bluuebunny/crossref_metadata_2025 huggingface dataset:
Tandem microplastic degradation and hydrogen production by hierarchical carbon nitride-supported single-atom iron catalysts
Authors: Lin Jingkai , Hu Kunsheng , Wang Yantao , Tian Wenjie , Hall Tony , Duan Xiaoguang , Sun Hongqi , Zhang Huayang , Cortés Emiliano , Wang Shaobin
Published: October 2024

Microplastic pollution, an emerging environmental issue, poses significant threats to aquatic ecosystems and human health. In tackling microplastic pollution and advancing green hydrogen production, this study reveals a tandem catalytic microplastic degradation-hydrogen evolution reaction (MPD-HER) process using hierarchical porous carbon nitride-supported single-atom iron catalysts (FeSA-hCN). Through hydrothermal-assisted Fenton-like reactions, we accomplish near-total ultrahigh-molecular-weight-polyethylene degradation into C3-C20 organics with 64% selectivity of carboxylic acid under neutral pH, a leap beyond current capabilities in efficiency, selectivity, eco-friendliness, and stability over six cycles. The system demonstrates versatility by degrading various daily-use plastics across different aquatic settings. The mixture of FeSA-hCN and plastic degradation products further achieves a hydrogen evolution of 42 μmol h‒1 under illumination, outperforming most existing plastic photoreforming methods. This tandem MPD-HER process not only provides a scalable and economically feasible strategy to combat plastic pollution but also contributes to the hydrogen economy, with far-reaching implications for global sustainability initiatives.
Transplacental SARS-CoV-2 protein ORF8 binds to complement C1q to trigger fetal inflammation
Authors: Azamor Tamiris , Familiar-Macedo Débora , Salem Gielenny M , Onwubueke Chineme , Melano Ivonne , Bian Lu , Vasconcelos Zilton , Nielsen-Saines Karin , Wu Xianfang , Jung Jae U , Lin Feng , Goje Oluwatosin , Chien Edward , Gordon Steve , Foster Charles B , Aly Hany , Farrell Ruth M , Chen Weiqiang , Foo Suan-Sin
Published: October 2024

Prenatal SARS-CoV-2 infection is associated with higher rates of pregnancy and birth complications, despite that vertical transmission rates are thought to be low. Here, multi-omics analyses of human placental tissues, cord tissues/plasma, and amniotic fluid from 23 COVID-19 mother-infant pairs revealed robust inflammatory responses in both maternal and fetal compartments. Pronounced expression of complement proteins (C1q, C3, C3b, C4, C5) and inflammatory cytokines (TNF, IL-1α, and IL-17A/E) was detected in the fetal compartment of COVID-19-affected pregnancies. While ~26% of fetal tissues were positive for SARS-CoV-2 RNA, more than 60% of fetal tissues contained SARS-CoV-2 ORF8 proteins, suggesting transplacental transfer of this viral accessory protein. ORF8-positive fetal compartments exhibited increased inflammation and complement activation compared to ORF8-negative COVID-19 pregnancies. In human placental trophoblasts in vitro, exogenous ORF8 exposure resulted in complement activation and inflammatory responses. Co-immunoprecipitation analysis demonstrated that ORF8 binds to C1q specifically by interacting with a 15-peptide region on ORF8 (C37-A51) and the globular domain of C1q subunit A. In conclusion, an ORF8-C1q-dependent complement activation pathway was identified in COVID-19-affected pregnancies, likely contributing to fetal inflammation independently of fetal virus exposure.
A bimetallic PtAu-modified carbon fiber electrochemical sensor for simultaneous and highly sensitive detection of catechol and hydroquinone in environmental water
Authors: Xiao Qi , Li Jiawen , Yang Mingli , Li Huihao , Fang Yi , Huang Shan
Published: October 2024

In this study, we report the development of a novel electrochemical sensor capable of the simultaneous detection of catechol (CC) and hydroquinone (HQ) through differential pulse voltammetry.
Unravelling the potential of yolkin for nutraceutical use: the origin, structure, and functional insights of a hen egg yolk polypeptide complex
Authors: Zambrowicz Aleksandra , Kapczyńska Katarzyna , Kania Paweł , Nowak Jakub Stanisław , Kaszowska Marta , Szymczak-Kulus Katarzyna , Kazana-Płuszka Wioletta , Piksa Marta , Górska Sabina , Jakubczyk Dominika , Macała Józefa , Zabłocka Agnieszka
Published: October 2024

The nutraceutical potential of yolkin health benefits from hen egg yolk.
Nanoplasmonic sensing to study CO and oxygen adsorption and CO oxidation on size-selected Pt10 clusters
Authors: Demirdjian Benjamin , Vaidulych Mykhailo , Ozerov Igor , Bedu Frédéric , Vajda Štefan , Henry Claude R.
Published: October 2024

The adsorption of CO and oxygen and CO oxidation on size-selected Pt10 clusters were studied by indirect nanoplasmonic sensing (INPS) in the pressure range of 1–100 Pa at T = 418 K.
Synergistic effect of ROS-generating polydopamine on drug-induced bone tissue regeneration
Authors: Han Hyeju , Kang Bongkyun , Sharker Shazid Md. , Kashem Tabassum Binte , Kim Yuejin , Lee Jeehee , Park Minok , Kim Eunjeong , Jung YunJae , Lim Jinkyu , Ryu Seungwon , Lee Kyueui
Published: October 2024

The combination of PDA NPs and 1,4-DPCA leads to a synergistic effect that enhances bone tissue regeneration in vivo.
Fragmentation patterns of DNA-stabilized silver nanoclusters under mass spectrometry
Authors: Guha Rweetuparna , Malola Sami , Rafik Malak , Khatun Maya , Gonzàlez-Rosell Anna , Häkkinen Hannu , Copp Stacy M.
Published: October 2024

Electrospray ionization mass spectrometry and molecular dynamics simulations probe how DNA-stabilized silver nanoclusters fragment.
C3-Chlorination of C2-substituted benzo[b]thiophene derivatives in the presence of sodium hypochlorite
Authors: Conrad Oppenheimer Vincent , Le Peter , Tran Cathy , Wang Haobin , Resendiz Marino J. E.
Published: October 2024

Benzo[b]thiophene was efficiently chlorinated at the C3-position using sodium hypochlorite pentahydrate. A mechanism was proposed and probed using a combination of DFT calculations and experiments.
BF3·OEt2-catalyzed/mediated alkyne cyclization: a comprehensive review of heterocycle synthesis with mechanistic insights
Authors: Ghosh Priya , Saikia Anil K.
Published: October 2024

The advancements in heterocycle synthesis through BF3·OEt2 catalyzed/mediated cyclization of alkynes have been highlighted.
Quadrupolar dinuclear hypervalent tin(iv) compounds with near-infrared emission consisting of Schiff bases based on π-conjugated scaffolds
Authors: Tanimura Kazuya , Tanaka Kento , Gon Masayuki , Tanaka Kazuo
Published: October 2024

The study focuses on dinuclear hypervalent tin(iv) compounds with near-infrared (NIR) emission and unique quadrupolar orientations, showing potential for constructing electronic structures with narrow energy gaps.
Quasi-two-dimensional dispersions of Brownian particles with competitive interactions: phase behavior and structural properties
Authors: Tan Zihan , Calandrini Vania , Dhont Jan K. G. , Nägele Gerhard
Published: October 2024

Langevin dynamics simulations reveal that quasi-2D Brownian particles with competitive short-range attractive and long-range repulsive interactions exhibit hexagonal ordering and double-stranded cluster morphologies as temperature and density vary.
A data‐driven transient stability‐based approach for out‐of‐step prediction in power systems
Authors: Shazdeh Sirwan , Golpîra Hêmin , Bevrani Hassan
Published: October 2024

This paper presents a prediction‐based algorithm designed to address out‐of‐step (OOS) conditions in power systems. The algorithm utilizes generator data obtained from phasor measurement units. The transient stability of a multi‐machine power system is evaluated using the equal‐area criterion (EAC). The proposed algorithm calculates the characteristics of the P‐δ curves within the EAC framework after a large disturbance. The critical P‐δ trace is determined by analysing the cumulative energy in the acceleration area following fault clearance. The stability margin of the rotor angle is then computed based on the actual active power and its relationship with the critical curve. The algorithm predicts the occurrence of OOS by comparing the measured active power with the corresponding value on the critical curve. Furthermore, a complementary strategy is proposed to predict the OOS condition in integrated inverter‐based power systems. The effectiveness of the proposed algorithm is validated through simulations conducted on the 73‐bus IEEE test power system.
MultiScale spectral–spatial convolutional transformer for hyperspectral image classification
Authors: Gong Zhiqiang , Zhou Xian , Yao Wen
Published: October 2024

Due to the powerful ability in capturing the global information, transformer has become an alternative architecture of CNNs for hyperspectral image classification. However, general transformer mainly considers the global spectral information while ignores the multiscale spatial information of the hyperspectral image. In this paper, we propose a multiscale spectral–spatial convolutional transformer (MultiFormer) for hyperspectral image classification. First, the developed method utilizes multiscale spatial patches as tokens to formulate the spatial transformer and generates multiscale spatial representation of each band in each pixel. Second, the spatial representation of all the bands in a given pixel are utilized as tokens to formulate the spectral transformer and generate the multiscale spectral–spatial representation of each pixel. Besides, a modified spectral–spatial CAF module is constructed in the MultiFormer to fuse cross‐layer spectral and spatial information. Therefore, the proposed MultiFormer can capture the multiscale spectral–spatial information and provide better performance than most of other architectures for hyperspectral image classification. Experiments are conducted over commonly used real‐world datasets and the comparison results show the superiority of the proposed method.
Primary Prevention of Cancer-Associated Thrombosis: Current Perspectives
Authors: Hart Christina , van Es Nick , Voigtlaender Minna
Published: October 2024

Over the past two decades, the incidence of cancer-associated thrombosis (CAT) has increased. It is nowadays a common and often serious complication among patients with cancer. Although medical thromboprophylaxis is recommended for most surgical and nonsurgical cancer patients, it has been infrequently used in ambulatory patients with cancer because of the burden of treatment and concerns about bleeding. However, various risk assessment scores are now available and randomized placebo-controlled trials have established the efficacy of low-molecular-weight heparin or the direct oral Xa inhibitors rivaroxaban and apixaban in ambulatory patients with cancer at high risk of venous thromboembolism (VTE). This review provides an overview of (1) primary thromboprophylaxis in the setting of hospitalized surgical and medical patients, (2) extended thromboprophylaxis after hospital discharge, (3) performance of risk assessment tools for CAT, and (4) primary thromboprophylaxis in ambulatory patients with cancer. The aim is to provide support to physicians in identifying ambulatory patients with cancer at high VTE risk who benefit most from medical thromboprophylaxis according to current recommendations from international guidelines.
Das weibliche Gehirn und Sex
Authors: Durner Verena , Rüger Alexander , Graf Heiko , Zeiss René
Published: October 2024

Gegenstand und Ziel Diese Übersichtsarbeit fasst wesentliche Befunde bildgebender Untersuchungen mit sexueller bzw. erotischer Stimulation und hormonelle Einflüsse bei Frauen zusammen.

Ergebnisse Im Vergleich zu Männern befassen sich bedeutend weniger bildgebende Studien mit Frauen und deren neurofunktioneller Verarbeitung sexueller Reize. Es zeigen sich heterogene Befunde in neurofunktionellen Korrelaten sexueller Stimulation bei Frauen, die durch unterschiedliche Paradigmen und Studiendesigns bedingt sein könnten. Bei Frauen führen eine Vielzahl erotischer Reize zu neurofunktionellen Aktivierungen in Regionen, die mit sexueller Reaktion in Verbindung gebracht werden. Nennenswert moduliert werden diese durch hormonelle Einflüsse im Rahmen des Menstruationszyklus, hormonelle Kontrazeption und Menopause, wenngleich spezifische Zuweisungen einzelner Hormone auf spezifische neurofunktionelle Aktivierungen noch offenbleiben. Es zeigten sich geschlechtsspezifische Unterschiede in der Hirnaktivität, insbesondere auf visuelle sexuelle Reize. Ein noch wenig untersuchter Prozess ist der weibliche Orgasmus in der Bildgebung.

Schlussfolgerungen und klinische Relevanz Ein vertieftes Verständnis der Sexualität mit einer breiteren Untersuchung von weiblichen Probanden ist für die Entwicklung eines umfassenden neurowissenschaftlichen Modells zur sexuellen Funktion von entscheidender Bedeutung. Dadurch wird ein Verständnis der sexuellen Funktion unabhängig vom Geschlecht oder der sexuellen Orientierung ermöglicht.
Contrast-enhanced endoscopic ultrasound for differential diagnosis of autoimmune pancreatitis: a meta-analysis
Authors: Zhu Shanshan , Cao Xinguang , Nabi Ghulam , Zhang Fangbin , Liu Ping , Zhang Jingwen , Guo Changqing
Published: October 2024

Background and study aims To assess the diagnostic value of contrast-enhanced endoscopic ultrasound (CE-EUS) for autoimmune pancreatitis and other solid pancreatic masses.

Patients and methods A systematic search of PubMed, Embase, and Web of Science was performed from inception to October 2022. We calculated individual and pooled sensitivities and specificities to determine the diagnostic ability of CE-EUS. In addition, we calculated I2 to test for heterogeneity and explored the source of heterogeneity by meta-regression analysis.

Results A total of 472 patients from seven eligible studies were included. The mean sensitivity and specificity of the Bivariate analysis were 0.84 (95% CI 0.71–0.92) and 0.95 (95% CI 0.84–0.99), respectively. The diagnostic advantage ratio was 107.91 (95% confidence interval [CI] 22.22–524.13), and the area under the summary receiver operating characteristics curve was 0.91 (95% CI 0.88–0.93). The overall heterogeneity of the studies is negligible (I2=0, 95% CI 0–100). However, notable heterogeneity was observed in the combined specificity (P <0.01, I2=74.82) and diagnostic odds ratio (P=0.05, I2=51.54). The heterogeneity in these aspects could be elucidated through sensitivity analysis.

Conclusions Our analysis showed that CE-EUS is useful in identifying autoimmune pancreatitis. However, further large sample size, multicenter, prospective studies are needed to demonstrate its utility.
Employing generative AI to optimize fusion experiments
Authors: Thompson Avery
Published: October 2024

Artificial intelligence can effectively explore large parameter spaces and suggest unconventional approaches for improving efficiency.
Analysis of alternative national development pathways for the cattle system in Ethiopia: linked economic and animal systems (LEAS) model
Authors: Aragie Emerta , Thurlow James
Published: October 2024

Context The livestock sector is undergoing rapid changes, and governments are designing sector development plans to account for this transition. However, the fundamental assumptions behind the medium- to long-term growth strategies of the sector should be looked at from the perspective of the dynamics in the domestic and global economy, and uncertainties around the driving forces of the transition. Aims This study used the case of Ethiopia to provide a scenario-based analysis of alternative national development trajectories, focusing on the prospects of growth performance, urbanisation, and their potential implications on the cattle system within the country. Methods We employed a newly developed linked economic and animal systems (LEAS) model where the livestock, economy-wide, and microsimulation subsystems are linked either way through flows of information. Key results Our findings suggested that demand for animal-source food (ASF) is highly dependent on economic-demographic changes and that income growth is the primary driver of overall livestock-system expansion. Additionally, urbanisation shifts the outputs of the livestock systems towards processed ASF products. Conclusion The analysis showed that livestock development plans should reflect the economic reality and potential risks facing the economic system. Herd offtake and livestock sector output vary considerably with assumptions about future growth and urbanisation trajectories. Implications In addition to relevant findings about the implications of the interplays between the economic and demographic variables, the study generated insights into the role of integrating economy-wide and livestock-system models to provide a risk-based approach to the prospects of the livestock sector.
Future frequencies of coastal floods in Australia: a seamless approach and dataset for visualising local impacts and informing adaptation
Authors: Hague Ben S. , Jakob Dörte , Kirezci Ebru , Jones David A. , Cherny Ilana L. , Stephens Scott A.
Published: October 2024

The rise of pathways-based approaches to coastal adaptation in Australia has changed user requirements for coastal flood hazard information to support decision-making. This study identifies and addresses three aspects not considered in the existing Australia-specific scientific guidance for planning adaptation to sea-level rise. First, changes in the frequency of present-day extreme sea levels are compared between locations. Second, extreme sea levels are related to impact-based thresholds associated with past flood events. Third, the potential for chronic flooding emerging is assessed. This complements global studies that provide some Australian results on these topics. We survey these to identify the methods most suitable for our application and apply the chosen methods to the reference dataset for monitoring Australian coastal sea-level change. This yields a water-level frequency dataset covering daily to centennial water levels for 37 Australian tide gauges. We analyse the dataset to provide a national picture of how sea-level rise is expected to influence the future frequencies of coastal floods in Australia. For example, 85% of Australian locations expect present-day centennial extremes to occur 30 days per year with less than 1-m sea-level rise. The locations with the largest increases in the future frequency of these extremes have the smallest present-day sea-level extreme magnitudes relative to mean sea level, and lower flood thresholds relative to these extremes. We demonstrate three further potential applications of our dataset and methods using local case studies: impact-based forecasting, climate risk services and identifying the required sea-level rise for adaptation triggers and thresholds to be reached.
Boundary layer height above the Great Barrier Reef studied using drone and Mini-Micropulse LiDAR measurements
Authors: Ryan Robert G. , Eckert Christian , Kelaher Brendan P. , Harrison Daniel P. , Schofield Robyn
Published: October 2024

The planetary boundary layer height (PBLH) is an important meteorological feature defining the boundary between surface processes and the free troposphere. The PBLH plays a key role in cloud formation and the vertical extent of aerosols and air pollutants. Measurements of PBLH were made by meteorological sensors mounted to a multi-copter drone over the southern Great Barrier Reef, Australia. We then compared these drone-based measurements to remote-sensed PBLH observations, using a Mini-Micropulse (MP) LiDAR system. Across the measurement campaign (1 March–2 April 2023), the mean PBLH value using the drones was 801 ± 203 m. Using the gradient method for MP LiDAR normalised relative backscatter profiles, the mean PBLH was 811 ± 260 m. Using an ideal MP LiDAR profile fitting method the mean was 912 ± 202 m and using a wavelet covariance transform method the mean was 862 ± 298 m. The boundary layer was consistently well mixed, without convective instability or a strong diurnal PBLH cycle. The three MP LiDAR methods compared well to the drone measurements overall with Pearson’s R correlation coefficients >0.60; however, estimates from the MP LiDAR were typically ~10% higher than from the drone. These results indicate congruence between the backscatter- and thermodynamically derived PBLH at One Tree Island, which is robust to variations in sampling conditions and the choice of MP LiDAR PBLH retrieval method.
Vale Pete Spencer
Authors: Hampton Jordan O.
Published: October 2024

An obituary for Peter Spencer, who passed away in 2024.
Parents’ attitudes and response to their child’s pornography consumption in Australia: cross-sectional survey
Authors: Lim Megan S. C. , Johnson Eleanor R. , Raggatt Michelle H.
Published: October 2024

Background Parents play an important role in monitoring children’s internet use, shaping their child’s understanding of sex, and are key stakeholders in the development of sexual health education policies. Therefore, we investigated parents’ awareness of and responses to children’s pornography exposure. Methods We invited parents with children aged from 8 to 20 years (n = 1029) to complete an observational cross-sectional online survey about pornography and young people. Results A total of 48% of parents thought that young people view pornography rarely or never, and 21% agreed that watching pornography could be part of a healthy relationship for young people. Some parents (27%) were aware that their child had ever viewed pornography. Most parents (56%) acted on this by talking to their child, while others (10%) took no action, or restricted access to devices (6%). Discussing pornography was found to be strongly associated (P < 0.001) with being aware of previous exposure to pornography for the child, and older child age (13 years or older). Parents were more likely to support education as the best practice to address pornography (65% agreed) than restricting access (39% agreed). Conclusions These findings provide new insights for policy responses and can guide the development of tools to support parents to respond to their children’s pornography exposure.
Measuring psychological immersion through cardiovascular response
measures in subtitled films
Authors: González César , Jankowska Anna
Published: October 2024

This paper presents a conceptual replication of Kruger et al.’s (2017a) study,
investigating the utility of heart rate (HR) and heart rate variability (HRV)
indicators as objective measurements of psychological immersion in subtitled
audiovisual products. The study employed a quasi-experimental design in ten
participants viewing video clips with and without subtitles, while their
physiological responses were monitored. Results suggest lower arousal levels in
both conditions compared to baseline, with statistically significant differences
observed in mean HR, mean RR, and RMSSD for the subtitles condition. While most
inferential tests did not yield significant outcomes, descriptive trends
indicate decreased arousal relative to the baseline. They also show increased
arousal throughout the clip for most indicators and opposing trends for Mean HR,
RMSSD and LF/HF between the two conditions. Methodological suggestions include
using multiple data points for HR and HRV analysis, exploring ultra short-term
measurements, selecting self-contained clips for viewing, and considering
post-task baselines for a more accurate resting state representation. Despite
limitations due to the small sample size, this study underscores the potential
of HR and HRV as measures of immersion in translated audiovisual products,
emphasising the need for larger sample sizes in future research to enhance
statistical power and generalizability.
The economic optimization of lactation and fertility in dairy cows
Authors: Tohumcu Vefa , Tulan Tohumcu D.
Published: October 2024

Lactation and fertility are recognized as fundamental factors that directly influence the sustainability of dairy farming. For farms working with high-yielding dairy cows in particular, maintaining fertility parameters at economically optimal levels is crucial to ensuring the continued viability of such operations. This review underscores the necessity of implementing multifaceted strategies to attain optimal lactation and fertility outcomes, elucidating the requisite steps involved in the execution of these strategies. These include the careful execution of estrus monitoring plans, comprehensive staff training, systematic record-keeping, ensuring optimal fertility parameters, and the judicious interpretation of herd management mathematics. Accurate forecasting and investment necessitate consideration of current market dynamics. Understanding the complex interplay between lactation and fertility in dairy cows is a critical prerequisite for improving overall economic productivity through herd management. To this end, the review presented simulates how the optimization of these two parameters can be achieved and their target values, based on a 100-head herd. While the exemplary model is based on costs in Türkiye, readers can adapt this simulation to calculate according to their own country’s standards. Furthermore, the simulation evinced that dairy farms relying solely on milk production incur losses, highlighting the need for diversification to ensure sustainability. In conclusion, the symbiotic relationship between lactation and fertility demands a mathematical approach, and the adoption of these integrated strategies is essential for the sustainability of dairy farms. In this context, profitability can be attained by heeding all cautions regarding the optimization of fertility and lactation, while closely monitoring current market costs.
Detecting phase transitions based on siamese neural network
Authors: Shen Jianmin , Wang Shanshan , Li Wei , Deng Weibing , Xu Dian , Gao Feng
Published: October 2024

Machine learning has been widely applied in physics research. Although unsupervised learning can extract the critical points of phase transitions, the percolation model remains a challenge. Unsupervised learning using the raw configurations of the percolation model fails to capture the critical points. To capture the configuration characteristics of the percolation model, this paper proposes using the maximum cluster as input to the neural network. It is well understood that the order parameter of the percolation model is not simply the particle density, but rather the probability that a given site or bond belongs to the percolating cluster. Additionally, we introduce the use of a Siamese Neural Network (SNN) to detect percolation phase transitions. Unlike unsupervised dimensionality reduction methods or supervised binary classification outputs, the SNN produces a scalar output referred to as similarity. By combining the maximum cluster and the SNN, we not only successfully extract the critical value of the percolation model, but also calculate the correlation exponent via data collapse. We believe that the SNN has great potential in handling phase transition classification problems and can serve as a reference for studying other phase transition systems.
Investigation of the capabilities of an electro-optic modulator based on a temperature-noncritical KTP crystal
Authors: Istamgulova Julia R , Gagarskiy Sergey V , Grechin Sergey G , Druzhinin Petr Y , Rusov Vladimir A , Sergeev Andrey N
Published: October 2024

The results of theoretical and experimental investigations on angular selectivity and features of a temperature-noncritical electro-optic modulator based on the potassium titanyl phosphate crystal are presented. The influence of angular selectivity and the walk-off effect on the electro-optic modulator contrast and the inhomogeneity of the transverse distribution of modulator transmittance are investigated. The contrast value was measured for both half-wave and compensated quarter-wave schemes.
Tuning the magnetocaloric and structural properties of La0.67Sr0.28Pr0.05Mn1–xCoxO3 refrigeration materials
Authors: Xu 徐 Changji 长吉 , Jiang 姜 Xinyu 心雨 , Zou 邹 Zhengguang 正光 , Xie 谢 Zhuojia 卓家 , Zhang 张 Weijian 伟建 , Feng 冯 Min 敏
Published: October 2024

The structural, magnetic and magnetocaloric properties of perovskite manganites La0.67Sr0.28Pr0.05Mn1−x
Co
x
O3 (x = 0.05, 0.075 and 0.10) (LSPMCO) are investigated. LSPMCO crystallizes as a rhombohedral structure with R-3c space group. As the Co content increases, the cell volume expands, the Mn–O–Mn bond angle reduces and the length of the Mn–O bond increases. The samples show irregular submicron particles under a Zeiss scanning electron microscopy. The particle size becomes larger with increasing doping. The chemical composition of the samples is confirmed by x-ray photoelectron spectroscopy (XPS). The ferromagnetic (FM) to paramagnetic (PM) phase transition occurs near the Curie temperature (T
C), and all transitions are second-order phase transitions (SMOPT) characterized by minimal thermal and magnetic hystereses. Critical behavior analysis indicates that the critical parameters of LSPMCO closely align with those predicted by the mean-field model. The T
C declines with Co doping and reaches near room temperature (302 K) at x = 0.075. The maximum magnetic entropy change (

−
Δ

S
M

max

) at x = 0.05 is 4.27 J/kg⋅K, and the relative cooling power (RCP) peaks at 310.81 J/K. Therefore, the system holds significant potential for development as a magnetic refrigeration material, meriting further professional and objective evaluation.
Suppression of the Kelvin–Helmholtz instability by coating in the double-cone ignition scheme
Authors: Xie 谢 Yuan-Kai 元凯 , Zhang 张 Cheng-Long 成龙 , Cheng 程 Yi-Zhen 翊真 , Li 李 Ying-Jun 英骏
Published: October 2024

In order to address the issue of gold mixing caused by the Kelvin–Helmholtz instability (KHI) in the double-cone ignition (DCI) scheme, we investigate the growth rate of the KHI at the bi-interface of the DCI scheme after applying a coating. This is done by solving the hydrodynamic equations for an ideal incompressible fluid using linear theory. Ultimately, it is discovered that applying a coating with a thickness slightly above h = 0.5(λ + 10 μm) and a density somewhat lower than that of the target layer can effectively reduce the growth rate of interfacial KHI. This work provides theoretical references for studying the bi-interface KHI in the DCI scheme.
Deep-learning-assisted optical communication with discretized state space of structured light
Authors: Zhang 张 Minyang 敏洋 , Chen 陈 Dong-Xu 东旭 , Ruan 阮 Pengxiang 鹏祥 , Liu 刘 Jun 俊 , Fu 付 Dong-Zhi 栋之 , Zhao 赵 Jun-Long 军龙 , Yang 杨 Chui-Ping 垂平
Published: October 2024

The rich structure of transverse spatial modes of structured light has facilitated their extensive applications in quantum information and optical communication. The Laguerre–Gaussian (LG) modes, which carry a well-defined orbital angular momentum (OAM), consist of a complete orthogonal basis describing the transverse spatial modes of light. The application of OAM in free-space optical communication is restricted due to the experimentally limited OAM numbers and the complex OAM recognition methods. Here, we present a novel method that uses the advanced deep learning technique for LG modes recognition. By discretizing the spatial modes of structured light, we turn the OAM state regression into classification. A proof-of-principle experiment is also performed, showing that our method effectively categorizes OAM states with small training samples and the accuracy exceeds 99% from three-dimensional (3D) to fifteen-dimensional (15D) space. By assigning each category a classical information, we further apply our approach to an image transmission task, achieving a transmission accuracy of 99.58%, which demonstrates the ability to encode large data with low OAM number. This work opens up a new avenue for achieving high-capacity optical communication with low OAM number based on structured light.
Experiment and detection method for loose bolts in sensor installation
Authors: Wan Fahui , Wu Yafeng , Li Jin , Tao Zhenyu
Published: October 2024

Aiming at the loosening problem of the sensor connected by bolts in the process of vibration signal acquisition, the experiment is designed and the method of the problem is studied. The sensor’s different loose degree is designed by using the vibration table. The frequency response characteristics and energy distribution of the sensor under different degrees of looseness are observed by broadband white noise. The variational mode decomposition method is used to extract the vibration response characteristics of different states. The classification algorithm is used to classify the features. According to the model prediction results, it shows that the method can effectively detect the loose state of the acceleration sensor.
Multi-objective optimization design of high-speed diaphragm coupling based on RSM and NSGA-II
Authors: Cui Peizhu , Gao Chuang
Published: October 2024

This study conducts a comprehensive strength analysis of diaphragm couplings in gas turbines, focusing particularly on their performance under complex operating conditions and overload scenarios. The presented text introduces a methodology for optimizing the design of diaphragm couplings. This methodology utilizes response surface methodology and the NSGA-II genetic algorithm. Following the optimization process, significant improvements have been observed in the performance of the diaphragm coupling. These enhancements encompass a noteworthy reduction of 14.7% in maximum stress, a significant decrease of 19.1% in stress amplitude, and a marginal reduction in mass by 0.004 kg.
Study on the effect of ultrasonic impact on residual stress and deformation in welding arc additive manufacturing
Authors: Wu Jinfeng , Yu Chang , Huang Fei , Yuan Shuxian , Zhao Yue
Published: October 2024

A 2219 aluminum alloy was manufactured by ultrasonic impact arc additive welding, and well-formed multilayer and multipass deposition parts were obtained. The residual stresses on the top and substrate of 2219 aluminum alloy samples deposited by the conventional arc and ultrasonic impingement arc were measured by ultrasonic stress testing equipment. Through experiments, the following conclusions were reached: the residual stress of those specimens subjected to ultrasonic impact is lower than that of the specimens without ultrasonic impact, and the residual stress of the arcing and quenching positions is the most obvious reduction. The deformation of the substrate treated by ultrasonic impact treatment is less than that of the sample without ultrasonic impact treatment.
Three-stage flapping-wing mechanism based on double crank and double rocker
Authors: Wang Ziyu , Gao Zifan
Published: October 2024

To address the limitations of current flapping-wing structures, which fail to achieve complex and variable flight attitudes and lack dexterous bionic performance, this paper introduces a novel three-segment flapping-wing drive mechanism. This mechanism can simultaneously achieve flapping and secondary folding through a single motor drive. Through kinematic analysis, the kinematic model of the driving mechanism was established. By using the transmission angle and rod length conditions as constraints for the model, and the swing angles of the inner and mid-section rockers as objective functions, the optimization model of the flapping mechanism is established, leading to the optimization of the rod length parameters. Finally, the designed flapping-wing mechanism is simulated and analyzed using ADAMS, and the theoretical analysis is validated. The results align with biological flight parameters, demonstrating that the flapping-wing mechanism possesses favorable flight characteristics and bionic motion properties. The ADAMS simulation analysis curve is consistent with the MATLAB theoretical calculation analysis curve, confirming the accuracy of the theoretical analysis.
Optimization of fuzzy-PID temperature controller based on improved slime mould algorithm
Authors: Liu Xiaoma , Zhang Zhen , Peng Zhuo , Yang Jingsong
Published: October 2024

The temperature control system in narrow and closed spaces such as heating furnaces often has the characteristics of large hysteresis, inertia, and non-linearity. In this scenario, the classical PID controller makes it difficult to achieve a satisfactory control effect, for this reason, domestic and foreign research and practical engineering applications mostly use fuzzy PID controllers. In this paper, we first introduce Tent chaotic mapping, nonlinear feedback updating factor to improve the standard slime mould optimization algorithm (SMA), and then the quantization factor and scale factor are both optimized based on the improved SMA. The simulation is carried out in the standard test function and the typical confined space temperature control system and the results show that compared with classical PID control and fuzzy PID control methods, the proposed controller has a shorter rise time, smaller tracking error, and superior control effect.
Simulation of cooling system performance of super magnetostrictive actuator for high-speed trains
Authors: Liu Tianren , Meng Jianjun
Published: October 2024

Given the thermal characteristics of the super magnetostrictive actuator, a cooling system is designed for the heat dissipation characteristics of the super magnetostrictive actuator of high-speed trains. Based on the Ansys finite element analysis platform, the heat generation problem of the super magnetostrictive actuator is introduced and analyzed, the thermal performance parameters of the magnetostrictive material are studied, the Jile-Atherton hysteresis regression model based on the eddy current loss and the additional loss parameter is established, and the total loss of the super magnetostrictive actuator in the active suspension system of the high-speed train is calculated. The cooling water flow field is solved and calculated as a boundary with the help of the finite element analysis method. With the help of finite element analysis, the temperature field of the super magnetostrictive actuator is calculated by solving the cooling water flow field and using it as the boundary. A new water cooling de-heating method is proposed. Through repeated simulations, the experimental data and the calculation results are consistent. The temperature fluctuations during operation are suppressed, which confirms the feasibility of heat dissipation and cooling, reduces the probability of the GMA temperature rise effect, effectively suppresses the harmful effects of the temperature rise effect, and has a good cooling effect on the super magnetostrictive actuator of high-speed trains.
Comparison of the dynamic response of clamped plates under fully confined and unconfined air-blast loading
Authors: Chen Zengkui , Xia Yan , Liu Dong , Li Xue , Zhao Zhenyu , Lu Tianjian
Published: October 2024

Compared to an unconfined explosion, e.g., air blast, explosive threats in confined spaces must be carefully considered in fields such as aerospace, aviation, and shipping due to their dramatic destructive potential. This paper systematically investigates and compares the dynamic mechanical responses of monolithic plates under fully confined/unconfined blast loadings. Three-dimensional finite element (FE) simulations using the Coupled Eulerian-Lagrangian (CEL) method are validated, demonstrating a remarkable concordance with experimental observations for monolithic plates. Structural permanent deflections and deformation modes are captured by detonating the spherical TNT charge. In addition, numerical predictions further reveal additional insights into the complex interactions of blast shock waves and structure. The structural response to confined blast conditions is contrasted with that under air blast, considering an equivalent stand-off distance between the spherical charge and the specimen. The comparison reveals that the final structural deformation is four times greater in the confined blast scenario compared to the air blast case.
Feature extraction for periodic impacts based on singular gini index
Authors: Liang Lin , Cui Xujun , Liu Chengxu
Published: October 2024

Impulsivity and periodicity are key characteristics of bearing impact faults, which can be more advisable than energy-oriented methods when applied to develop effective singular component selection strategies. Therefore, unlike standard singular value decomposition methods, a fault feature extraction technique based on singular value sequence distribution and the Gini index is proposed. This approach employs the Gini index as a metric to assess both the impulsiveness and periodicity characteristics of individual components. It can describe the richness of fault information in singular components. Based on the proposed evaluation criteria, an effective singular component retention strategy is proposed, which can identify components with weak energy but rich fault information in vibration signals. Through simulation data analysis and application examples, the validity of the approach is confirmed.
Design of a new scintillator-based fast ion loss detector on the HL-2A tokamak
Authors: Yuxiao Han , Jinlin Xie , Jie Zhang , Xiaofei He , Yongqing Wang , Linzi Liu , Hongbing Xu , Xuwen Zhan , Kuancheng Liu , Yipo Zhang , Zhongbing Shi , Wei Chen , Wulv Zhong , Min Xu , Ge Zhuang ,   the HL-2A Team
Published: October 2024

A new scintillator-based fast ion loss detector (FILD) has
been devised for the HL-2A tokamak, with the objective of discerning
the temporal evolution of energy and pitch angle among lost fast
ions. A code named FILD Simulation (FSC) has been developed to
assist in the design of the detector head and the interpretation of
experimental data. By optimising the geometric design, the
resolutions of energy and pitch angle are optimised to 5 keV and
3°, respectively. A branched imaging fiber bundle is used to
relay the fluorescence image on the scintillator to two distinct
instruments. One of these is a high-speed camera, while the other is
a silicon photomultiplier tube (SiPM) array with a sampling rate of
up to 1 MSamples/s. This configuration enables the attainment of
superior temporal and spatial resolution, as well as high photon
sensitivity.
Improving the representation of cattle grazing patterns in the European Union
Authors: Malek Žiga , Romanchuk Zoriana , Yaschun Orysia , Jones Gwyn , Petersen Jan-Erik , Fritz Steffen , See Linda
Published: October 2024

Improving the sustainability of the European cattle sector requires improved knowledge not only of the density of cattle, but also of the grazing patterns. Only in this way can the potential negative impacts of cattle related to local ecosystem degradation, as well as positive ones such as preserving cultural landscapes through grazing, be analyzed. While data on livestock distribution often used in scientific analyses can provide estimates on density, the separation between the livestock that has access to outdoor grazing and those that remain indoors is not available. This is problematic because it prevents the identification of the intensity and type of grassland management, as well as the consequential environmental impacts of grazing livestock. Here we present an approach where we combined agricultural and veterinary statistics, in-situ data, expert surveys and machine learning to develop a map of grazing cattle distribution for the wider European Union region. Our approach and the resulting data allow for the differentiation between cattle that are actually grazing versus those that do not. We also compare our method to traditional approaches that do not have a clear separation between grazing and non-grazing cattle, illustrating the implications that this can have for agricultural, land use and environmental assessments.
Data visualisation for decision making under deep uncertainty: current challenges and opportunities
Authors: Hadjimichael Antonia , Schlumberger Julius , Haasnoot Marjolijn
Published: October 2024

This perspective article explores the role of data visualisation in decision-making under deep uncertainty (DMDU), a growing discipline tackling complex socio-environmental challenges, such as climate impacts and adaptation, natural resource management, and preparedness for extreme events. We discuss the role of visualisation for both analysis (or exploratory) purposes, as well as communication (or explanatory) purposes, including to stakeholders and the public. We identify a lack of comprehensive guidelines on how visualisations are currently used and their potential in enhancing DMDU processes. Drawing on literature and insights from a recent workshop, we identify key challenges DMDU analysts face when visualising data: managing complexity and dimensionality, effectively communicating uncertainty, and ensuring user engagement and interpretability. We propose a research agenda to address these challenges, by taxonomising and evaluating the effectiveness of different visual forms in decision-making contexts, and fostering interdisciplinary collaboration. We argue that, through these efforts, we can improve the communication and usability of DMDU analyses, ultimately aiding in more informed and adaptive decision-making in the face of deep uncertainty.
Exact solution of long-range stabilizer Rényi entropy in the dual-unitary XXZ model*
Authors: Montañà López Jordi Arnau , Kos Pavel
Published: October 2024

Quantum systems can not be efficiently simulated classically due to the presence of entanglement and nonstabilizerness, also known as quantum magic. Here we study the generation of magic under evolution by a quantum circuit. To be able to provide exact solutions, we focus on the dual-unitary XXZ model and a measure of magic called stabilizer Rényi entropy (SRE). Moreover, we focus also on long-range SRE, which cannot be removed by short-depth quantum circuits. To obtain exact solutions we use a ZX-calculus representation and graphical rules for the evaluation of the required expressions. We obtain exact results for SRE after short-time evolution in the thermodynamic limit and for long-range SRE for all times and all Rényi parameters for a particular partition of the state. Since the numerical evaluation of these quantities is exponentially costly in the Rényi parameter, we verify this numerically for low Rényi parameters and accessible system sizes and provide numerical results for the long-range SRE in other partitions.
Singing Utopia
Authors: Macpherson Ben
Published: October 2024

Singing Utopia offers an original and provocative account of singing voices in musical theatre. It listens to extraordinary voices across fifteen case studies, from Florodora to Hadestown, and hears an emotional and situational directness—a utopian sound which seems to escape the mundanity of everyday life. Yet, the very idea of the utopian is paradoxical, fraught with undercurrents of nostalgia, melancholy, and the perpetual threat of the dystopian. Singing Utopia also explores these facets and considers what it means for a musical to give voice to an imagined world which is always a contradiction in terms. Exploring who gets to inhabit such a world and who may be excluded, the book draws on a diverse range of disciplinary approaches from voice studies and musicology to literary studies and ethnography. It examines the political potentials and paradoxes of musical theatre vocality in relation to class, race, gender, and culture. In doing so, Singing Utopia examines current ways of listening to and analysing voice and at the same time moves beyond them to develop a series of new terms, including ‘decadent appropriation’, ‘simuloquism’, two kinds of ‘voiceworld’, and three new approaches to the chorus and ensemble. Together, these offer readers a new set of tools for listening to voice in musical theatre, with further applications to other fields.