracture systems.
Improving the Predictability of the US Seasonal Surface Temperature With Convolutional Neural Networks Trained on CESM2 LENS
Authors: An Yujay , Kim Hyemi
Published: August 2024

To better understand and improve the prediction of the seasonal surface temperature (TS) across the United States, we employed convolutional neural network (CNN) models trained on the Community Earth System Model Version 2 Large Ensemble (CESM2 LENS). We used lagged sea surface temperatures (SST) over the tropical Pacific region, containing the information of the El Niño Southern Oscillation (ENSO), as input for the CNN models. ENSO is the principal driver of variability in seasonal US surface temperatures (TSUS) and employing CNN models allows for spatiotemporal aspects of ENSO to be analyzed to make seasonal TSUS predictions. For predicting TSUS, the CNN models exhibited significantly improved skill over standard statistical multilinear regression (MLR) models and dynamical forecasts across most regions in the US, for lead times ranging from 1 to 6 months. Furthermore, we employed the CNN models to predict seasonal TSUS during extreme ENSO events. For these events, the CNN models outperformed the MLR models in predicting the effects on seasonal TSUS, suggesting that the CNN models are able to capture the ENSO‐TSUS teleconnection more effectively. Results from a heatmap analysis demonstrate that the CNN models utilize spatial features of ENSO rather than solely the magnitude of the ENSO events, indicating that the improved skill of seasonal TSUS is due to analyzing spatial variation in ENSO events. The proposed CNN model demonstrates a promising improvement in prediction skill compared to existing methods, suggesting a potential path forward for enhancing TSUS forecast skill from subseasonal to seasonal timescales.
Optimizing Radar Functionality: Development of a Steerable Patch Antenna Array With Enhanced Bandwidth
Authors: Alanazi Mubarak , Assisi Aladdin
Published: August 2024

Today, wireless communication systems need an antenna with a high gain, efficiency and beamsteering, as well as broadband capability, especially important in radar communications. The array antenna is commonly used in many applications due to its advantages, such as high gain and wide bandwidth. This paper presents an advanced design of a horizontally steerable planar antenna array intended for significant radar applications. A novel structure is used to create a compact array antenna of 8 × 3 elements. The design features a comprehensive 60° steering sector alongside a notable 12% bandwidth (4.45─5.42 GHz), using 8 × 3 planar array in an novel configuration. A three‐element series‐fed vertical array is utilized, employing aperture feeds with precisely sized patches to maximize performance. A detailed description of the design and refinement process of this array is presented, with emphasis on its exceptional capabilities for horizontal steering and bandwidth efficiency. By employing series‐fed vertical arrays with variable patch dimensions, we have successfully developed an antenna array that meets the stringent bandwidth requirements essential for radar technology, thereby enhancing the operational versatility of radar systems.
Metastable Helium Lidar for Thermosphere and Lower Exosphere Measurements: Instrument Description and Initial Results
Authors: Zhao Ruocan , Liu Zhenwei , Xue Xianghui , Zhou Hang , Wang Zhaofeng , Liu Yingyu , Li Jiangtao , Sun Dongsong , Lan Jiaxin , Chen Tingdi , Zhao Dongfeng , Dou Xiankang
Published: August 2024

In this work, we present a metastable helium lidar system for the measurements of metastable helium He(23S) density in the thermosphere and lower exosphere. This lidar system consists of a high power 1,083 nm pulsed laser, a 1 m aperture laser beam expander, six 1 m aperture receiving telescopes and a superconducting nanowire single‐photon detector (SNSPD). This system realizes metastable helium density detection up to 1,000 km. Daily rapid variation of metastable helium density within several hours was measured with a height resolution of 50 km for the first time. It demonstrates the capability of ground‐based lidar for continuous height‐resolved detection of the atmospheric metastable helium in the height range of 200–1,000 km. This is a promising tool to help study the coupling of neutral and ionized atmosphere in this height range and further providing observation basis for space weather prediction.
Elucidating the role of S100A10 in CD8+ T cell exhaustion and HCC immune escape via the cPLA2 and 5-LOX axis
Authors: Wang Ganggang , Shen Xiaowei , Jin Wenzhi , Song Chao , Dong Meiyuan , Zhou Zhijie , Wang Xiaoliang
Published: August 2024

Hepatocellular carcinoma (HCC) is a common malignant tumor with a complex immune evasion mechanism posing a challenge to treatment. The role of the S100A10 gene in various cancers has garnered significant attention. This study aims to elucidate the impact of S100A10 on CD8+ T cell exhaustion via the cPLA2 and 5-LOX axis, thereby elucidating its role in immune evasion in HCC. By analyzing the HCC-related data from the GEO and TCGA databases, we identified differentially expressed genes associated with lipid metabolism and developed a prognostic risk model. Subsequently, through RNA-seq and PPI analyses, we determined vital lipid metabolism genes and downstream factors S100A10, ACOT7, and SMS, which were significantly correlated with CD8+ T cell infiltration. Given the most significant expression differences, we selected S100A10 for further investigation. Both in vitro and in vivo experiments were conducted, including co-culture experiments of CD8+ T cells with MHCC97-L cells, Co-IP experiments, and validation in an HCC mouse model. S100A10 was significantly overexpressed in HCC tissues and potentially regulates CD8+ T cell exhaustion and lipid metabolism reprogramming through the cPLA2 and 5-LOX axis. Silencing S100A10 could inhibit CD8+ T cell exhaustion, further suppressing immune evasion in HCC. S100A10 may activate the cPLA2 and 5-LOX axis, initiating lipid metabolism reprogramming and upregulating LTB4 levels, thus promoting CD8+ T cell exhaustion in HCC tissues, facilitating immune evasion by HCC cells, ultimately impacting the growth and migration of HCC cells. This research highlights the critical role of S100A10 via the cPLA2 and 5-LOX axis in immune evasion in HCC, providing new theoretical foundations and potential targets for diagnosing and treating HCC.
ALYREF promotes the metastasis of nasopharyngeal carcinoma by increasing the stability of NOTCH1 mRNA
Authors: Jin Yanan , Yao Jijin , Fu Jianchang , Huang Qitao , Luo Yilin , You Yafei , Zhang Wangjian , Zhong Qian , Xia Tianliang , Xia Liangping
Published: August 2024

Approximately 70% of treatment failures in nasopharyngeal carcinoma (NPC) patients are attributed to distant metastasis, yet the underlying mechanisms remain unclear. RNA 5-methylcytosine (m5C) is an emerging regulatory modification that controls gene expression and plays a critical role in tumor progression. However, there is little information on the potential roles of RNA m5C modification in NPC metastasis. In this study, we found that the m5C reader Aly/REF export factor (ALYREF) is significantly upregulated in NPC, whereby its high expression is associated with metastasis and poor prognosis. ALYREF overexpression was found to promote tumor metastasis of NPC cells in vitro and in vivo. Mechanistically, m5C-modified NOTCH1 mRNA was identified as a target of ALYREF. Moreover, ALYREF was found to upregulate NOTCH1 expression by enhancing its RNA stability in an m5C modification-dependent manner, thereby promoting the activation of the NOTCH signaling pathway and facilitating NPC metastasis. Overall, our data reveal the crucial role of ALYREF in NPC metastasis and provide a potential therapeutic target for NPC.
Pyroptosis leads to loss of centrosomal integrity in macrophages
Authors: Bai Siyi , Martin-Sanchez Fatima , Brough David , Lopez-Castejon Gloria
Published: August 2024

NLRP3 forms a multiprotein inflammasome complex to initiate the inflammatory response when macrophages sense infection or tissue damage, which leads to caspase-1 activation, maturation and release of the inflammatory cytokines interleukin-1β (IL-1β) and IL-18 and Gasdermin-D (GSDMD) mediated pyroptosis. NLRP3 inflammasome activity must be controlled as unregulated and chronic inflammation underlies inflammatory and autoimmune diseases. Several findings uncovered that NLRP3 inflammasome activity is under the regulation of centrosome localized proteins such as NEK7 and HDAC6, however, whether the centrosome composition or structure is altered during the inflammasome activation is not known. Our data show that levels of the centrosomal scaffold protein pericentrin (PCNT) are reduced upon NLRP3 inflammasome activation via different activators in human and murine macrophages. PCNT loss occurs in the presence of membrane stabilizer punicalagin, suggesting this is not a consequence of membrane rupture. We found that PCNT loss is dependent on NLRP3 and active caspases as MCC950 and pan caspase inhibitor ZVAD prevent its degradation. Moreover, caspase-1 and GSDMD are both required for this NLRP3-mediated PCNT loss because absence of caspase-1 or GSDMD triggers an alternative regulation of PCNT via its cleavage by caspase-3 in response to nigericin stimulation. PCNT degradation occurs in response to nigericin, but also other NLRP3 activators including lysomotropic agent L-Leucyl-L-Leucine methyl ester (LLOMe) and hypotonicity but not AIM2 activation. Our work reveals that the NLRP3 inflammasome activation alters centrosome composition highlighting the need to further understand the role of this organelle during inflammatory responses.
Combination of eribulin and anlotinib exerts synergistic cytotoxicity in retroperitoneal liposarcoma by inducing endoplasmic reticulum stress
Authors: Li Shuquan , Zhang Hongtao , Yu Hao , Wu Yifan , Yan Liang , Guan Xiaoya , Dong Bin , Zhao Min , Tian Xiuyun , Hao Chunyi , Wu Jianhui
Published: August 2024

Primary retroperitoneal liposarcoma (RLPS) is a rare heterogeneous tumor occurring within retroperitoneal space, and its overall survival has not improved much in the past few decades. Based on a small-sample clinical practice at our center, patients with RLPS can greatly benefit from anlotinib and eribulin combination. In this study, we investigated the combinational effect of anlotinib and eribulin on RLPS. In vitro experiments revealed that a low dose of anlotinib significantly enhances the cytotoxic effects of eribulin, leading to a remarkable suppression of RLPS cell proliferation, viability, colony formation, migration, and cell-cycle progression compared to individual drug treatments. At the organoid level, the combination treatment causes the spheroids in Matrigel to disintegrate earlier than the single-drug group. In vivo, RLPS patient-derived xenograft (PDX) models demonstrated that the combination of these two drugs can obviously exert a safe and effective anti-tumor effect. Through transcriptome analysis, we uncovered and validated that the synergistic effect mainly is induced by the endoplasmic reticulum stress (ERS) pathway both in vitro and in vivo. Further analyses indicate that anlotinib plus eribulin treatment results in micro-vessel density and PD-L1 expression alterations, suggesting a potential impact on the tumor microenvironment. This study extensively explored the combination regimen at multiple levels and its underlying molecular mechanism in RLPS, thus providing a foundation for translational medicine research.
Proximity labelling of pro-interleukin-1α reveals evolutionary conserved nuclear interactions
Authors: Wellens Rose , Tapia Victor S. , Seoane Paula I. , Bennett Hayley , Adamson Antony , Coutts Graham , Rivers-Auty Jack , Lowe Martin , Green Jack P. , Lopez-Castejon Gloria , Brough David , Hoyle Christopher
Published: August 2024

Interleukin-1α is a suggested dual-function cytokine that diverged from interleukin-1β in mammals potentially by acquiring additional biological roles that relate to highly conserved regions in the pro-domain of interleukin-1α, including a nuclear localisation sequence and histone acetyltransferase-binding domains. Why evolution modified pro-interleukin-1α’s subcellular location and protein interactome, and how this shaped interleukin-1α’s intracellular role, is unknown. Here we show that TurboID proximity labelling with pro-interleukin-1α suggests a nuclear role for pro-interleukin-1α that involves interaction with histone acetyltransferases, including EP300. We also identify and validate inactivating mutations in the pro-interleukin-1α nuclear localisation sequence of multiple mammalian species, including toothed whales, castorimorpha and marsupials. However, histone acetyltransferase-binding domains are conserved in those species that have lost pro-interleukin-1α nuclear localisation. Together, these data suggest that histone acetyltransferase binding and nuclear localisation occurred together, and that while some species lost the nuclear localisation sequence in their pro-interleukin-1α, histone acetyltransferase binding ability was maintained. The nuclear localisation sequence was lost from several distinct species at different evolutionary times, suggesting convergent evolution, and that the loss of the nuclear localisation sequence confers some important biological outcome.
Achiral hard bananas assemble double-twist skyrmions and blue phases
Authors: Subert Rodolfo , Campos-Villalobos Gerardo , Dijkstra Marjolein
Published: August 2024

Skyrmions are topologically protected, vortex-like structures found in various condensed-matter systems including helical ferromagnets and liquid crystals, typically arising from chiral interactions. Using extensive particle-based simulations, we demonstrate that non-chiral hard banana-shaped particles, governed solely by excluded-volume interactions, spontaneously stabilize skyrmion structures through the bend-flexoelectric effect. Under thin confinement, we observe the formation of quasi-2D layers of isolated skyrmions or dense skyrmion lattices. These structures, comprising a racemic mixture of left- and right-handed skyrmions, show resilience against thermal fluctuations while remaining responsive to external fields, offering intriguing possibilities for manipulation. We also find that the size of these skyrmions can be adjusted by the dimensions and curvature of the banana-shaped particles. In the absence of geometric frustration due to confinement, a blue phase III may emerge, characterized by a 3D network of chiral skyrmion filaments of the nematic director field within an isotropic background. Our findings provide valuable insights into stabilizing skyrmion lattices and blue phases, showcasing non-Gaussian fluid-like dynamics in systems of achiral hard particles. Furthermore, they highlight the remarkable capacity of these complex fluids in designing advanced functional materials with diverse applications in photonics and memory devices.
ProDOL: a general method to determine the degree of labeling for staining optimization and molecular counting
Authors: Tashev Stanimir Asenov , Euchner Jonas , Yserentant Klaus , Hänselmann Siegfried , Hild Felix , Chmielewicz Wioleta , Hummert Johan , Schwörer Florian , Tsopoulidis Nikolaos , Germer Stefan , Saßmannshausen Zoe , Fackler Oliver T. , Klingmüller Ursula , Herten Dirk-Peter
Published: August 2024

Determining the label to target ratio, also known as the degree of labeling (DOL), is crucial for quantitative fluorescence microscopy and a high DOL with minimal unspecific labeling is beneficial for fluorescence microscopy in general. Yet robust, versatile and easy-to-use tools for measuring cell-specific labeling efficiencies are not available. Here we present a DOL determination technique named protein-tag DOL (ProDOL), which enables fast quantification and optimization of protein-tag labeling. With ProDOL various factors affecting labeling efficiency, including substrate type, incubation time and concentration, as well as sample fixation and cell type can be easily assessed. We applied ProDOL to investigate how human immunodeficiency virus-1 pathogenesis factor Nef modulates CD4 T cell activation measuring total and activated copy numbers of the adapter protein SLP-76 in signaling microclusters. ProDOL proved to be a versatile and robust tool for labeling calibration, enabling determination of labeling efficiencies, optimization of strategies and quantification of protein stoichiometry.