bluuebunny/crossref_metadata_2025 huggingface dataset:
Ptychographic X-ray computed tomography of porous membranes with nanoscale resolution
Authors: Górecki Radosław , Polo Carla Cristina , Kalile Tiago Araujo , Miqueles Eduardo X. S. , Tonin Yuri R. , Upadhyaya Lakshmeesha , Meneau Florian , Nunes Suzana P.
Published: September 2023

New visualization methods can be utilized to resolve structures at resolutions that were previously unachievable. 3D images of porous materials with high resolution have been so far obtained using transmission electron tomography or focused ion beam coupled with scanning electron microscopy. For these methods, ultra-vacuum is required, and only a small volume of the sample is visualized. Here, we demonstrate the application of ptychographic X-ray computed tomography for the visualization of soft matter with a resolution of 26 nm over large fields of view. Thanks to the high-penetration depth of the X-ray beam, we visualize the 3D complex porous structure of polyetherimide hollow fibers in a non-destructive manner and obtain quantitative information about pore size distribution and pore network interconnectivity across the whole membrane wall. The non-destructive nature of this method, coupled with its ability to image samples without requiring modification or a high vacuum environment, makes it valuable in the fields of porous- and nano-material sciences enabling imaging under different environmental conditions.
Top-down structuring of freshwater bacterial communities by mixotrophic flagellates
Authors: Ivanković Marina , Ptacnik Robert , Bengtsson Mia Maria
Published: September 2023

Mixotrophic and heterotrophic protists hold a key position in aquatic microbial food webs. Whereas they can account for the bulk of bacterivory in pelagic systems, the potential structuring effect of these consumers on bacterial communities is far from clear. We conducted short-term grazing experiments to test for the overall impact on bacterial community structure and possible prey preferences of phagotrophic protists. The protist taxa selected for this study include three mixotrophic flagellates, comprising two obligate- and one facultative mixotroph, and one phagoheterotrophic flagellate lacking phototrophic capacity. Bacterioplankton from seven different lakes were enriched and used to represent semi-natural prey communities. Our study demonstrated protist strain specific impacts on bacterial community composition linked to grazing. The three mixotrophs had variable impacts on bacterial communities where the two obligate mixotrophs exhibited lower grazing rates, while showing a tendency to promote higher bacterial diversity. The phagoheterotroph displayed the highest grazing rates and structured the bacterial communities via apparent selective grazing. Consistent selectivity trends were observed throughout the experiments, such as the apparent avoidance of all flagellates of Actinobacteria, and high grazing on dominant Burkholderiales taxa. However, there was no consistent “fingerprint” of mixotrophic grazing on prey communities, but the structuring impact rather seemed to depend on the trophic mode of the individual protist taxa, i.e. their dependence on phototrophy vs. phagotrophy. Our findings highlight the differential structuring impact of protist taxa on bacterial communities which may have important ecological implications, for example during periodic dominance of obligate mixotrophic bacterivores in changing lake ecosystems.
Top abundant deep ocean heterotrophic bacteria can be retrieved by cultivation
Authors: Sanz-Sáez Isabel , Sánchez Pablo , Salazar Guillem , Sunagawa Shinichi , de Vargas Colomban , Bowler Chris , Sullivan Matthew B , Wincker Patrick , Karsenti Eric , Pedrós-Alió Carlos , Agustí Susana , Gojobori Takashi , Duarte Carlos M , Gasol Josep M , Sánchez Olga , Acinas Silvia G
Published: September 2023

Traditional culture techniques usually retrieve a small fraction of the marine microbial diversity, which mainly belong to the so-called rare biosphere. However, this paradigm has not been fully tested at a broad scale, especially in the deep ocean. Here, we examined the fraction of heterotrophic bacterial communities in photic and deep ocean layers that could be recovered by culture-dependent techniques at a large scale. We compared 16S rRNA gene sequences from a collection of 2003 cultured heterotrophic marine bacteria with global 16S rRNA metabarcoding datasets (16S TAGs) covering surface, mesopelagic and bathypelagic ocean samples that included 16 of the 23 samples used for isolation. These global datasets represent 60 322 unique 16S amplicon sequence variants (ASVs). Our results reveal a significantly higher proportion of isolates identical to ASVs in deeper ocean layers reaching up to 28% of the 16S TAGs of the bathypelagic microbial communities, which included the isolation of 3 of the top 10 most abundant 16S ASVs in the global bathypelagic ocean, related to the genera Sulfitobacter, Halomonas and Erythrobacter. These isolates contributed differently to the prokaryotic communities across different plankton size fractions, recruiting between 38% in the free-living fraction (0.2–0.8 µm) and up to 45% in the largest particles (20–200 µm) in the bathypelagic ocean. Our findings support the hypothesis that sinking particles in the bathypelagic act as resource-rich habitats, suitable for the growth of heterotrophic bacteria with a copiotroph lifestyle that can be cultured, and that these cultivable bacteria can also thrive as free-living bacteria.
Phagotrophic protists preserve antibiotic-resistant opportunistic human pathogens in the vegetable phyllosphere
Authors: Lin Chenshuo , Li Li-Juan , Ren Kexin , Zhou Shu-Yi-Dan , Isabwe Alain , Yang Le-Yang , Neilson Roy , Yang Xiao-Ru , Cytryn Eddie , Zhu Yong-Guan
Published: September 2023

Food safety of leafy greens is an emerging public health issue as they can harbor opportunistic human pathogens (OHPs) and expose OHPs to consumers. Protists are an integral part of phyllosphere microbial ecosystems. However, our understanding of protist-pathogen associations in the phyllosphere and their consequences on public health remains poor. Here, we examined phyllosphere protists, human pathogen marker genes (HPMGs), and protist endosymbionts from four species of leafy greens from major supermarkets in Xiamen, China. Our results showed that Staphylococcus aureus and Klebsiella pneumoniae were the dominant human pathogens in the vegetable phyllosphere. The distribution of HPMGs and protistan communities differed between vegetable species, of which Chinese chive possessed the most diverse protists and highest abundance of HPMGs. HPMGs abundance positively correlated with the diversity and relative abundance of phagotrophic protists. Whole genome sequencing further uncovered that most isolated phyllosphere protists harbored multiple OHPs which carried antibiotic resistance genes, virulence factors, and metal resistance genes and had the potential to HGT. Colpoda were identified as key phagotrophic protists which positively linked to OHPs and carried diverse resistance and virulence potential endosymbiont OHPs including Pseudomonas nitroreducens, Achromobacter xylosoxidans, and Stenotrophomonas maltophilia. We highlight that phyllosphere protists contribute to the transmission of resistant OHPs through internalization and thus pose risks to the food safety of leafy greens and human health. Our study provides insights into the protist-OHP interactions in the phyllosphere, which will help in food safety surveillance and human health.
Cationic metal–organic framework with charge separation effect as a high output triboelectric nanogenerator material for self-powered anticorrosion
Authors: Shao Zhichao , Cheng Haoran , Wei Yi , Chen Junshuai , Gao Kexin , Fang Zhe , Yan Yangshuang , Mi Liwei , Hou Hongwei
Published: September 2023

A cationic metal–organic framework with good chemical stability and excellent triboelectric output performance was prepared. The good output performance makes ZUT-iMOF-1(Cu) effective in preventing metal corrosion in cathodic protection systems.
A wide temperature 10 V solid-state electrolyte with a critical current density of over 20 mA cm−2
Authors: Wei Yiqi , Li Zhenglong , Chen Zichong , Gao Panyu , Gao Mingxi , Yan Chenhui , Wu Zhijun , Ma Qihang , Jiang Yinzhu , Yu Xuebin , Zhang Xin , Liu Yongfeng , Yang Yaxiong , Gao Mingxia , Sun Wenping , Qu Zhiguo , Chen Jian , Pan Hongge
Published: September 2023

An in situ melting reaction is used to create covalently bonded coordination on the surfaces of hydride electrolytes, which achieves strong capacity to suppress dendrite growth, broaden voltage windows, and extend operational temperature ranges.
Spectrally narrow band-edge photoluminescence from AgInS2-based core/shell quantum dots for electroluminescence applications
Authors: Uematsu Taro , Izumi Ryunosuke , Sugano Shoki , Sugano Riku , Hirano Tatsuya , Motomura Genichi , Torimoto Tsukasa , Kuwabata Susumu
Published: September 2023

This study facilitates the synthesis of cadmium-free QDs, enhances their photoluminescence, and proposes a new LED device structure suitable for these QDs.
Lactobacillus rhamnosus GG administration partially prevents diet-induced insulin resistance in rats: a comparison with its heat-inactivated parabiotic
Authors: Arellano-García L. , Macarulla M. T. , Cuevas-Sierra A. , Martínez J. A. , Portillo M. P. , Milton-Laskibar I.
Published: September 2023

Insulin resistance and type 2 diabetes are obesity-related health alterations, featuring an ever-increasing prevalence.
Ultrasound-driven fabrication of hybrid magnetic tryptophan nanoparticles
Authors: Baral Anshul , Zhu Haiyan , Moffat Bradford A. , Chattopadhyay Santanu , Cavalieri Francesca , Ashokkumar Muthupandian
Published: September 2023

A facile sonochemical method to fabricate magnetic tryptophan-iron oxide nanoparticles for biomedical applications.
Infected wound repair with an ultrasound-enhanced nanozyme hydrogel scaffold
Authors: Zhang Fan , Kang Yong , Feng Liwen , Xi Guan , Chen Wei , Kong Na , Tao Wei , Luan Tiangang , Koo Seyoung , Ji Xiaoyuan
Published: September 2023

An all-round therapeutic strategy based on high-density platinum nanoparticle assemblies nanozymes was developed to simultaneously scavenge ROS, generate O2 and regulate the immune system for accelerating diabetic wound healing.
Ruthenium(v) terminal arylimido corroles: isolation, spectroscopic characterization and reactivity
Authors: Shing Ka-Pan , Qin Lin , Wu Liang-Liang , Huang Jie-Sheng , Che Chi-Ming
Published: September 2023

This work reports the isolation and spectroscopic characterization of pentavalent metal–imido species that are reactive towards N-group transfer reactions including alkene aziridination and C–H amination.
Simultaneous on-site visual identification of norovirus GI and GII genogroups with point-of-care molecular lateral flow strip
Authors: Zong Ziwen , Meng Xianzhuo , Li Weiwei , Xu Jianguo , Yu Junling , Wang Xinxin , Wang Peng , Liu Guodong , Sun Yong , Chen Wei
Published: September 2023

Norovirus (NoV) possesses a significant risk for outbreaks of acute gastroenteritis all over the world.
A hybrid mechanistic machine learning approach to model industrial network dynamics for sustainable design of emerging carbon capture and utilization technologies
Authors: Shekhar Abhimanyu Raj , Moar Raghav R. , Singh Shweta
Published: September 2023

Industrial networks consist of multiple industrial nodes interacting with each other through material exchanges that support the overall production goal of the network.
Shape memory photonic materials: fabrication and emerging applications
Authors: Chen Xiaodong , Hu Zhen , Lyu Quanqian , Li Miaomiao , Zhang Lianbin , Zhu Jintao
Published: September 2023

Shape memory photonic materials are intelligent optical materials that have shape memory abilities and show great potential in various applications, including actuators, visual sensors, anti-counterfeiting labels, and smart display units.
Morphology and gene expression of sex‐determining region Y‐box 9 and runt‐related transcription factor 2 in centrifugally compressed cell collagen‐combined constructs (C6)
Authors: Ye Xu , Yamazaki Masashi , Ando Wataru , Nakamura Norimasa , Fujie Hiromichi
Published: September 2023

The authors previously developed a scaffold‐free tissue‐engineered construct (TEC) from mesenchymal stem cells (MSCs). Although the TEC exhibited even cell distribution and was successfully applied for cartilage repair in animal models, it is unsuitable for relatively large‐scale cartilage defects due to its small size. To solve the problem, the authors recently developed a novel biomaterial, a centrifugally compressed cell‐collagen combined construct (C6) from a mixture of MSCs and atelocollagen, both of which are subjected to centrifugation. The results of the previous study indicated that C6 exhibited high cell viability (70 %) and sufficient cell distribution similar to that of the TEC. In the present study, the morphology and gene expression of C6 were investigated. Histological examination indicated that C6 is six times thicker (approximately 1 mm) than the TEC after a 7‐day culture. The C6 remained unchanged in scale with increased cell density after a 21‐day culture. Scanning electron microscopic observation indicated that C6 exhibited interconnected and porous microstructures, while the TEC had close‐knit microstructures. Reverse transcriptase‐polymerase chain reaction analysis indicated that the expression of sex‐determining region Y‐box 9 and runt‐related transcription factor 2 was significantly higher in C6 than that in TEC.
Unleashing the power of generative adversarial networks: A novel machine learning approach for vehicle detection and localisation in the dark
Authors: Hassan Onim Md Saif , Nyeem Hussain , Khan Arnob Md. Wahiduzzaman , Pooja Arunima Dey
Published: September 2023

Machine vision in low‐light conditions is a critical requirement for object detection in road transportation, particularly for assisted and autonomous driving scenarios. Existing vision‐based techniques are limited to daylight traffic scenarios due to their reliance on adequate lighting and high frame rates. This paper presents a novel approach to tackle this problem by investigating Vehicle Detection and Localisation (VDL) in extremely low‐light conditions by using a new machine learning model. Specifically, the proposed model employs two customised generative adversarial networks, based on Pix2PixGAN and CycleGAN, to enhance dark images for input into a YOLOv4‐based VDL algorithm. The model's performance is thoroughly analysed and compared against the prominent models. Our findings validate that the proposed model detects and localises vehicles accurately in extremely dark images, with an additional run‐time of approximately 11 ms and an accuracy improvement of 10%–50% compared to the other models. Moreover, our model demonstrates a 4%–8% increase in Intersection over Union (IoU) at a mean frame rate of 9 fps, which underscores its potential for broader applications in ubiquitous road‐object detection. The results demonstrate the significance of the proposed model as an early step to overcoming the challenges of low‐light vision in road‐object detection and autonomous driving, paving the way for safer and more efficient transportation systems.
Deep Q‐learning recommender algorithm with update policy for a real steam turbine system
Authors: Modirrousta Mohammad Hossein , Aliyari Shoorehdeli Mahdi , Yari Mostafa , Ghahremani Arash
Published: September 2023

In modern industrial systems, diagnosing faults in time and using the best methods becomes increasingly crucial. It is possible to fail a system or to waste resources if faults are not detected or are detected late. Machine learning and deep learning (DL) have proposed various methods for data‐based fault diagnosis, and the authors are looking for the most reliable and practical ones. A framework based on DL and reinforcement learning (RL) is developed for fault detection. The authors have utilised two algorithms in their work: Q‐Learning and Soft Q‐Learning. Reinforcement learning frameworks frequently include efficient algorithms for policy updates, including Q‐learning. These algorithms optimise the policy based on the predictions and rewards, resulting in more efficient updates and quicker convergence. The authors can increase accuracy, overcome data imbalance, and better predict future defects by updating the RL policy when new data is received. By applying their method, an increase of 3%–4% in all evaluation metrics by updating policy, an improvement in prediction speed, and an increase of 3%–6% in all evaluation metrics compared to a typical backpropagation multi‐layer neural network prediction with comparable parameters is observed. In addition, the Soft Q‐learning algorithm yields better outcomes compared to Q‐learning.
Electric vehicle dispatching strategy considering time cost and risk of operating distribution network
Authors: Wang He , Leng Xianda , Liang Zhifeng , Huo Xuesong , Yu Ruoying , Bian Jing
Published: September 2023

Electric vehicles (EVs) are increasingly being valued by countries, but the disorderly charging behaviour of too many EVs poses a huge challenge to the operation of the power grid. First, for EVs, a methodical charging and discharging technique was designed, taking into account the temporal and spatiotemporal characteristics of different EV models, time convenience of owners, and safe operation of power grid. Second, the EV characteristics and safe operation of the grid after EV integration into the grid are presented for vehicle owners to achieve minimal charging station and optimal charging stations selection as well as charging and discharging schemes. Third, simulation calculations and analyses of ordered charging and discharging modes as well as disordered charging modes under various scenarios were performed. This study fully considers the characteristics of different vehicle models and the willingness of users to respond, making the model more realistic. The findings demonstrate that the optimised charging and discharging strategy in this study lowers the cost of charging for vehicle owners, boosts revenue from the charging station and the rate of use of the charging pile, lowers the risk of the safe operation of distribution networks, and effectively relieves pressure on the power grid. While solving the scheduling difficulties of a large number of EVs, it increases the economy between users and the power grid, and improves the safety of power grid operation.
Research on train braking model by improved Polach model considering wheel‐rail adhesion characteristics
Authors: Chen Peiwen , Zhu Wenliang , Yu Chaogang , Sun Ningyuan , Xue Wenshen
Published: September 2023

To study the braking process of the train under different adhesion conditions, this paper takes the braking system of a single rail vehicle as the research object. The author establishes a corresponding co‐simulation platform based on MATLAB/Simulink and AMESim, including the sub‐models of braking control, vehicle brake longitudinal dynamics and air brake unit. Considering the cleaning effect caused by large sliding, the author builds a suitable adhesion model for different adhesion conditions based on the improved Polach model, which is the input of the vehicle braking longitudinal dynamics sub‐model. Based on the finite state machine, the anti‐skid control algorithm of the train is constructed as the core of the brake control sub‐model, which can judge the motion state of the wheelset, and control the stage release and hold of the brake cylinder pressure. According to the International Standard EN15595 and the actual operating parameters of a certain type of train, the braking process of the train under dry and wet rail conditions is simulated on the platform. The validity of the model is verified, which provides a reliable method for future research on the braking process.
Outage performance prediction of cooperative vehicle network based on sparrow search algorithm based on back‐propagation neural network
Authors: Li Ya , Zhang Yu , Tian Xinji , Liu Ruipeng
Published: September 2023

With the support of the sixth‐generation mobile networks (6G) technology, the Internet‐of‐Vehicle (IoV) can realize the perception and monitoring of vehicle road information. However, due to the change of network topology and various environment, the reliable performance of the communication link is facing challenges. For the sake of improving communication quality, a cooperative vehicular network (CVN) system is established, which adopts cooperative communication and multiple input multiple output (MIMO) technology. According to the signal‐to‐noise ratio (SNR) threshold of relay vehicles, using hybrid decode‐amplify‐forward (HDAF) protocol and combining with antenna selection, the analytical expression of outage probability (OP) with Meijer‐G function is obtained. For predicting the OP accurately, the sparrow search algorithm based on back‐propagation neural network (SSA‐BPNN) is put forward. The simulation results show that the cascade order of the channels has a negative effect on the OP. Meanwhile, the prediction accuracy of SSA‐BPNN is 64.8% higher than that of BPNN, and 98.96% greater than that of general regression neural network, and the convergence rate is faster than ICS‐BPNN.
Reinforcement learning for the traveling salesman problem: Performance comparison of three algorithms
Authors: Wang Jiaying , Xiao Chenglong , Wang Shanshan , Ruan Yaqi
Published: September 2023

Travelling salesman problem (TSP) is one of the most famous problems in graph theory, as well as one of the typical nondeterministic polynomial time (NP)‐hard problems in combinatorial optimization. Reinforcement learning (RL) has been widely regarded as an effective tool for solving combinatorial optimization problems. This paper attempts to solve the TSP problem using different reinforcement learning algorithms and evaluated the performance of three RL algorithms (Q‐Learning, SARSA, and Double Q‐Learning) under different reward functions, ε‐greedy decay strategies, and running times. A comprehensive analysis and comparison of the three algorithms mentioned above were conducted in the experiment. First, the experimental results indicate that the Double Q‐Learning algorithm is the best algorithm. Among the eight TSP instances, the Double Q‐Learning algorithm outperforms the other two algorithms in five instances. Additionally, it has shorter runtimes compared to the SARSA algorithm and similar runtimes to the Q‐Learning algorithm across all instances. Second, upon analysing the results, it was found that using the reward strategy contributes to obtaining the best results for all algorithms. Among the 24 combinations of 3 algorithms and 8 instances, 17 combinations achieved the best results when the reward strategy was set to .
The role of supernovae inside AGN jets in UHECR acceleration
Authors: Bosch-Ramon V.
Published: September 2023

Context. Jets of active galactic nuclei are potential accelerators of ultra high-energy cosmic rays. Supernovae can occur inside these jets and contribute to cosmic ray acceleration, particularly of heavy nuclei, but that contribution has been hardly investigated so far.

Aims. We carried out a first dedicated exploration of the role of supernovae inside extragalactic jets in the production of ultra high-energy cosmic rays.

Methods. We characterized the energy budget of supernova-jet interactions, and the maximum possible energies of the particles accelerated in those events, likely dominated by heavy nuclei. This allowed us to assess whether these interactions can be potential acceleration sites of ultra high-energy cosmic rays, or at least of their seeds. For that, we estimated the cosmic ray luminosity for different galaxy types, and compared the injection rate of cosmic ray seeds into the jet with that due to galactic cosmic ray entrainment.

Results. Since the supernova is fueled for a long time by the luminosity of the jet, the energy of a supernova-jet interaction can be several orders of magnitude greater than that of an isolated supernova. Thus, despite the low rate of supernovae expected to occur in the jet, they could still provide more seeds for accelerating ultra high-energy particles than cosmic ray entrainment from the host galaxy. Moreover, these interactions can create sufficiently efficient accelerators to be a source of cosmic rays with energies ≳10 EeV.

Conclusions. Supernova-jet interactions can contribute significantly to the production of ultra high-energy cosmic rays, either directly by accelerating these particles themselves or indirectly by providing pre-accelerated seeds.
Stellar obliquity and planetary albedo in HAT-P-32
Authors: Czesla S. , Schneider P. C. , Hatzes A.
Published: September 2023

HAT-P-32 is an exceptional planetary system. Its active F-type host star is orbited by a hot Jupiter, the evaporation of which produces a giant structure of tidal tails. We analyze the light curve of HAT-P-32 obtained by the Transiting Exoplanet Survey Satellite (TESS) and find a secondary eclipse superimposed on photometric modulation likely caused by stellar rotation. We estimate a secondary eclipse depth of (1.4 ± 0.4)×10−4. Adopting a prior of 1962 ± 83 K for the effective planetary dayside temperature yields values of 0.16 ± 0.07 for the geometric albedo and an associated estimate of 0.46 ± 0.21 for the circulation efficiency of HAT-P-32 b, which favor a dark and windy scenario for the atmosphere. Our analysis of the photometric modulation yields a stellar rotation period of 2.974 ± 0.004 d, implying a value of 79° for the inclination of the stellar rotation axis with a 95% credible interval from 70° to 88°. This constraint further allows us to estimate a value of (84.9 ± 1.5)° for the three-dimensional obliquity. Despite showing an almost polar planetary orbit, the host star is, therefore, seen nearly equator on.
Algorithmic aspect on total Roman {2}-domination of Cartesian products of paths and cycles
Authors: Chen Qin
Published: September 2023

A total Roman {2}-dominating function (TR2DF) on a graph G with vertex set V is a function f : V → {0, 1, 2} having the property that for every vertex v with f(v) = 0, ∑u∈N (v) f(u) ≥ 2, where N(v) represents the open neighborhood of v, and the subgraph of G induced by the set of vertices with f(v) > 0 has no isolated vertex. The weight of a TR2DF f is the value w(f) = ∑v∈V f(v), and the minimum weight of a TR2DF of G is the total Roman {2}-domination number γtR2(G). The total Roman {2}-domination problem (TR2DP) is to determine the value γtR2(G). In this paper, we first propose an integer linear programming (ILP) formulation for the TR2DP. Furthermore, we apply the discharging approach to determine the total Roman {2}-domination number for some Cartesian products of paths and cycles.
Statistical validation of ionospheric electron density profiles retrievals from GOES geosynchronous satellites
Authors: Zakharenkova Irina , Cherniak Iurii , Gleason Scott , Hunt Douglas , Freesland Douglas , Krimchansky Alexander , McCorkel Joel , Ramsey Graeme , Chapel Jim
Published: September 2023

In this paper, we discuss a novel retrieval of ionospheric electron density profiles using the Radio Occultation (RO) technique applied to measurements captured by the Global Positioning System (GPS) receivers onboard two Geostationary Operational Environmental Satellites (GOES). The GOES satellites operate at ~35,800 km altitude and are primarily weather satellites that operationally contribute continuous remote-sensing data for real-time weather forecasting, as well as near-Earth environment monitoring and Sun observations. The GPS receivers onboard GOES-16 and GOES-17 satellites can track GPS signals propagated through the Earth’s atmosphere, and although the receivers are primarily designed for navigation and station-keeping maneuvers, these GPS measurements that traverse the Earth’s atmosphere can be used to retrieve the ionospheric electron density profiles. This process poses a range of technical challenges. GOES RO links are different from the traditional low Earth orbit (LEO) RO geometry since the receiver is located in an orbit that is higher in altitude than the GPS constellation of transmitters. Additionally, the GPS receivers onboard GOES satellites provide only single-frequency GPS L1 observations and have clocks much less stable than those typically used for RO measurements. The geographical distribution of the retrieved GEO-based RO profiles was found to be uniquely constrained and repeatable based on the relative geostationary fixed positions in the Earth-Centered Earth Fixed reference frame with respect to the GPS constellation orbiting at lower altitude, and significantly different from the coverage patterns of LEO-based RO missions. We demonstrate the successful application of the proposed RO profiling technique with a statistically significant set of GPS observations from GOES-16 and GOES-17 satellites over several years of data collection. This enabled us to retrieve more than 10,000 ionospheric electron density profiles with a maximum altitude of up to 1000–2000 km, much higher than any existing LEO-based RO mission. We demonstrate good performance of GEO-based RO measurements for properly specifying the vertical distribution of ionospheric plasma density by comparing the profiles dataset from the GOES RO experiment with independent reference observations – ground-based ionosondes and LEO-based RO missions, as well as model simulation results provided by the empirical International Reference Ionosphere model. Over multiple years of observations, statistical analysis of discrepancies between the ionospheric F2 layer peak parameters (peak density and height) derived from geosynchronous GOES observations and reference measurements was conducted. This analysis reveals a very good agreement between GOES RO electron density profiles and independent types of measurements in both the F2 peak and the profile shape.
The concept of “interaction” in debates on human–machine interaction
Authors: Schleidgen Sebastian , Friedrich Orsolya , Gerlek Selin , Assadi Galia , Seifert Johanna
Published: September 2023

The concept of “interaction” is central to debates on Human–machine interaction (HMI). At the same time, however, it is vague and ambiguous: “interaction” is understood in different ways within and between the scientific disciplines involved in debates on HMI. Ultimately, this makes it difficult to reasonably debate questions of ethics, politics, engineering, and the sciences regarding HMI. Against this background, we elaborate and analyze the different meanings and dimensions of the term “interaction” in the disciplines and discourses relevant to debates on modern HMI. For this purpose, we introduce a four-dimensional SMPC model, according to which “interaction” is specified with a view to its subjects, modes, purposes, and contexts. With this, we aim to provide a basis for a fruitful intra- and particularly interdisciplinary discourse on HMI.
The effect of WC-Co substrates on TiN/TiCN/Al2O3/TiCNO multilayer coatings
Authors: Huang Yingpu , Zhu Lihui , Liu Zhenyu , Bian Yuanyuan
Published: September 2023

In order to determine optimum substrate, TiN/TiCN/Al2O3/TiCNO coatings were deposited on WC-7Co substrate and WC-6Co substrate (named as Coating-7Co and Coating-6Co, respectively), and then the effect of WC-Co substrates on TiN/TiCN/Al2O3/TiCNO multilayer coatings was investigated by comparing the microstructure, hardness, adhesion strength, oxidation resistance and wear resistance of Coating-7Co and Coating-6Co. Results show that WC grain size of WC-6Co substrate is smaller, correspondingly the grain size of each layer in Coating-6Co is smaller, and the surface roughness is lower. Compared with Coating-7Co, Coating-6Co exhibits higher hardness, better plastic deformation capability, better oxidation resistance, lower friction coefficient and better short-period wear resistance. However, because of higher residual tensile stress and lower adhesion strength, the long-period wear resistance of Coating-6Co is worse than Coating-7Co conversely. To make good use of Coating-6Co, some post-deposition treatment techniques that can reduce residual tensile stress and improve adhesion strength should be considered.
Comparative first-principles structural and vibrational properties of rutile and anatase TiO2
Authors: Ghose Krishna K , Liu Yun , Frankcombe Terry J
Published: September 2023

The structural and vibrational properties of two polymorphs of TiO2, rutile and anatase, have been investigated by first-principles methods at different levels of exchange-correlational (XC) energy functionals in density functional theory (DFT). Reports in the literature to date are contradictory regarding the stability of the rutile phase using DFT XC-functionals more sophisticated than simple local-density approximation. Here the PBEsol generalized gradient approximation (GGA), TPSS meta-GGA, and HSE06 hybrid functionals have been employed to demonstrate the XC-functional effects on the calculated structural, phonon and thermodynamic properties of rutile and anatase TiO2. Lattice and elastic parameters correctly calculated with these XC-functionals show good agreement with the experimental values. Calculated phonon frequencies generated stable phonon dispersion relations for both rutile and anatase TiO2 when correctly converged, in agreement with the experimental observations. The phonon frequencies along high symmetry Brillouin zone paths and their corresponding phonon density of states showed sensitivity to different levels of XC-functional employed in phonon dispersion prediction. Nevertheless, the thermodynamic properties of rutile and anatase TiO2 estimated by harmonic approximations are in excellent experimental agreement and are effectively invariant to the level of theory employed in the DFT XC-functional.
Application of chaotic colony predation algorithm in electromagnetics
Authors: Hu Kui , Liu Yan , Zhao KunXia
Published: September 2023

The colony predation algorithm (CPA) is a new meta-heuristic algorithm that mimics the predation of animals to improve the radiation properties of antenna arrays. To overcome CPA’s problems of low accuracy and fast convergence, we propose an improved CPA called the chaotic colony predation algorithm (CCPA). The performance of CCPA was investigated in three parts. First, CCPA was tested with four benchmark functions. Then, CCPA was applied to equally spaced linear arrays to suppress the peak side-lobe level (PSLL) and place nulls in the desired directions. Finally, CCPA was used for a pattern synthesis of equally spaced linear arrays to reduce the PSLL under various constraints. Our results show that CCPA performed competitively with other well-known algorithms. Thus, CCPA is a promising option for solving electromagnetic optimization problems.
Terahertz emission with remarkable efficiency through spherical nanoparticles using dark-hollow-Gaussian beams
Authors: Malik Hitendra K , Sharma Dimple
Published: September 2023

Simultaneous tuning of Terahertz (THz) radiation with respect to its frequency, power and focus is still a challenge for the scientific community, because of which its use is lacking in several areas. To achieve such properties, the present work proposes monodisperse graphite nanoparticles (NPs) of spherical shape dispersed in two orthogonal directions with normal vector of their basal planes parallel and perpendicular to the electric field of the dark-hollow-Gaussian beams (DHGBs) used for the generation of THz radiation. The NPs are impinged upon by two DHGBs of slightly different frequencies, which exert a ponderomotive force on the conduction electrons of the NPs. The motion of these electrons under the action of high intensity laser beams constitutes a macroscopic nonlinear current that produces the THz radiation. The well-structured THz emission occurs with the efficiency reaching 10−2 when the NPs resonate with the beating frequency, and they are arranged in their parallel orientations with respect to the electric field of the lasers. The proposal and the obtained results will contribute to the THz science and technology along with their use in medical science and THz time-domain spectroscopy.
NeuSort: an automatic adaptive spike sorting approach with neuromorphic models
Authors: Yu Hang , Qi Yu , Pan Gang
Published: September 2023

Objective. Spike sorting, a critical step in neural data processing, aims to classify spiking events from single electrode recordings based on different waveforms. This study aims to develop a novel online spike sorter, NeuSort, using neuromorphic models, with the ability to adaptively adjust to changes in neural signals, including waveform deformations and the appearance of new neurons. Approach. NeuSort leverages a neuromorphic model to emulate template-matching processes. This model incorporates plasticity learning mechanisms inspired by biological neural systems, facilitating real-time adjustments to online parameters. Results. Experimental findings demonstrate NeuSort’s ability to track neuron activities amidst waveform deformations and identify new neurons in real-time. NeuSort excels in handling non-stationary neural signals, significantly enhancing its applicability for long-term spike sorting tasks. Moreover, its implementation on neuromorphic chips guarantees ultra-low energy consumption during computation. Significance. NeuSort caters to the demand for real-time spike sorting in brain-machine interfaces through a neuromorphic approach. Its unsupervised, automated spike sorting process makes it a plug-and-play solution for online spike sorting.
Plant-inspired rearrangement of liquid in a porous structure for controlled swelling
Authors: Sarokin Yauheni , Aabloo Alvo , Must Indrek
Published: September 2023

Soft robots can adapt to dynamic environments without prior knowledge of their properties. Plants inspire mechanisms for counterbalancing dynamic loads by locally modulating compliance through anisotropic humidity-responsive materials and structures. In addition to well-known passive bilayers, plants may also actively control swelling. The combination of robust hygroscopic material-level response and simple electrical control makes active swelling particularly attractive for technological implementation. However, dynamic swelling demands the development and optimisation of congruent pumping solutions. This work suggests electrohydrodynamic pumping, enabled by highly reversible ion immobilisation at capacitive electrodes, as a particularly suitable low-pressure, high-area liquid displacement solution for active swelling. Local pore fill ratio (PFR) modulation is used as a measure for dynamic liquid displacement and swelling. A method for highly localised (10 μm membrane thickness) assessment of the dynamic variation of PFR in a 400 μm laminate undergoing cross-plane electrokinetic liquid displacement is developed. Two modes for transient PFR modulation were identified: electrokinetic ion transfer and diffusive solvent redistribution, pronounced at high and low voltage scan rates, respectively. The strategic combination of these modes enables various compliance-modulation scenarios. The system contains (within a cycle) a constant amount of liquid in an open network of liquid-filled pores. 30%–75% PFR yielded the highest dynamic PFR modulation: a high amount of empty pores is beneficial, yet a too-low PFR compromises the continuous liquid pathway necessary for electrokinetic pumping. The dynamic nature of internal liquid rearrangement was characterised by relatively fast electrokinetics-driven fluxes (6.3% PFR change in 80 s), followed by a slow equilibration of concentration and PFR. At high scan rates, PFR decreased at positive polarisation, while both positive and negative polarity yielded a similar decrease at low scan rates (5 mV s−1). Localised control over the swelling gradient enables the design of systems that morphologically adapt to complex dynamic loading conditions.
Double-layered blood vessels over 3 mm in diameter extruded by the inverse-gravity technique
Authors: Duong Van Thuy , Nguyen Chanh Trung , Phan Huu Lam , Le Van Phu , Dang Thao Thi , Choi Cholong , Seo Jongmo , Cha Chaenyung , Back Sung Hoon , Koo Kyo-in
Published: September 2023

One of the most promising techniques for treating severe peripheral artery disease is the use of cellular tissue-engineered vascular grafts (TEVGs). This study proposes an inverse-gravity (IG) extrusion technique for creating long double-layered cellular TEVGs with diameters over 3 mm. A three-layered coaxial laminar hydrogel flow in an 8 mm-diameter pipe was realised simply by changing the extrusion direction of the hydrogel from being aligned with the direction of gravity to against it. This technique produced an extruded mixture of human aortic smooth muscle cells (HASMCs) and type-I collagen as a tubular structure with an inner diameter of 3.5 mm. After a 21 day maturation period, the maximal burst pressure, longitudinal breaking force, and circumferential breaking force of the HASMC TEVG were 416 mmHg, 0.69 N, and 0.89 N, respectively. The HASMC TEVG was endothelialised with human umbilical vein endothelial cells to form a tunica intima that simulated human vessels. Besides subcutaneous implantability on mice, the double-layered blood vessels showed a considerably lower adherence of platelets and red blood cells once exposed to heparinised mouse blood and were considered nonhaemolytic. The proposed IG extrusion technique can be applied in various fields requiring multilayered materials with large diameters.
Investigating the microstructure and mechanical properties of deposited metal with ENiCrFe-7 covered electrode
Authors: Zhu Haiyang , Yu Wei , Liu Kun , Weng Xiang , Li Xiaobing , Xu Changzheng , Zou Jiasheng
Published: September 2023

The effect of post weld heat treatment (PWHT) on microstructure and mechanical properties of deposited metal using ENiCrFe-7 covered electrode was investigated. The PWHT was conducted at 615 °C for 24 h. The results showed that three types of precipitates existed in both as-welded and PWHT deposited metals, i.e., NbC carbides, Al-Ti oxides in grains, and M23C6 carbides on grain boundaries. The M23C6 carbides coarsened after PWHT. The room temperature and elevated temperature (350 °C) tensile strength decreased by about 30 MPa, and elongation increased by about 3%–4% after PWHT. The tensile specimens presented ductile fracture feature and the dimples in PWHT condition were larger than that in as-welded condition. The hardness of deposited metal in as-welded condition was higher than that of PWHT condition. The impact toughness showed no significant change after PWHT. Both as-welded and PWHT impact specimens showed a mixed fracture mode with dominant ductile fracture and cleavage fracture.
Prediction of age-hardening behaviour of LM4 and its composites using artificial neural networks
Authors: Gowrishankar M C , Doddapaneni Srinivas , Sharma Sathyashankara , Hegde Ananda , Shettar Manjunath , Karthik B M
Published: September 2023

This research work highlights the prediction of hardness behaviour of age-hardened LM4 and its composites fabricated using a two-stage stir casting method with TiB2 and Si3N4. MATLAB - Artificial Neural Networks is used to predict the age-hardening behaviour of LM4 and its composites. Experiments (hardness and tensile tests) are conducted to collect data for training an ANN model as well as to investigate the effect of reinforcements and age-hardening treatment on LM4 and its composites. The results show that with an increment in the reinforcement wt%, there is an enhancement in hardness and ultimate tensile strength (UTS) values within the monolithic composites. As-cast hybrid composites display a 37 to 54% improvement in hardness compared to as-cast LM4. Heat-treated samples, specifically those treated with peak aging with MSHT and 100 °C aging, perform better than as-cast samples and other heat-treated samples in terms of UTS and hardness. Compared to as-cast LM4, MSHT, and 100 °C aged samples display an 85 to 202% increment in VHN. Hybrid composites perform better in terms of hardness, while composites with 3 wt% of TiB2 (L3TB) perform better in terms of UTS, peak aged (MSHT and 100 °C aging) L3TB display 68% increment in UTS when compared to as-cast LM4. ANN model is developed and trained with five inputs (wt% of TiB2, wt% of Si3N4, type of solutionizing, aging temperature, and aging time) and one output (VHN) using different algorithms and a different number of hidden neurons to predict the age hardening behaviour of composites. Among them, Lavenberg-Marquardt (LM) training algorithm with normalized data and 30 hidden neurons performs well and shows a least average error of 1.588364. The confirmation test confirms that the trained ANN model can predict the output with an average %error of 0.14 using unseen data.
Study on macro performance and micro-analysis of high strength grouting material
Authors: Shu Benan , Zeng Guodong , Zhou Min , Li Yongling , Ren Yanfei , Yang Tengyu , Qiu Keyi
Published: September 2023

Wind turbine duct put forward higher requirements for the performance of grouting materials. In order to obtain more economical high strength grouting materials (HSG), three kinds of low price main components, cement, quartz sand (QS) and fly ash microspheres (MS) were utilized and developed. Macro performance and micro-analysis of the HSG were conducted. The macro performance tests revealed that the mix proportion of HSG is determined as, cement: QS: MS: superplasticizer: swelling agent = 80:10:10:0.3:0.12, water binder ratio is determined as 0.26. Compressive and flexural strength of the HSG exceeding 120 MPa and 20 MPa respectively. The HSG also showed good fluidity and homogeneity. The micro-analysis showed that a complete and continuous micro-structure was formed and interface transition zone could not be observed. XRD and TG-DSC results meant that the amount of AFt increased. On the contrary, the amount of Ca(OH)2 decreased. pore diameter of the HSG was mostly 10 nm. The addition of swelling agent and MS did not changed the types of hydration products of HSG, but the pore structure was optimized. Due to the cheap components, HSG contributed higher profits with the lower price, and which perform good economic benefits and market competitiveness.
Designing for strength: enhancing mechanical performance through structured patterns in 3D printed elastomer
Authors: Zou Yuxin , Song Yating , Liu Xuan
Published: September 2023

The mechanical performance of 3D printed elastomers is a crucial factor for their successful utilization in various applications, including soft robotics, wearable devices, and biomedical engineering. This study focuses on investigating the influence of different structured patterns, namely vertical and crosswise vertical SC, on the strength and mechanical performance of 3D printed elastomers. Through a series of experimental tests and numerical simulations, it was found that the cross-shaped structure exhibited the best strength among the tested patterns. This enhanced performance can be attributed to the unique arrangement of the crosswise structure, which effectively distributes stress and reduces strain concentration. This study provide valuable insights into the design and fabrication of high-performance 3D printed elastomers, paving the way for the development of advanced materials and devices with enhanced mechanical properties.