bluuebunny/crossref_metadata_2025 huggingface dataset:
Plasma proteomics-based brain aging signature and incident dementia risk
Authors: Kou Minghao , Ma Hao , Wang Xuan , Heianza Yoriko , Qi Lu
Published: November 2024

Investigating brain-enriched proteins with machine learning methods may enable a brain-specific understanding of brain aging and provide insights into the molecular mechanisms and pathological pathways of dementia. The study aims to analyze associations of brain-specific plasma proteomic aging signature with risks of incident dementia. In 45,429 dementia-free UK Biobank participants at baseline, we generated a brain-specific biological age using 63 brain-enriched plasma proteins with machine learning methods. The brain age gap was estimated, and Cox proportional hazards models were used to study the association with incident all-cause dementia, Alzheimer’s disease (AD), and vascular dementia. Per-unit increment in the brain age gap z-score was associated with significantly higher risks of all-cause dementia (hazard ratio [95% confidence interval], 1.67 [1.56–1.79], P < 0.001), AD (1.85 [1.66–2.08], P < 0.001), and vascular dementia (1.86 [1.55–2.24], P < 0.001), respectively. Notably, 2.1% of the study population exhibited extreme old brain aging defined as brain age gap z-score > 2, correlating with over threefold increased risks of all-cause dementia and vascular dementia (3.42 [2.25–5.20], P < 0.001, and 3.41 [1.05–11.13], P = 0.042, respectively), and fourfold increased risk of AD (4.45 [2.32–8.54], P < 0.001). The associations were stronger among participants with healthier lifestyle factors (all P-interaction < 0.05). These findings were corroborated by magnetic resonance imaging assessments showing that a higher brain age gap aligns global pathophysiology of dementia, including global and regional atrophy in gray matter, and white matter lesions (P < 0.001). The brain-specific proteomic age gap is a powerful biomarker of brain aging, indicative of dementia risk and neurodegeneration.
Functional and vascular neuroimaging in maritime pilots with long-term sleep disruption
Authors: Mentink Lara J. , van Osch Matthias J. P. , Bakker Leanne J. , Olde Rikkert Marcel G. M. , Beckmann Christian F. , Claassen Jurgen A. H. R. , Haak Koen V.
Published: November 2024

The mechanism underlying the possible causal association between long-term sleep disruption and Alzheimer’s disease remains unclear Musiek et al. 2015. A hypothesised pathway through increased brain amyloid load was not confirmed in previous work in our cohort of maritime pilots with long-term work-related sleep disruption Thomas et al. Alzheimer’s Res Ther 2020;12:101. Here, using functional MRI, T2-FLAIR, and arterial spin labeling MRI scans, we explored alternative neuroimaging biomarkers related to both sleep disruption and AD: resting-state network co-activation and between-network connectivity of the default mode network (DMN), salience network (SAL) and frontoparietal network (FPN), vascular damage and cerebral blood flow (CBF). We acquired data of 16 maritime pilots (56 ± 2.3 years old) with work-related long-term sleep disruption (23 ± 4.8 working years) and 16 healthy controls (59 ± 3.3 years old), with normal sleep patterns (Pittsburgh Sleep Quality Index ≤ 5). Maritime pilots did not show altered co-activation in either the DMN, FPN, or SAL and no differences in between-network connectivity. We did not detect increased markers of vascular damage in maritime pilots, and additionally, maritime pilots did not show altered CBF-patterns compared to healthy controls. In summary, maritime pilots with long-term sleep disruption did not show neuroimaging markers indicative of preclinical AD compared to healthy controls. These findings do not resemble those of short-term sleep deprivation studies. This could be due to resiliency to sleep disruption or selection bias, as participants have already been exposed to and were able to deal with sleep disruption for multiple years, or to compensatory mechanisms Mentink et al. PLoS ONE. 2021;15(12):e0237622. This suggests the relationship between sleep disruption and AD is not as strong as previously implied in studies on short-term sleep deprivation, which would be beneficial for all shift workers suffering from work-related sleep disruptions.
Unraveling the Nexus: The Role of Collapsin Response Mediator Protein 2 Phosphorylation in Neurodegeneration and Neuroregeneration
Authors: Wang Yuebing , Ohshima Toshio
Published: November 2024

Neurodegenerative disease characterized by the progressive damage of the nervous system, and neuropathies caused by the neuronal injury are both led to substantial impairments in neural function and quality of life among geriatric populations. Recovery from nerve damage and neurodegenerative diseases present a significant challenge, as the central nervous system (CNS) has limited capacity for self-repair. Investigating mechanism of neurodegeneration and regeneration is essential for advancing our understanding and development of effective therapies for nerve damage and degenerative conditions, which can significantly enhance patient outcomes. Collapsin response mediator protein 2 (CRMP2) was first identified as a key mediator of axonal growth and guidance is essential for neurogenesis and neuroregeneration. Phosphorylation as a primary modification approach of CRMP2 facilitates its involvement in numerous physiological processes, including axonal guidance, neuroplasticity, and cytoskeleton dynamics. Prior research on CRMP2 phosphorylation has elucidated its involvement in the mechanisms of neurodegenerative diseases and nerve damage. Pharmacological and genetic interventions that alter CRMP2 phosphorylation have shown the potential to influence neurodegenerative diseases and promote nerve regeneration. Even with decades of research delving into the intricacies of CRMP2 phosphorylation, there remains a scarcity of comprehensive literature reviews addressing this topic. This absence of synthesis and integration of findings hampers the field’s progress by preventing a holistic understanding of CRMP2’s implications in neurobiology, thereby impeding potential advancements in clinical treatments and interventions. This review intends to compile investigations focused on the role of CRMP2 phosphorylation in both neurodegenerative disease models and injury models to summarizing impacts and offer novel insight for clinical therapies.
An Improved Transformer Model for Sap Flow Prediction that Efficiently Utilizes Environmental Information
Authors: Yu Chenhao , Yao Yan , Yang Haiqing , Wang Xin
Published: November 2024

As an important reference for assessing plant water consumption and estimating plant transpiration, it is of great significance to achieve accurate prediction of plant sap flow. A number of deep learning models were established and compared using approximately 3 years of continuous eucalyptus flow time series data collected from the SAPFLUXNET open dataset and 6 environmental factors, including shortwave solar incident radiation, air temperature, air relative humidity, net radiation, vapor pressure deficit, and photosynthetic photon flux density. The experimental results show that the improved Transformer model, with the introduction of a two-step self-attention mechanism and simplified design, maintains significant predictive performance advantages compared to the original Transformer model, long short-term memory, gated recurrent unit, and temporal convolutional neural network models. In the shorter 1-h forecast, the mean squared error and coefficient of determination (R2) of the improved Transformer model are 0.0191 and 0.965, respectively. Compared to the suboptimal typical Transformer model, the MSE is reduced by 22.9%, and R2 is increased by 1.0%. Additionally, the improved model maintains stable predictive performance advantages in long-term plant flow prediction. In the longest 8-h advance prediction, the MSE is reduced by 14.9% compared to the suboptimal Transformer model, and R2 increases by 3.0% compared to the Transformer model. The comprehensive experimental results show that the improved Transformer model makes more effective use of environmental information to achieve more accurate and long-term plant flow prediction. This study emphasizes the basic principle and validity of the two-step self-attention network structure and provides a valuable basis for developing more effective methods for predicting plant sap flow.
Viability of Flax Fiber-Reinforced Salt Cores for Aluminum High-Pressure Die Casting in Experiment and Simulation
Authors: Boos Dominik , Zaremba Swen , Drechsler Klaus
Published: November 2024

Parts with undercuts or hollow sections exploit the maximum lightweight potential due to efficient material usage. However, such geometries are often challenging to produce with ordinary tooling technology, especially in aluminum high-pressure die casting (HPDC). In order to close this gap, this paper investigates flax fiber-reinforced salt made by wet compression molding as a new lost core material that can be removed with water. Three-point bending tests and HPDC experiments characterized the material. The 2D and 3D simulations with aluminum melt and compressible air were carried out in ANSYS Fluent 2023R1. The outlet vent boundary condition is characterized separately to address the geometric features of the outlet vent. Combined with a two-phase flow filling simulation, it allows assessing the actual loads on the lost core material. The simulations show an excellent agreement between the proposed one-dimensional, analytical outlet model and the computational fluid dynamics (CFD) results. The 2D filling simulations are helpful to prove mesh convergence and model simplifications but overestimate the loads. A 3D simulation predicts stress peaks up to 33 MPa for an ingate speed of 64 m/s. Conventional, brittle salt cores with a bending strength of 15 MPa fail under these conditions in the HPDC experiment. In contrast, fiber-reinforced salt cores with bending strengths between 11 and 37 MPa are viable thanks to their toughness, which was demonstrated by a eight to 31 times higher energy absorption than the unreinforced benchmark in the three-point bending tests. With the new robust lost core material, a foundry gains a technology advantage that opens up new markets, e.g., in the mobility sector.
Quantifying Virtual Field Trip Efficiency
Authors: Pugsley J. H. , Howell J. A. , Hartley A. J. , Buckley S. J. , Chmielewska M. , Naumann N. , Schofield N. J. , Brackenridge R.
Published: November 2024

The efficiency of virtual field trips (VFTs) compared to their physical counterparts, is often regarded as one of their key benefits. Virtual field trips are typically more time, cost and environmentally efficient and logistically easier to plan and execute. This is largely due to the lack of travel, however, the nature of these efficiencies, which is essential for deciding whether a trip should be virtual, physical or blended, have not previously been quantified. Here we present a quantitative evaluation of several measures of efficiency, using data from a like-for-like comparison between 10 day long virtual and physical field trips to Utah, USA, from the University of Aberdeen, UK. For this case study, our results demonstrate that virtual field trips are more efficient across all the categories of time, cost, environmental impact, and logistics. In addition to saved air travel days at the start and end of the physical trip, a further 33.3% of the time on the physical field trip was spent travelling (walking and driving). This time saving allowed an additional 16 localities to be visited on the virtual field trip. The virtual field trip localities also ran in an order that best suited the geological narrative rather than their geographic location which the physical field trip was restricted by. Flights and driven kilometres for the physical trip produced c. 4 t of carbon dioxide equivalent (CO2) per student. The virtual trip produce <1% of the CO2 and was comparable to a typical teaching week, making it significantly more environmentally efficient. The cost of the virtual trip was negligible compared to that of the physical trip (saving up to £ 3000 GBP per student). These findings were compared to the fulfilment of learning outcomes, quantified primarily through questionnaires, the student responses suggest that the PFT and VFT perceptions of learning outcomes were generally comparable. Efficiency is not the only measure of a successful field trip, with other parameters such as social cohesion and embodiment within the outdoor environment that must also be considered when planning a field trip. Therefore, the authors do not advocate or support an abandonment of physical field trips. Rather, this study aims to provide a first attempt to quantify efficiency to inform decision making when planning field training.
Characterization of autochthone biological control agents for pear protection against the brown spot of pear disease caused by Stemphylium vesicarium
Authors: Soriato Elia , Gatta Massimo , Danzi Davide , Casagrande Martina , Cerrato Alfonso , Cucchi Francesca , Vandelle Elodie
Published: November 2024

Stemphylium vesicarium is an important phytopathogen for many plant species, that switches between necrotrophic and saprophytic lifestyles. In the last decade, it has severely affected pear production worldwide, causing the so-called brown spot of pears (BSP), which led to the replacement of several pear orchards in northern Italy with consequent important economic losses. In the field, the management of the disease still relies on fungicide application, though several resistant genotypes of the pathogen emerged through the years. In the present study, three different bacterial species have been isolated from an infected orchard and evaluated as potential biological control agents (BCAs) against a local isolate of Stemphylium vesicarium. Two bacterial isolates belonging to the Bacillus genus demonstrated a significant ability to inhibit S. vesicarium growth in vitro, both through direct antagonism and the emission of volatile organic compounds (VOCs). The cell-free supernatant from one of these isolates exhibited a strong biocontrol activity, particularly through compounds extracted in acidic conditions. The protective effectiveness of the two most promising BCAs was further validated on detached pear fruits infected with S. vesicarium. Overall, the findings suggest that these two BCAs have the potential to be developed into a bio-based alternative to fungicides to control BSP, thus contributing to a more sustainable pear production.
ChatGPT versus Google Gemini: a comparison to evaluate patient education guide created on common neurological disorders
Authors: Phillips Vidith , Kiryakoza Fadi , Arefin Shamsul , Choudhary Nishtha , Garifullin Renat
Published: November 2024

Introduction

This study assesses the effectiveness of AI tools, ChatGPT and Google Gemini, in educating the public about neurological conditions such as Bell’s palsy, Tetanus, and Headaches, and assess chatbot-generated patient guides based on readability and ease of understanding.

Methodology

In March 2024, the authors conducted a cross-sectional study to develop patient education brochures for Bell’s palsy, Tetanus vaccination, and Persistent Headache, leveraging AI models ChatGPT and Google Gemini. The brochures’ quality was assessed through readability, similarity, and a modified DISCERN score for reliability. Statistical analysis, performed in R software, compared responses from both AI models using unpaired T-tests. The correlation between ease score and reliability was explored using Pearson’s Coefficient of Correlation.

Results

The study revealed no significant variances in word count, sentence count, or average words per sentence between the two AI tools. However, materials generated by ChatGPT exhibited significantly higher ease scores, highlighting its proficiency in creating more understandable content (p < 0.05).

Conclusions

This study finds ChatGPT outperforms Google Gemini in readability despite similar metrics. This suggests ChatGPT's potential superiority in creating more understandable patient education materials. As AI advances, it’s essential to research more tools and medical conditions to ensure they meet diverse patient education needs.
Aboriginal Art and the Telling of History
Authors: Rademaker Laura , May Sally K. , Maralngurra Gabriel , Goldhahn Joakim
Published: November 2024

The rock art of Australia is among the oldest, most complex, and most fascinating manifestations of human creativity and imagination in the world. Aboriginal people used art to record their experiences, ceremonies, and knowledge by embedding their understanding of the world in the landscape over many generations. Indeed, rock art serves as archives and libraries for Australia's Indigenous people. It is, in effect, its repository of memory. This volume explores Indigenous perspectives on rock art. It challenges the limits and assumptions of traditional, academic ways of understanding and knowing the past by showing how history has literally been painted 'on the rocks'. Each chapter features a biography of an artist or family of artists, together with an artwork created by contemporary artist Gabriel Maralngurra. By bringing together history, archaeology, and Indigenous artistic practice, the book offers new insights into the medium of rock art and demonstrates the limits of academic methods and approaches.
Flexible multi-fidelity framework for load estimation of wind farms through graph neural networks and transfer learning
Authors: Duthé Gregory , de N Santos Francisco , Abdallah Imad , Weijtjens Wout , Devriendt Christof , Chatzi Eleni
Published: November 2024

With global wind energy capacity ramping up, accurately predicting damage equivalent loads (DELs) and fatigue across wind turbine populations is critical, not only for ensuring the longevity of existing wind farms but also for the design of new farms. However, the estimation of such quantities of interests is hampered by the inherent complexity in modeling critical underlying processes, such as the aerodynamic wake interactions between turbines that increase mechanical stress and reduce useful lifetime. While high-fidelity computational fluid dynamics and aeroelastic models can capture these effects, their computational requirements limits real-world usage. Recently, fast machine learning-based surrogates which emulate more complex simulations have emerged as a promising solution. Yet, most surrogates are task-specific and lack flexibility for varying turbine layouts and types. This study explores the use of graph neural networks (GNNs) to create a robust, generalizable flow and DEL prediction platform. By conceptualizing wind turbine populations as graphs, GNNs effectively capture farm layout-dependent relational data, allowing extrapolation to novel configurations. We train a GNN surrogate on a large database of PyWake simulations of random wind farm layouts to learn basic wake physics, then fine-tune the model on limited data for a specific unseen layout simulated in HAWC2Farm for accurate adapted predictions. This transfer learning approach circumvents data scarcity limitations and leverages fundamental physics knowledge from the source low-resolution data. The proposed platform aims to match simulator accuracy, while enabling efficient adaptation to new higher-fidelity domains, providing a flexible blueprint for wake load forecasting across varying farm configurations.
Classical-quantum simulation of non-equilibrium Marshak waves
Authors: Myers C.J. , Gentile Nick , Rouillard Hunter , Vogt Ryan , Graziani F. , Gaitan F.
Published: November 2024

In the radiation hydrodynamic simulations used to design inertial confinement fusion (ICF) and pulsed power experiments, nonlinear radiation diffusion tends to dominate CPU time. This raises the interesting question of whether a quantum algorithm can be found for nonlinear radiation diffusion which provides a quantum speedup. Recently, such a quantum algorithm was introduced based on a quantum algorithm for solving systems of nonlinear partial differential equations (PDEs) which provides a quadratic quantum speedup. Here, we apply this quantum PDE (QPDE) algorithm to the problem of a non-equilibrium Marshak wave propagating through a cold, semi-infinite, optically thick target, where the radiation and matter fields are not assumed to be in local thermodynamic equilibrium. The dynamics is governed by a coupled pair of nonlinear PDEs which are solved using the QPDE algorithm, as well as two standard PDE solvers: (i) Python's py-pde solver; and (ii) the KULL ICF simulation code developed at Lawrence-Livermore National Laboratory. We compare the simulation results obtained using the QPDE algorithm and the standard PDE solvers and find excellent agreement.
Response of a relativistically streaming pulsar plasma
Authors: Rafat M.Z. , Melrose D.B. , Demcsak V.M.
Published: November 2024

The response tensor is derived for a relativistically streaming, strongly magnetized, one-dimensional Jüttner distribution of electrons and positrons, referred to as a pulsar plasma. This is used to produce a general treatment of wave dispersion in a pulsar plasma. Specifically, relativistic streaming, the spread in Lorentz factors in a pulsar rest frame and cyclotron resonances are taken into account. Approximations to the response tensor are derived by making approximations to relativistic plasma dispersion functions appearing in the general form of the response tensor. The cold-plasma limit, the highly relativistic limit and limits related to cyclotron resonances are considered. The theory developed in this paper has applications to generalized Faraday rotation in pulsars and magnetars.
Molecular characterization and B-cell epitope analysis of the TSP11 gene in Echinococcus infection strains from Yunnan Province
Authors: Xu Qian , Wang Zhengqing , Zi Jinrong , Cai Xuan , Wu Fangwei , Li Benfu , Peng Jia , Li Jianxiong , Yan Xinliu , Dong Ying , Yang Yaming
Published: November 2024

This study investigates the molecular intricacies of the transmembrane protein TSP11 gene in Echinococcus strains isolated from livestock and patients in Yunnan Province afflicted with Echinococcus granulosus (E. granulosus) between 2016 and 2020. Gene typing analysis of the ND1 gene revealed the presence of the G1 type, G5 type and untyped strains, constituting 52.4, 38.1 and 9.5%, respectively. The analysis of 42 DNA sequences has revealed 24 novel single nucleotide polymorphic sites, delineating 11 haplotypes, all of which were of the mutant type. Importantly, there were no variations observed in mutation sites or haplotypes in any of the hosts. The total length of the TSP11 gene's 4 exons is 762 bp, encoding 254 amino acids. Our analysis posits the existence of 6 potential B-cell antigenic epitopes within TSP11, specifically at positions 49-KSN-51, 139-GKRG-142, 162-DNG-164, 169-NGS-171, 185-DS-186 and 231-PPRFTN-236. Notably, these epitopes exhibit consistent presence among various intermediate hosts and haplotypes. However, further validation is imperative to ascertain their viability as diagnostic antigens for E. granulosus in the Yunnan Province.
Application of simulated AIS data to study the collision risk system of ships
Authors: Lee Sin-Der , Yang Ming-Feng , Chen Shih-Tzung , Hsu Huang-Kai
Published: November 2024

In previous research, several computational methods have been proposed to analyse the navigation, transportation safety and collision risks of maritime vessels. The objective of this study is to use Automatic Identification System (AIS) data to assess the collision risk between two vessels before an actual collision occurs. We introduce the concept of an angle interval in the model to enable real-time response to vessel collision risks. When predicting collision risks, we consider factors such as relative distance, relative velocity and phase between the vessels. Lastly, the collision risk is divided into different regions and represented by different colours. The green region represents a low-risk area, the yellow region serves as a cautionary zone and the red region indicates a high-alert zone. If a signal enters the red region, the vessel's control system will automatically intervene and initiate evasive manoeuvres. This reactive mechanism enhances the safety of vessel operations, ensuring the implementation of effective collision avoidance measures.
First discovery of Antarctic amber
Authors: Klages Johann P. , Gerschel Henny , Salzmann Ulrich , Nehrke Gernot , Müller Juliane , Hillenbrand Claus-Dieter , Bohaty Steven M. , Bickert Torsten
Published: November 2024

Here, we report the first discovery of Antarctic fossil resin (commonly referred to as amber) within a ~5 cm-thick lignite layer, which constitutes the top part of a ~3 m-long palynomorph-rich and root-bearing carbonaceous mudstone of mid-Cretaceous age (Klages et al.2020). The sedimentary sequence (Fig. 1) was recovered by the MARUM-MeBo70 seafloor drill rig at Site PS104_20 (73.57° S, 107.09° W; 946 m water depth) from the mid-shelf section of Pine Island trough in the Amundsen Sea Embayment, West Antarctica, during RV Polarstern Expedition PS104 in early 2017 (Gohl 2017; Fig. 1a). So far, amber deposits have been described from every continent except Antarctica (Langenheim 2003, Quinney et al. 2015; Fig. 1a).
Comparing cancer stage at diagnosis between migrants and non-migrants: a meta-analysis
Authors: Harvey-Sullivan Adam , Ali Sana , Dhesi Parveen , Hart Joseph , Painter Helena , Walter Fiona M. , Funston Garth , Zenner Dominik
Published: November 2024

Background

Migrants face barriers accessing healthcare, risking delays in cancer diagnosis. Diagnostic delays result in later stage diagnosis which is associated with poorer cancer survival. This review aims to compare the differences in cancer stage at diagnosis between migrants and non-migrants.

Methods

We conducted a systematic review and meta-analysis of three databases from 2000 to 2023 for studies conducted in OECD countries that compared stage at diagnosis between migrants and non-migrants. Meta-analysis compared odds ratios (OR) for early (stage I and II) stage at diagnosis. The Risk of Bias in Non-randomised Studies of Exposure tool was used to assess study quality.

Results

41 of the 11,549 studies identified were included; 34 studies had suitable data for meta-analysis. Overall, migrants were significantly less likely to be diagnosed with early stage cancer compared with non-migrants (OR 0.84; 95% CI 0.78–0.91). This difference was maintained across cancer types, although only statistically significant for breast (OR 0.78; 95% CI 0.70–0.87) and prostate cancer (OR 0.92; 95% CI 0.85–0.99).

Discussion

Published studies indicate that migrants are less likely to be diagnosed with early stage cancer. Variation by cancer type, study location and region of origin highlights the need for further research to understand these differences.
Seven-year performance of a clinical metagenomic next-generation sequencing test for diagnosis of central nervous system infections
Authors: Benoit Patrick , Brazer Noah , de Lorenzi-Tognon Mikael , Kelly Emily , Servellita Venice , Oseguera Miriam , Nguyen Jenny , Tang Jack , Omura Charles , Streithorst Jessica , Hillberg Melissa , Ingebrigtsen Danielle , Zorn Kelsey , Wilson Michael R. , Blicharz Tim , Wong Amy P. , O’Donovan Brian , Murray Brad , Miller Steve , Chiu Charles Y.
Published: November 2024

Metagenomic next-generation sequencing (mNGS) of cerebrospinal fluid (CSF) is an agnostic method for broad-based diagnosis of central nervous system (CNS) infections. Here we analyzed the 7-year performance of clinical CSF mNGS testing of 4,828 samples from June 2016 to April 2023 performed by the University of California, San Francisco (UCSF) clinical microbiology laboratory. Overall, mNGS testing detected 797 organisms from 697 (14.4%) of 4,828 samples, consisting of 363 (45.5%) DNA viruses, 211 (26.4%) RNA viruses, 132 (16.6%) bacteria, 68 (8.5%) fungi and 23 (2.9%) parasites. We also extracted clinical and laboratory metadata from a subset of the samples (n = 1,164) from 1,053 UCSF patients. Among the 220 infectious diagnoses in this subset, 48 (21.8%) were identified by mNGS alone. The sensitivity, specificity and accuracy of mNGS testing for CNS infections were 63.1%, 99.6% and 92.9%, respectively. mNGS testing exhibited higher sensitivity (63.1%) than indirect serologic testing (28.8%) and direct detection testing from both CSF (45.9%) and non-CSF (15.0%) samples (P < 0.001 for all three comparisons). When only considering diagnoses made by CSF direct detection testing, the sensitivity of mNGS testing increased to 86%. These results justify the routine use of diagnostic mNGS testing for hospitalized patients with suspected CNS infection.
A versatile conformal circularly polarized quad-element antenna for X-band applications
Authors: Sundaravadivel P. , Kumar D. Rajesh , Padmanaban Yuvaraj , Kumar Om Prakash
Published: November 2024

This article presents a flexible four-element antenna for X-band applications. The proposed antenna covers the spectrum ranging from 10.6 to 11.9 GHz, including a significant portion of the X-band. The single antenna element comprises a modified E-shaped radiating patch, which is fed by a unique feeding structure consisting of a 50-Ω feeding strip connected with two rectangular stubs on both sides. All antenna elements are printed on a flexible felt 60 mm × 60 mm × 1 mm (2.12 λ × 2.12 λ × 0.035 λ at 10.6 GHz) substrate. The proposed antenna exhibits circular polarization over the desired bans of operation with an axial ratio (< 3 dB) bandwidth of 1.2 GHz, which is significant for X-band applications. The designed antenna is manufactured and practically tested. Both simulated and measured results agree well with each other, ensuring the optimal performance of the antenna. Moreover, the antenna achieves a maximum gain of up to 8 dBi in the desired band of operation. Further MIMO parameters, including envelope correlation coefficient (ECC), diversity gain (DG), channel capacity loss (CCL), and mean effective gain (MEG), are calculated to validate the MIMO performance. Finally, a conformal analysis was carried out to study the robustness of the antenna in various bending scenarios. Results show that the antenna reported in this article is the correct choice for conformal X-band MIMO applications.
Fluid upwelling across the Hikurangi subduction thrust during deep slow-slip earthquakes
Authors: Herath Pasan , Audet Pascal
Published: November 2024

Slow-slip events at global subduction zones relieve tectonic stress over days to years. Through slow-slip cycles, high fluid pressures observed at the top of subducting plates are thought to fluctuate, potentially due to the valving action of an impermeable layer near the plate interface. We model teleseismic scattering data at the Manawatu deep slow-slip patch at the Hikurangi margin in New Zealand and find high seismic P-to-S wave velocity ratios, VP/VS, in the upper ~5 km of the subducting Pacific Plate, reflecting sustained elevated fluid pressures that decrease during slow-slip and increase during inter-slow-slip periods. Within a ~ 3 km thick lower crustal layer of the overriding Australian Plate, decreasing VP/VS during inter-slow-slip periods reflects permeability reduction due to mineral precipitation. Increasing VP/VS during slow-slip reflects increasing permeability and crack density, facilitating upward fluid transfer through this layer. Our results suggest it acts as a valve to relieve high fluid pressures in the subducting slab.
Clay alignment takes place during early stages of sedimentation
Authors: Kuehn Rebecca , Kilian Rüdiger , Lang Dustin , Morales Luiz Grafulha , Grendal Ola G. , Stipp Michael
Published: November 2024

The alignment of clay minerals in sediments is of high importance for their mechanical and physical properties. The development of this alignment starts with the deposition of clay, its strength is measured by the crystallographic preferred orientation. So far, the early stages of sedimentation have been restricted to post-mortem observations. Here we present particle settling experiments in four dimensions (time and orientation, as a function of overburden and composition) observed in situ using synchrotron diffraction, in which kaolinite and kaolinite-illite mixtures were sedimented in water columns. The alignment strength in freshly settled sediments increases with overburden, but is higher in deionized water than in seawater. Alignment strength increases within the first few millimetres of overburden and stagnates afterwards. With illite added, the resulting alignment strength is substantially decreased. Our results demonstrate that electrostatic interactions between particles are overcome by gravitational forces already within the upper millimetres of sediment.
Calcium signaling from damaged lysosomes induces cytoprotective stress granules
Authors: Duran Jacob , Salinas Jay E , Wheaton Rui ping , Poolsup Suttinee , Allers Lee , Rosas-Lemus Monica , Chen Li , Cheng Qiuying , Pu Jing , Salemi Michelle , Phinney Brett , Ivanov Pavel , Lystad Alf Håkon , Bhaskar Kiran , Rajaiya Jaya , Perkins Douglas J , Jia Jingyue
Published: November 2024

Lysosomal damage induces stress granule (SG) formation. However, the importance of SGs in determining cell fate and the precise mechanisms that mediate SG formation in response to lysosomal damage remain unclear. Here, we describe a novel calcium-dependent pathway controlling SG formation, which promotes cell survival during lysosomal damage. Mechanistically, the calcium-activated protein ALIX transduces lysosomal damage signals to SG formation by controlling eIF2α phosphorylation after sensing calcium leakage. ALIX enhances eIF2α phosphorylation by promoting the association between PKR and its activator PACT, with galectin-3 inhibiting this interaction; these regulatory events occur on damaged lysosomes. We further find that SG formation plays a crucial role in promoting cell survival upon lysosomal damage caused by factors such as SARS-CoV-2ORF3a, adenovirus, malarial pigment, proteopathic tau, or environmental hazards. Collectively, these data provide insights into the mechanism of SG formation upon lysosomal damage and implicate it in diseases associated with damaged lysosomes and SGs.
Green chemistry startups: some lessons learned
Authors: Hallett Jason P.
Published: November 2024

There has been an explosive growth in environmentally driven startups in recent years.
Iron-catalysed intramolecular C(sp3)–H amination of alkyl azides
Authors: Wu Kai , Che Chi-Ming
Published: November 2024

This review summarizes recent major advances in iron-catalysed C–H aminations of alkyl azides through iron–alkylnitrene/alkylimido intermediates to access various N-heterocycles.
Copper nanoclusters: emerging photoredox catalysts for organic bond formations
Authors: Sagadevan Arunachalam , Murugesan Kathiravan , Bakr Osman M. , Rueping Magnus
Published: November 2024

In this feature article, we provide an overview of the photocatalytic capabilities of copper-based nanoclusters for organic bond-forming reactions.
Machine learning directed discovery and optimisation of a platinum-catalysed amide reduction
Authors: Casillo Eleonora , Maliszewski Benon P. , Urbina-Blanco César A. , Scattolin Thomas , Cazin Catherine S. J. , Nolan Steven P.
Published: November 2024

The discovery and optimisation of reaction conditions leading to the reduction of amides, a fundamental large-scale industrial reaction, is achieved using a machine learning (ML) platform and a platinum catalyst.
Single-ion magnetism in novel Btp-based cobalt complexes of different charge
Authors: Rama-Martínez Gustavo , Osorio-Celis Marcelo , Sabater-Algarra Yolanda , Sánchez-Brunete Diego , Llamas-Saiz Antonio L. , Quirós-Díez Eugenia P. , Vázquez M. Eugenio , Vázquez López Miguel , Giménez López María del Carmen
Published: November 2024

By deprotonating Btp-derived ligands, precise control over counterions in the outer-coordination sphere is achieved in both neutral and charged anisotropic CoII complexes exhibiting field-induced single-ion magnetism.
Combining sequential extractions with bulk and micro X-ray spectroscopy to elucidate iron and phosphorus speciation in sediments of an iron-treated peat lake
Authors: Münch Melanie A. , Voegelin Andreas , Colocho Hurtarte Luis Carlos , Göttlicher Jörg , Behrends Thilo
Published: November 2024

Nanoscale mixed inorganic–organic Fe–Ca–P-OM co-precipitates formed in sediments of eutrophic peat lake after Fe treatment increase seasonal internal P loading.
High-efficiency green catalytic conversion for waste CS2 by non-noble metal cage-based MOFs: an access pathway to high-value thiazolidine-2-thione
Authors: Ding Wenyu , Tang Xinyu , Jin Sheng , Li Zhao , Xu Dongwei , Kang Xiaomin , Liu Zhiliang
Published: November 2024

High-efficiency non-noble cage-based MOFs catalyst for CS2 waste green disposal through catalytic conversion into high-value thiazolidine-2-thione.
Mechanoenzymatic hydrolysis of cotton to cellulose nanocrystals
Authors: Kaabel Sandra , Schlapp-Hackl Inge , Kontturi Eero , Kostiainen Mauri A.
Published: November 2024

Mechanoenzymatic hydrolysis generates cellulose nanocrystals from cotton within 15 minutes of ball milling, providing a rapid and low-waste method to generate CNCs with a high space–time-yield.
Generation of antibody–drug conjugates by proximity-driven acyl transfer and sortase-mediated ligation
Authors: Cui Zhi-Hui , Zhang Hua , Zheng Feng-Hao , Xue Jun-Hao , Yin Qing-Hong , Xie Xiao-Lei , Wang Yu-Xuan , Wang Tao , Zhou Li , Fang Ge-Min
Published: November 2024

We report a sortase-based site-specific antibody–drug conjugation strategy involving an affinity peptide-directed acyl transfer reaction and the sortase-mediated peptide ligation that allows for the attachment of protein-based payloads to antibodies.
Dual-function applications of photochromic BiNbO4:Er3+ ceramics based on reversible upconversion luminescence modulation
Authors: Ullah Asad , Khan Imran , Cun Yangke , Liu Yue , Song Zhiguo , Qiu Jianbei , Tatiana Cherkasova , Huang Anjun , Haider Asif Ali , Yang Zhengwen
Published: November 2024

This research introduces a photochromic luminescent BiNbO4:Er ceramic, showing good coloration contrast and efficient upconversion luminescence modulation rate. The dual-functional applications in security and fingerprint acquisition are developed.
Influence of hydrogen bonds and π–π stacking on the self-assembly of aryldipyrrolidones
Authors: Ximenis Pedro , Rubert Llorenç , Ehmann Heike M. A. , Soberats Bartolome
Published: November 2024

We report on the self-assembly behavior of two aryldipyrrolidone dyes forming conventional assemblies via π–π stacking or unconventional multistranded columnar phases through hydrogen bonding depending on their π-core.
Three‐phase four‐wire power flow solution for multi‐grounded distribution networks with non‐bolted grounding
Authors: Yang Nien‐Che , Zeng Song‐Ting
Published: November 2024

This study proposes a direct three‐phase four‐wire power flow method to accurately analyse the neutral line and multiple grounding characteristics. In particular, the proposed grounding impedance building‐based solution method was used to analyse the neutral grounding impedance in power flow studies based on the slack bus grounding impedance. The accuracy of the proposed method was verified using a neutral‐to‐earth voltage test system. IEEE 13‐bus and 123‐bus test systems were used to compare the advantages and disadvantages of the proposed method. Compared to the current injection full Newton and forward–backward sweep methods, the proposed method achieves a significant reduction in iteration numbers of up to 76.92% and 77.78%, respectively. For different grounding scenarios, stable convergence characteristics were exhibited by the proposed method after six to seven iterations.
Prediction of fire danger index using a new machine learning based method to enhance power system resiliency against wildfires
Authors: Pham Tan Nhat , Shah Rakibuzzaman , Amjady Nima , Islam Syed
Published: November 2024

Wildfires, which can cause significant damage to power systems, are mostly inevitable and unpredictable. Fire danger indexes, such as the Forest Fire Danger Index (FFDI) and the Canadian Fire Weather Index (FWI), measure the potential wildfire danger at a given time and location. Thus, by predicting these fire danger indexes in advance, power system operators can obtain valuable insight into the potential wildfire risks and can better be prepared to tackle the wildfires. However, due to dependency on weather conditions, these indexes usually have volatile time series, which make their prediction complex. Taking these facts into account, this paper, unlike previous approaches that predict fire danger indexes based on climatological models, develops a machine learning‐based forecast process to predict these indexes using the relevant weather data and past performance. To do this, first, a volatility analysis approach is presented to analyse the volatility level of the time series data of a fire danger index. Afterwards, an effective machine learning‐based forecast methodology using a new deep feature selection model is proposed to predict fire danger indexes. The developed forecast methodology is tested on the real‐world data of FFDI and FWI and is compared with several popular alternative methods reported in the literature.
An innovative traffic flow detection model based on temporal video frame analysis and grayscale aggregation quantification
Authors: Liu Xin , Meng Qiao , Li Xin , Wang Zhijie , Kong Siyuan , Li Bingyu
Published: November 2024

Current traffic status detection methods heavily rely on historical traffic flow data and vehicle counts. However, these methods often fail to meet the stringent real‐time requirements of state detection, especially on edge devices with limited computing resources.To address these challenges, this study develops a traffic alert model using temporal video frame analysis and grayscale aggregation quantization techniques. Initially, the model uses distance mapping between pixel features and frames of road traffic videos to construct a comprehensive road environment and vehicle segmentation model. The model also establishes a mapping between pixel equidistant lines and actual distances, enabling precise congestion detection. This approach significantly reduces costs associated with traditional traffic detection methods as it does not rely on historical data. Performance evaluation using fixed‐point road monitoring data indicates that the proposed model outperforms traditional traffic state detection models, with a performance improvement of approximately 4.7% to 9.5%. Additionally, the model improves computing resource efficiency by approximately 72.5% and demonstrates substantial real‐time detection capabilities.
A synchronization method based on current orthogonal decomposition considering harmonic components for wireless power transfer system
Authors: Wu Min , Li Songyan , Zhou Xiang , Yu Xipei
Published: November 2024

In order to improve the wireless power transfer (WPT) system, an active rectifier is commonly used. Synchronization technology is critical for active rectifier. The traditional synchronization method based on zero‐crossing detection (ZCD) is unstable and not suitable for the case with lots of harmonic component in the resonant current. Here, a new synchronization method with harmonic compensation is proposed for the WPT system without the ZCD of the resonant current. A mathematical model is built to analyse and compensate the impact caused by the harmonic on phase angle. Therefore, the proposed method can be applied to the high‐order resonant network like LCC compensated topology where the harmonic component is rich in the resonant current. For verifying the proposed synchronization method, a laboratory prototype is built. The experimental results prove that the system can operate stably with parameter perturbation and different load. The peak transfer efficiency of the system can achieve the 94.5%.
The rotation rate of single- and double-lined southern O stars
Authors: Blex Susanne , Haas Martin , Chini Rolf
Published: November 2024

We determined the projected rotational velocity (v sin i) of 238 southern O stars selected from the Galactic O-star Survey. The sample contains 130 spectroscopic single stars (C), 36 single-lined binaries (SB1), and 72 SB2 systems (including eight triples). We applied the Fourier method to high-resolution spectra taken at Cerro Murphy, Chile, and supplemented by archival spectra. The overall v sin i statistics peaks at slow rotators (40–100 km/s) with a tail towards medium (100–200 km/s) and fast rotators (200–400 km/s). Binaries, on average, show increased rotation, which differs for close (Porb < 10 d) and wide binaries (10 d <  Porb < 3700 d), and for primaries and secondaries. The spin-up of close binaries is well explained by the superposition of spin-orbit synchronisation and mass transfer via Roche-lobe overflow. The increased rotation of wide binaries, however, needs another explanation. Therefore, we discuss various spin-up mechanisms. Timescale arguments lead us to favour a scenario where wide O binaries are spun-up by a combination of cloud or disk fragmentation, which lays the basis of triple and multiple stars, and the subsequent merging or swallowing of low-mass by higher-mass stars or proto-stars.
Bidirectional propagating brightenings in arch filament systems observed by Solar Orbiter/EUI
Authors: Chen Yajie , Mandal Sudip , Peter Hardi , Chitta Lakshmi Pradeep
Published: November 2024

Arch filament systems (AFSs) are chromospheric and coronal manifestations of emerging magnetic flux. Using high spatial resolution observations taken at a high cadence by the Extreme Ultraviolet Imager (EUI) on board Solar Orbiter, we identified small-scale elongated brightenings within the AFSs. These brightenings appear as bidirectional flows along the threads of AFSs. For our study, we investigated the coordinated observations of the AFSs acquired by the EUI instrument and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) on 2022 March 4 and 17. We analyzed 15 bidirectional propagating brightenings from EUI 174 Å images. These brightenings reached propagating speeds of 100–150 km s−1. The event observed on March 17 exhibits blob-like structures, which may be signatures of plasmoids and due to magnetic reconnection. In this case, we also observed counterparts in the running difference slit-jaw images in the 1400 Å passbands taken by the Interface Region Imaging Spectrograph (IRIS). Most events show co-temporal intensity variations in all AIA EUV passbands. Together, this implies that these brightenings in the AFSs are dominated by emission from cool plasma with temperatures well below 1 MK. The Polarimetric and Helioseismic Imager (PHI) on board Solar Orbiter provides photospheric magnetograms at a similar spatial resolution as EUI and from the same viewing angle. The magnetograms taken by PHI show signatures of flux emergence beneath the brightenings. This suggests that the events in the AFSs are triggered by magnetic reconnection that may occur between the newly emerging magnetic flux and the preexisting magnetic field structures in the middle of the AFSs. This would also give a natural explanation for the bidirectional propagation of the brightenings near the apex of the AFSs. The interaction of the preexisting field and the emerging flux may be important for mass and energy transfer within the AFSs.