bluuebunny/crossref_metadata_2025_split huggingface dataset:
Targeting Adhesive Tumor Adventitia via Injectable Electrospun Short Fibers in Perfusion of Intraperitoneal Sporadic Tumors
Authors: Ruan Dan , Wang Juan , Ding Tao , Chen Liang , Du Yawei , Ruan Yiyin , Cui Wenguo , Feng Weiwei 
Published: September 2023

AbstractIntraperitoneal sporadic tumor is a common and complicated syndrome in cancers, causing a high rate of death, and people find that intraperitoneal chemotherapy (IPC) can treat intraperitoneal sporadic tumors better than intravenous chemotherapy and surgery. However, the effectiveness and side effects of IPC are controversial, and the operation process of IPC is complicated. Herein, the injectable paclitaxel‐loaded (PTX‐loaded) electrospun short fibers are constructed through a series process of electrospinning, homogenizing, crosslinking, and subsequent polydopamine coating and folate acid (FA) modification. The evenly dispersed short fibers exhibited effective tumor cell killing and good injectable ability, which is convenient to use and greatly improved the complex operation procedure. Mussel‐like protein poly‐dopamine coating and FA modification endowed short fibers with the ability of targeted adhesion to tumors, and therefore the short fibers further acted as a kind of micro membrane that could release drugs to tumors at close range, maintaining local high drug concentration and prevent paclitaxel killing normal tissues. Thus, the target‐adhesive injectable electrospun short fibers are expected to be the potential candidate for cancer treatment, especially the intraperitoneal sporadic tumors, which are hard to treat by surgery or intravenous chemotherapy.
Building Smarter Aqueous Batteries
Authors: Deng Canbin , Li Yiqing , Huang Jiaqiang 
Published: September 2023

AbstractAmidst the global trend of advancing renewable energies toward carbon neutrality, energy storage becomes increasingly critical due to the intermittency of renewables. As an alternative to lithium‐ion batteries (LIBs), aqueous batteries have received growing attention for large‐scale energy storage due to their economical and safe features. Despite the fruitful achievements at the material level, the reliability and lifetime of aqueous batteries are still far from satisfactory. Alike LIBs, integrating smartness is essential for more reliable and long‐life aqueous batteries via operando monitoring and automatic response to extreme abuses. In this review, recent advances in sensing techniques and multifunctional battery‐sensor systems together with self‐healing methods in aqueous batteries is summarized. The significant role of artificial intelligence in designing and optimizing aqueous batteries with high efficiency is also highlighted. Ultimately, it is extrapolated toward the future and present the humble perspective for building smarter aqueous batteries.
Development of reflective cooling plasticized polyvinyl chloride/precipitated barium sulfate composites for building roof applications throughout entire solar wavebands
Authors: Han Songcheng , Yang Zhangbin , Zhang Ling , Zhang Zhen , Zhang Jun 
Published: September 2023

AbstractBarium sulfate (BaSO4) has high reflectance throughout entire solar waveband (280–2500 nm). In this study, the melt blending method was used to incorporate BaSO4 into a plasticized polyvinyl chloride (PVC) matrix. The aim was to create composites that exhibit excellent reflective cooling performance in the solar waveband, specifically for use in building roofs. By increasing the content of BaSO4 from 0 to 200 phr, the total reflectance of the samples in the solar waveband showed significant improvement, rising from 6% to 48.8%. Furthermore, the thermal conductivity of the samples accordingly emerged apparent enhancement, increasing by 46.3% from 0.178 to 0.262 W m−1 K−1. Additionally, when subjected to irradiation by a solar simulator under a solar light intensity of 1000 W/m2 for 1 h, the indoor simulated irradiation temperature decreased from 41.4 to 27.4°C.Highlights
White plasticized polyvinyl chloride (PVC) films with reflective cooling performance were prepared.
The solar reflectance and cooling performance of PVC was enhanced by BaSO4.
The reflectance mechanism of BaSO4 in PVC was established.
Generalized thermal properties of hybrid NANOLIQUID composed of aluminum oxide (Al2O3) and silver (Ag) nanoparticles with water (H2O) as base liquid
Authors: Parveen Nabeela , Awais Muhammad , Awan Saeed Ehsan 
Published: September 2023

AbstractHeat transfer rate is numerically analyzed in convective flow of Al2O3‐Ag/ H2O hybrid nanoliquid through a stretching sheet by incorporating induced magnetic field. Results of entropy generation in system are evaluated as well. Considered physical factors associated with heat transfer are heat generation parameter and viscous dissipation. The system of nonlinear partial differential equations is modeled and dimensionally simplified by implementing boundary layer approximation assumption and proper similarity transformations. Adam's Bashforth method is applied to get highly accurate and stable numerical solutions. Numerical results of flow variables, entropy generation number and physical quantities are interpreted by way of graphs and bar charts to perceive the extensive significance of the problem. It is visualized that rise in numeric values of mixed convection parameter λ1 leads to enhance velocity; entropy generation number and Nusselt number while suppress temperature. High magnitude of heat generation parameter δ augments velocity and temperature but reverse behavior is observed for Nusselt number and entropy generation number. Moreover, the factor of viscous dissipation significantly modifies rate of flow and heat transfer under the effect of no‐slip condition on sheet. The present study is useful in different fields of industries, technological processes, mechanical processes, and electrical processes due to the applications of magnetic hybrid nanofluid with improved heat and mass transfer.
Decay of the mediator particle at threshold
Authors: Matsumoto Shigeki , Watanabe Yu , Watanabe Yuki , White Graham 
Published: September 2023

Abstract
A light mediator particle is often predicted in the dark sector scenario, which weakly interacts with the standard model (SM) particles. The weakness of the interaction is usually described by a small coupling; however, the small coupling does not always guarantee the weakness of the interaction. When the mass of the mediator particle lies in a threshold region, the so-called threshold singularity may emerge, and then the perturbative calculation fails. This singularity causes several effects, e.g., the mixing between the mediator particle and bound states, the Sommerfeld effect on the final state of the mediator particle decay, etc. Taking the minimal model of the vector mediator particle decaying mainly into the SM particles as an example, we develop a method to describe the singularity quantitatively. We also calculate some physical quantities using this method, such as the lifetime of the mediator particle and find that those could be significantly altered compared with the result of the perturbative calculation.
Black hole extremality in nonlinear electrodynamics: a lesson for weak gravity and Festina Lente bounds
Authors: Abe Yoshihiko , Noumi Toshifumi , Yoshimura Kaho 
Published: September 2023

Abstract
We study black hole extremality in nonlinear electrodynamics motivated by the Weak Gravity Conjecture (WGC) and the Festina Lente (FL) bound. For illustration, we consider the Euler-Heisenberg model and the Dirac-Born-Infeld model in asymptotically flat spacetime, de Sitter spacetime, and anti-de Sitter spacetime. We find that in all cases the extremal condition enjoys a certain monotonicity expected by the WGC. This provides evidence for the conjecture beyond the leading order corrections to the Einstein-Maxwell theory. We also study how light charged particles modify the mass-charge relation of Nariai black holes in de Sitter spacetime and discuss possible implications for the FL bound. Besides, we point out an interesting similarity between our black hole analysis and gravitational positivity bounds on scattering amplitudes.
Anomaly and double copy in quantum self-dual Yang-Mills and gravity
Authors: Monteiro Ricardo , Stark-Muchão Ricardo , Wikeley Sam 
Published: September 2023

Abstract
Recent works have explored how scattering amplitudes in quantum self-dual Yang-Mills theory and self-dual gravity can be interpreted as resulting from an anomaly, as first proposed by W. Bardeen. We study this problem in the light-cone-gauge formulation of the theories. Firstly, we describe how the infinite tower of symmetries associated to classical integrability can be quantum corrected, exhibiting the one-loop anomaly. Secondly, we present quantum-corrected light-cone Lagrangians worthy of the simplicity of the amplitudes, building on recent works describing the anomaly in twistor space. Finally, we discover an unexpected BCJ-like double copy for the (loop-integrated) amplitudes, distinct from the well-known BCJ double copy for the loop integrands.
Subduction–exhumation cycle recorded by calcite deformation microstructures: blueschist-facies metacarbonates and kinematic implications for deformation of the Meliata Unit (Western Carpathians)
Authors: Potočný Tomáš , Jeřábek Petr , Plašienka Dušan 
Published: September 2023

AbstractThe Meliata Unit (Meliaticum) is a tectonic superunit of the Western Carpathians that incorporates the blueschists-facies Bôrka Nappe and the low-grade metasediments and polygenetic mélange, Meliata Unit s.s., both occurring as scattered tectonic slices overlying the Gemeric Superunit. Calcitic marbles were sampled in a wide area within the Bôrka Nappe and blocks embedded in Jurassic oceanic sediments (Meliata Unit s.s.). Based on the microstructural evaluation and electron backscatter diffraction analysis (EBSD), the carbonates of the Bôrka Nappe experienced differential post-subduction P–T–D paths related to a collisional/exhumation setting following closure of the Neotethys-related “Meliata Ocean”. Variations in the calcite deformation microstructures were used to distinguish three principal microstructural groups. The first group (G1) contains large columnar and lobate calcite grains (≥ 1 mm) reflecting peak P–T conditions during subduction of the Meliata oceanic lithosphere. The second group (G2) exhibits dynamic recrystallization of the original G1 grains resulting in grain size reduction (< 0.5 mm) and shape-preferred orientation related to exhumation and formation of the accretionary complex. The third group (G3) shows a ‘foam’ microstructure with a uniform grain size (0.4–1 mm), sharp grain boundaries and triple junctions. The G3 microstructure may have been caused by a static recrystallization at elevated temperatures postdating the main deformation, and it is restricted to peripheries of the underlying Veporic metamorphic dome and probably is not associated with the Meliata sequences nor its tectono-metamorphic evolution. The corrected kinematic sections indicate dominantly ESE–WNW-trending lineations suggesting top-to-WNW kinematics of the Meliata subduction–exhumation process for G1 and G2 microstructures, and Gemeric–Veporic E–W orogen-parallel stretching for G3.
Evaluating normative capacity through Arctic environmental governance
Authors: Wood-Donnelly Corine 
Published: September 2023

AbstractInternational cooperation in the Arctic is largely operationalised through environmental governance in a constellation of institutions that promote scientific knowledge of the Arctic region. While the Arctic Council is placed at the centre of this network for environmental protection and resource management across the region, other institutions play critical roles in facilitating scientific knowledge production that promotes the security and development of the region and its resources across national boundaries. Evaluating the role of environmental protection in Arctic governance within models of science diplomacy, this paper argues that the assumption of environmental responsibility should act as a normative operator for Arctic environmental governance, shaping the relations between actors in this regional network and legitimising decision-making by Arctic states as they socially construct the mechanisms and regional exceptionalism of Arctic governance. However, environmental responsibility falls short of acting as a normative operator for environmental protection that also prevents the impact of climate change on the Arctic environment, excluding its function as an overarching normative operator for the international system, reducing state legitimacy for regional decision-making in extra-territorial spaces.
Is deeper always better? Evaluating deep learning models for yield forecasting with small data
Authors: Sabo Filip , Meroni Michele , Waldner François , Rembold Felix 
Published: September 2023

AbstractPredicting crop yields, and especially anomalously low yields, is of special importance for food insecure countries. In this study, we investigate a flexible deep learning approach to forecast crop yield at the provincial administrative level based on deep 1D and 2D convolutional neural networks using limited data. This approach meets the operational requirements—public and global records of satellite data in an application ready format with near real time updates—and can be transferred to any country with reliable yield statistics. Three-dimensional histograms of normalized difference vegetation index (NDVI) and climate data are used as input to the 2D model, while simple administrative-level time series averages of NDVI and climate data to the 1D model. The best model architecture is automatically identified during efficient and extensive hyperparameter optimization. To demonstrate the relevance of this approach, we hindcast (2002–2018) the yields of Algeria’s three main crops (barley, durum and soft wheat) and contrast the model’s performance with machine learning algorithms and conventional benchmark models used in a previous study. Simple benchmarks such as peak NDVI remained challenging to outperform while machine learning models were superior to deep learning models for all forecasting months and all tested crops. We attribute the poor performance of deep learning to the small size of the dataset available.
Deep Reinforcement Learning with Heuristic Corrections for UGV Navigation
Authors: Wei Changyun , Li Yajun , Ouyang Yongping , Ji Ze 
Published: September 2023

AbstractMapless navigation for mobile Unmanned Ground Vehicles (UGVs) using Deep Reinforcement Learning (DRL) has attracted significantly rising attention in robotic and related research communities. Collision avoidance from dynamic obstacles in unstructured environments, such as pedestrians and other vehicles, is one of the key challenges for mapless navigation. This paper proposes a DRL algorithm based on heuristic correction learning for autonomous navigation of a UGV in mapless configuration. We use a 24-dimensional lidar sensor, and merge the target position information and the speed information of the UGV as the input of the reinforcement learning agent. The actions of the UGV are produced as the output of the agent. Our proposed algorithm has been trained and evaluated in both static and dynamic environments. The experimental result shows that our proposed algorithm can reach the target in less time with shorter distances under the premise of ensuring safety than other algorithms. Especially, the success rate of our proposed algorithm is 2.05 times higher than the second effective algorithm and the trajectory efficiency is improved by $$24\%$$

24
%

in the dynamic environment. Finally, our proposed algorithm is deployed on a real robot in the real-world environment to validate and evaluate the algorithm performance. Experimental results show that our proposed algorithm can be directly applied to real robots robustly.
Childhood obesity, metabolic syndrome, and oxidative stress: microRNAs go on stage
Authors: González-Domínguez Álvaro , Belmonte Thalía , González-Domínguez Raúl 
Published: September 2023

AbstractThe incidence of childhood obesity and metabolic syndrome has grown notably in the last years, becoming major public health burdens in developed countries. Nowadays, oxidative stress is well-recognized to be closely associated with the onset and progression of several obesity-related complications within the framework of a complex crosstalk involving other intertwined pathogenic events, such as inflammation, insulin disturbances, and dyslipidemia. Thus, understanding the molecular basis behind these oxidative dysregulations could provide new approaches for the diagnosis, prevention, and treatment of childhood obesity and associated disorders. In this respect, the transcriptomic characterization of miRNAs bares great potential because of their involvement in post-transcriptional modulation of genetic expression. Herein, we provide a comprehensive literature revision gathering state-of-the-art research into the association between childhood obesity, metabolic syndrome, and miRNAs. We put special emphasis on the potential role of miRNAs in modulating obesity-related pathogenic events, with particular focus on oxidative stress.
Nanostructured copper-organic frameworks for the generation of sulphate radicals: application in wastewater disinfection
Authors: Giráldez Alba , Fdez-Sanromán Antía , Terrón Daniel , Sanromán M Angeles , Pazos Marta 
Published: September 2023

AbstractIn recent years, the presence of pathogens in the environment has become an issue of widespread concern in society. Thus, new research lines have been developed regarding the removal of pathogens and persistent pollutants in water. In this research, the efficacy of nanostructure copper-organic framework, HKUST-1, has been evaluated for its ability to eliminate Escherichia coli and generate sulphate radicals as catalyst for the treatment of effluents with a high microbiological load via peroxymonosulphate (PMS) activation. The disinfection process has been optimized, achieving complete elimination of Escherichia coli growth after 30 min of testing using a concentration of 60.5 mg/L HKUST-1 and 0.1 mM of PMS. To overcome the operational limitations of this system and facilitate its handling and reutilization in a flow disinfection process, HKUST-1 has been efficiently encapsulated on polyacrylonitrile as a novel development that could be scaled up to achieve continuous treatment.
Mental health, gender, and higher education attainment
Authors: Burger Kaspar , Strassmann Rocha Diego 
Published: September 2023

AbstractWe compared the mental health of higher education students with that of nonstudents. Moreover, we examined whether the mental health of students predicts their probability of obtaining a higher education degree, and whether the extent to which mental health affects educational attainment varies by gender. Drawing on a risk and resilience framework, we considered five facets of mental health that may be implicated in distinct ways in the educational attainment process: positive attitude towards life, self-esteem, self-efficacy, negative affectivity, and perceived stress. We used data from a nationally representative panel study from Switzerland (Nstudents = 2070, 42.8% male;Nnonstudents = 3755, 45.9% male). The findings suggest that overall, the mental health of higher education students was relatively similar to that of nonstudents, although students exhibited slightly higher self-esteem, slightly weaker self-efficacy, greater negative affectivity, and higher levels of perceived stress. The effects of different facets of mental health on higher education degree attainment were mostly statistically and/or practically insignificant. However, positive attitudes towards life had a substantial positive effect on the probability of being awarded a higher education degree. Mental health was equally important for male and female students’ educational attainment.
Direct generation of Zn metal using laser-induced ZnS to eradicate carbon emissions from electrolysis Zn production
Authors: Chen Ying , Duan Ning , Jiang Linhua , Xu Fuyuan , Zhu Guangbin , Wang Yao , Liu Yong , Cheng Wen , Xu Yanli 
Published: September 2023

Abstract
In response to the goal of net-zero emissions proposed by Intergovernmental Panel on Climate Change, Chinese government has pledged that carbon emissions will peak by 2030, and achieve carbon neutrality by 2060. However, the high carbon energy structure of traditional industries has aggravated environmental problems, such as greenhouse effect and air pollution. The goal of carbon neutrality will be difficult to achieve without the development of disruptive theories and technologies. The electrolytic zinc industry requires high-temperature roasting at ∼1000 °C, generating large amounts of greenhouse gases and SO2. High concentrations of sulfuric acid (200 g/L) are subsequently used for electrolysis, and each ton of zinc produced generates 50 kg of anode slime with lead content of up to 16%, as well as 0.35 m3 of wastewater containing zinc and lead. To solve these problems, an optical metallurgy method is proposed in this study. The proposed method uses laser-induced photoreduction to decompose ZnS and reduce metal ions to metal. Results indicate that Zn0 and S8 can be detected on the surface of ZnS at a specific wavelength and laser fluence. The generation mechanism of Zn0 is such that laser induces an electronic transition that breaks ionic bond in ZnS, resulting in its decomposition and photoreduction to Zn0 under an inert argon gas atmosphere. This method does not reduce other metals in the mineral since it does not use high-temperature roasting, providing a new way of producing high-purity metal without greenhouse gas emissions and heavy metal pollution caused by traditional zinc electrolysis.
Local large deviations for periodic infinite horizon Lorentz gases
Authors: Melbourne Ian , Pène Françoise , Terhesiu Dalia 
Published: September 2023

AbstractWe prove optimal local large deviations for the periodic infinite horizon Lorentz gas viewed as a ℤd-cover (d = 1,2) of a dispersing billiard. In addition to this specific example, we prove a general result for a class of nonuni-formly hyperbolic dynamical systems and observables associated with central limit theorems with nonstandard normalisation.