bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of elevated dodecane jets in crossflow at supercritical pressure
Authors: Ding Siyu , Li Jiabin , Wang Xingjian
Published: July 2024

In advanced aero-engines, kerosene is often transversely injected into the combustor at supercritical pressure, where the shorter jet penetration depth may result in poor mixing and the local hot spots near the combustor wall. Elevating the jet nozzle is proposed to remedy these issues, where the flowfield complexity increases as a result of the intricate interactions among the jet, crossflow, and stack wake. The distinct flow dynamics of elevated dodecane jets in crossflow (EJICF) at supercritical pressure are numerically investigated using large eddy simulation. The effects of various parameters, including ambient pressure, elevation stack thickness, and stack height are studied. The results reveal that, the jet-wake recirculation bubble is prominently evident at low supercritical pressure, attributed to the strong real-fluid effect resulting from significant density stratification in the jet's upstream shear layer. Analysis of streamline patterns and vorticity budgets underscores the role of the real-fluid effect in delaying the shift of the flow pattern from the transitional regime to the jet-dominated regime. Increasing stack thickness mitigates the impact of jet upshear effects and has the potential to eliminate the lock-in phenomena between jet wake and stack wake. A reduction in stack height leads to the diminishment of the stack wake vortex shedding. In contrast to conventional JICF, the EJICF configuration exhibits a heightened tendency for recirculation bubble formation in the jet wake region. An analysis of spatial mixing deficiencies demonstrates that incorporating an elevation stack with proper thickness and height can dramatically improve the jet-crossflow mixing efficiency.
Phase stability, piezoelectricity, and ferroelectricity in nitride short-period superlattices
Authors: Zhao Ling-Xu , Liu Jian
Published: July 2024

Improving piezoelectric and ferroelectric responses of group III-nitrides is desired for their potential applications in the emerging microelectromechanical-based systems. One possible approach to realize the optimization and control of functionalities is to bring together compounds with different properties to form the ordered multilayer superlattices. In this work, we systematically investigate the phase stability, piezoelectricity, and ferroelectricity in a class of wurtzite-structure-derived nitride superlattices with a periodic alternation of chemically and/or structurally different layers. The structural heterogeneity and phase stability of the ordered wurtzite-structure-derived superlattices are intimately related to the ionic radii mismatch between the substitutional compounds and the parent nitrides. Moreover, the internal structural distortion of the nitride superlattices has a crucial impact on the ferroelectricity and piezoelectricity, namely, piezoelectric and ferroelectric responses become increasingly enhanced as the buckled atomic layers becomes flatter. This work offers fundamental physical insights into the structure–property relationships in nitride superlattices and may propose some material design strategies for achieving high-performance materials with desired responses.
A methodology of quantifying membrane permeability based on returning probability theory and molecular dynamics simulation
Authors: Matsubara Yuya , Okabe Ryo , Masayama Ren , Watanabe Nozomi Morishita , Umakoshi Hiroshi , Kasahara Kento , Matubayasi Nobuyuki
Published: July 2024

We propose a theoretical approach to estimate the permeability coefficients of substrates (permeants) for crossing membranes from donor (D) phase to acceptor (A) phase by means of molecular dynamics (MD) simulation. A fundamental aspect of our approach involves reformulating the returning probability (RP) theory, a rigorous bimolecular reaction theory, to describe permeation phenomena. This reformulation relies on the parallelism between permeation and bimolecular reaction processes. In the present method, the permeability coefficient is represented in terms of the thermodynamic and kinetic quantities for the reactive (R) phase that exists within the inner region of a membrane. One can evaluate these quantities using multiple MD trajectories starting from phase R. We apply the RP theory to the permeation of ethanol and methylamine at different concentrations (infinitely dilute and 1 mol % conditions of permeants). Under the 1 mol% condition, the present method yields a larger permeability coefficient for ethanol (0.12 ± 0.01 cm s−1) than for methylamine (0.069 ± 0.006 cm s−1), while the values of the permeability coefficient are satisfactorily close to those obtained from the brute-force MD simulations (0.18 ± 0.03 and 0.052 ± 0.005 cm s−1 for ethanol and methylamine, respectively). Moreover, upon analyzing the thermodynamic and kinetic contributions to the permeability, we clarify that a higher concentration dependency of permeability for ethanol, as compared to methylamine, arises from the sensitive nature of ethanol’s free-energy barrier within the inner region of the membrane against ethanol concentration.
Fano resonances in dielectric metasurfaces with hemispherical voids: Effect on the optical Kerr nonlinearity
Authors: Panov Andrey V.
Published: July 2024

The optical behavior of the square lattices of the hemispherical nanovoids on the surface of the high-refractive-index all-dielectric slabs in the visible range is studied numerically using gallium phosphide as an example. There exist Fano resonances for these metasurfaces for a limited range of thicknesses. The Fano resonances are caused by the interference between the Mie-type scattering resonances of surface pattern elements and the Fabry–Pérot modes of the slabs. The maximum enhancements of the optical Kerr nonlinearity with respect to the bulk material are revealed at the Fano resonances, in particular, for the thinnest nanostructures. Interestingly, no positive correlation between the quality factor and the enhancement of the optical Kerr effect of the metasurface at the Fano resonances is observed.
Determination of light-independent shunt resistance in CIGS photovoltaic cells using a collection function-based model
Authors: El Khoury M. , Moret M. , Tiberj A. , Desrat W.
Published: July 2024

Shunt resistance Rsh is a critical parameter for photovoltaic cells designed for low light indoor applications because it negatively affects the open circuit voltage, fill factor, and conversion efficiency. Standard CIGS cells are known to have low Rsh and are, therefore, unpromising candidates for indoor energy sources. In this paper, we extend the original work of Virtuani et al. by determining the electrical specifications of many CIGS cells with copper contents [Cu]/([Ga]+[In]) as low as 0.33 and gallium contents between 0.28 and 0.81. First, IV data are fitted by a standard single-diode electrical circuit model for each illumination, resulting in light-dependent parameters. Then, we use a procedure based on a single dataset of electrical variables, i.e., independent of light, corrected by the experimental collection function, which captures light-dependent physical mechanisms. In this way, we are able to correctly reproduce the illuminance dependence of the electrical response of the PV cell over three orders of magnitude, in particular with a fixed value of the shunt resistance. The highest Rsh is obtained with a low copper composition of 0.5, regardless of the gallium composition.
Healing gradient degradation in Nb3Sn SRF cavities using a recoating method
Authors: Viklund Eric , Seidman David N. , Posen Sam , Tennis Brad M. , Eremeev Grigory
Published: July 2024

Despite having advantageous superconducting properties, Nb3Sn superconducting radiofrequency (SRF) cavities still have practical challenges compared to Nb SRF cavities due to the brittle nature of Nb3Sn. Performance degradation can occur when an Nb3Sn SRF cavity experiences mechanical stresses, such as during handling and tuning of the cavity. In this study, we present a potential treatment for SRF cavities that have experienced stress-induced performance degradation that involves a recoating procedure. The degraded cavity is coated with a small amount of Sn using a single-step vapor-diffusion methodology. Using this approach, we can recover a significant portion of the lost performance of the Nb3Sn SRF cavity.
Electron cyclotron emission detection of neoclassical tearing modes for control for ITER
Authors: Ziegel J. P. , Rowan W. L. , Waelbroeck F. L.
Published: July 2024

Successful operation of ITER requires control of magnetic instabilities including neoclassical tearing modes (NTMs) that can degrade confinement and lead to disruption. Low latency detection by electron cyclotron emission (ECE) diagnostics has been demonstrated in a few current experiments. Using a synthetic diagnostic, we demonstrate low latency NTM detection for ITER with plasmas described by ITER IMAS database scenarios and with realistic limitations imposed on the instrumentation by these high temperature scenarios. 2/1 NTMs are detected 430 ms after magnetic island seeding and before island locking. The radiometer configuration was optimized using simulation, and the smallest detectable island size was explored. Island sizes of ∼3 cm are detectable at the 2/1 surface. The simulated signals incorporate recent physics models for island growth and rotation, which show early locking and continued island growth after locking and before disruption. This work determines limits for ITER ECE spatial resolution imposed by relativistic broadening of channels, which informs hardware design. Real-time detection is demonstrated in hardware that is required by ITER, including on an NI PXI-7853R FPGA system. Development of a synthetic diagnostic and details of the hardware will be discussed.
Fully appreciating the impossibility of shock wave regular reflection from the axis of symmetry in axisymmetric internal flows
Authors: Zhang Tao , Hu Waner , Da Xingya , Shi Chongguang , Zhu Chengxiang , You Yancheng
Published: July 2024

This study investigates the reflection of shock waves in internal axisymmetric flows and conclusively shows that regular reflection cannot occur over the axis of symmetry. The analysis employs the curved shock theory to examine flow gradients behind the axisymmetric shock. The curved shock equations are presented in explicit form using influence coefficients, which establish a direct relation between flow gradients in polar coordinates and shock curvatures. The gradient information reveals that the flow behind the incident shock around the reflection point is governed by the Taylor–Maccoll equation, indicating that the flow pattern is locally conical. By analyzing the singularity of internal conical flows, the only possible structure of conical shock reflection with a smooth singularity is constructed. After a thorough theoretical analysis of this conical shock reflection structure, the study concludes with definitive proof that this specific flow pattern cannot occur in practical applications because it requires the incident shock angle to be less than the freestream Mach angle. This suggests that regular reflection is impossible to occur over the axis of symmetry in internal axisymmetric flows.
Using detection dogs for surveillance of invasive dama wallaby (Notamacropus eugenii) in North Island, New Zealand
Authors: Latham A. David M. , Latham M. Cecilia , Peace Jo , Gormley Andrew M.
Published: July 2024

Context Dama wallabies (Notamacropus eugenii) were introduced into the Bay of Plenty Region, New Zealand, in the early 1900s. They subsequently became an invasive pest, damaging pasture, silviculture, and native vegetation. One key management strategy is the eradication of isolated populations. Aims First, we empirically determined the detection probabilities of detection dogs and handlers searching for faecal pellet groups of dama wallaby in pasture and forested habitats. Second, we used detection probabilities to derive surveillance system sensitivity (SSe) and estimate the cost per hectare required to have a high confidence (95%) that a targeted wallaby population has been eradicated. Methods We collected and deployed faecal pellet groups in an area with no naturally occurring wallabies. Following faecal pellet surveys by detection dogs and handlers, we estimated the probability of a dog–handler team detecting a pellet group and derived SSe. We derived SSe for a single faecal pellet group and, using simulation, upscaled this estimate to multiple pellet groups voided by a single surviving individual. Key results The detection probability of dogs searching for a single faecal pellet group that was within the detection swathe was relatively high (minimum of 45%). Scaling this instantaneous probability of detection for a single pellet group to the multiple pellet groups voided by a single wallaby around its home range resulted in 30–33-fold increases in SSe compared to the sensitivity of searching for a single faecal pellet group. The costs of surveillance for confirming eradication using detection dogs and handlers are NZ$54–NZ$72 for a 100-ha area. Conclusions Detection dogs and handlers are an efficacious and cost-effective surveillance method for confirming eradication of dama wallaby in open and forested habitats. Implications Detection dogs and handlers are an important surveillance tool for the management of wallabies in New Zealand. The data from this study enable managers to determine the required surveillance effort to have high confidence (e.g. 0.95) that a wallaby population has been eradicated, or that a suspected new population is actually absent if no wallabies are detected. Additionally, it enables per hectare costs of surveillance to be estimated and compared to alternative methods.
Capture rates of highly degenerate neutrons
Authors: Knight B , Caballero O L , Schatz H
Published: July 2024

At the low temperature and high density conditions of a neutron star crust neutrons are degenerate. In this work, we study the effect of this degeneracy on the capture rates of neutrons on neutron rich nuclei in accreted crusts. We use a statistical Hauser–Feshbach model to calculate neutron capture rates and find that neutron degeneracy can increase rates significantly. Changes increase from a factor of a few to many orders of magnitude near the neutron drip line. We also quantify uncertainties due to model inputs for masses, γ-strength functions, and level densities. We find that uncertainties increase dramatically away from stability and that degeneracy tends to increase these uncertainties further, except for cases near the neutron drip line where degeneracy leads to more robustness. As in the case of capture of classically distributed neutrons, variations in the mass model have the strongest impact. Corresponding variations in the reaction rates can be as high as 3–4 orders of magnitude, and be more than 5 times larger than under classical conditions. To ease the incorporation of neutron degeneracy in nucleosynthesis networks, we provide tabulated results of capture rates as well as analytical expressions as function of temperature and neutron chemical potential, for proton numbers between 3 ≤ Z ≤ 85, derived from fits to our numerical results. Fits are based on a new parametrization that complements previously employed power law approximations with additional Lorentzian terms that account for low energy resonances, significantly improving accuracy.
Verification and validation of electrostatic turbulence simulation for numerical Lie transform code
Authors: Yang N , Wang J Q , Liu D J , Ye L , Qu H P , Wang F , Zhao P F , Wang G X
Published: July 2024

This paper reports the verification and validation of a new gyrokinetic (GK) code, numerical Lie transform (NLT), for electrostatic turbulence simulation in tokamak plasmas. Based on the standard cyclone base case (CBC), NLT has been verified against two typical GK codes, GK toroidal code (GTC) and GK numerical experiment of tokamak, by simulating the ion temperature gradient mode and trapped electron mode. The linear dispersion relation and mode structure agree well among all these codes. In nonlinear simulation, the time evolution of ion heat diffusivity obtained from NLT is consistent with the GTC results. Furthermore, utilizing experimental equilibria with obvious turbulence features from HL-2A shot #22388, the validation of NLT for real tokamak simulation has been carried out. The profiles of ion turbulent thermal diffusivity calculated by NLT match well with experimental results.
Identification of combined sensor faults in structural health monitoring systems
Authors: Al-Nasser Heba , Al-Zuriqat Thamer , Dragos Kosmas , Geck Carlos Chillón , Smarsly Kay
Published: July 2024

Fault diagnosis (FD), comprising fault detection, isolation, identification and accommodation, enables structural health monitoring (SHM) systems to operate reliably by allowing timely rectification of sensor faults that may cause data corruption or loss. Although sensor fault identification is scarce in FD of SHM systems, recent FD methods have included fault identification assuming one sensor fault at a time. However, real-world SHM systems may include combined faults that simultaneously affect individual sensors. This paper presents a methodology for identifying combined sensor faults occurring simultaneously in individual sensors. To improve the quality of FD and comprehend the causes leading to sensor faults, the identification of combined sensor faults (ICSF) methodology is based on a formal classification of the types of combined sensor faults. Specifically, the ICSF methodology builds upon long short-term memory (LSTM) networks, i.e. a type of recurrent neural networks, used for classifying ‘sequences’, such as sets of acceleration measurements. The ICSF methodology is validated using real-world acceleration measurements from an SHM system installed on a bridge, demonstrating the capability of the LSTM networks in identifying combined sensor faults, thus improving the quality of FD in SHM systems. Future research aims to decentralize the ICSF methodology and to reformulate the classification models in a mathematical form with an explanation interface, using explainable artificial intelligence, for increased transparency.
Air quality prediction based on improved quantum long short-term memory neural networks
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Authors: Li Feifei , Dong Yumin
Published: July 2024

Accurate prediction of urban air quality is of vital importance in preventing urban air pollution and improving the quality of life of urban residents. In order to achieve more accurate prediction of air quality, this study proposes a novel hybrid quantum neural network prediction model that combines an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and a quantum long short-term memory network (QLSTM) optimized by the particle swarm optimization (PSO) algorithm.This study focuses on using the QLSTM model to mine the time-real fluctuations and historical dependence of air quality data and applying the PSO algorithm to optimize the hyper-parameters of the quantum model to improve the prediction accuracy; then, ICEEMDAN is introduced to disassemble the original air quality data series into multiple pattern components containing different information, which effectively reduces the complexity of the data; the feasibility and validity of the proposed methodology are verified through comparison experiments with other prediction modeling methods. The results show that the proposed QLSTM prediction method incorporating ICEEMDAN and PSO optimization has the highest prediction accuracy in terms of prediction accuracy, which contributes a novel and quantum-specific technical approach to the field of air quality prediction.
Dynamics, periodic orbits of a novel four-dimensional hyperchaotic system with hidden attractors
Authors: Wei Dianshuang , Dong Chengwei
Published: July 2024

In recent years, the investigation of systems featuring hidden attractors and coexisting attractors has garnered significant attention. This paper presents a novel four-dimensional (4D) hyperchaotic system devoid of equilibrium points, achieved by formulating an equation without a solution or constructing a system without fixed points. Due to the complex shape of this attractor, a novel coding method is utilized to establish symbol dynamics using eight letters. The proposed system exhibits highly intricate dynamics, including variations in topological structure with alterations in system parameters, as well as an exploration and discussion of four types of coexisting attractors. Our extensive practice has led us to propose a new conjecture: hyperchaotic systems with parameters close to the bifurcation point frequently display multistable states. Furthermore, the unstable periodic orbits with different topological lengths in the hidden hyperchaotic attractor are calculated systematically using the variational method. Additionally, the DSP circuit implementation is employed to validate the numerical simulation results for this new 4D system. Finally, adaptive synchronization is successfully realized within the system, thereby confirming its feasibility.
Modelling and numerical simulation of sequencing strategies for connected and autonomous vehicles at signal-free intersections
Authors: Zhang Jiaqi , Yang Qiaoli
Published: July 2024

The signal-free intersections employ connected and automated vehicle technology to manage vehicles passing through the intersection. Due to conflicting traffic flows in opposition directions, a proper sequencing of Connected and Autonomous Vehicles (CAVs) at signal-free intersections becomes critical to impacting intersection traffic performance. Based on an examination of CAV queueing rules under the most common sequencing strategies of First-Come-First-Serve (FCFS) and Longest-Queue-First (LQF), commonly employed as benchmarks for evaluating diverse innovative approaches to signal-free intersections, we propose a Dynamic-Queue-Service (DQS) strategy that is tailored to accommodate high traffic demand. To explicitly elucidate the impact of diverse traffic demand in conflicting directions on the queue uncertainty and stochasticity of CAVs, as well as to investigate how various sequencing strategies influence the equity of CAV traffic at signal-free intersections with regard to CAV queueing dynamics under different strategies, we have developed a double-input traffic queueing model and derived a range of metrics, including the queue length, delay, conditional queue length, and variance of queue length. In addition, for the three strategies, we performed a series of numerical simulations to investigate the queueing process of CAVs at signal-free intersections. Numerical results show that under different levels of traffic demand in the conflicting directions, the FCFS, LQF, and DQS strategies output diverse traffic queueing performances, and the DQS strategy is confirmed to be well-suited for the situation of high traffic demand in both conflicting directions.
Controlled fabrication of freestanding monolayer SiC by electron irradiation
Authors: Da 笪 Yunli 蕴力 , Luo 罗 Ruichun 瑞春 , Lei 雷 Bao 宝 , Ji 季 Wei 威 , Zhou 周 Wu 武
Published: July 2024

The design and preparation of novel quantum materials with atomic precision are crucial for exploring new physics and for device applications. Electron irradiation has been demonstrated as an effective method for preparing novel quantum materials and quantum structures that could be challenging to obtain otherwise. It features the advantages of precise control over the patterning of such new materials and their integration with other materials with different functionalities. Here, we present a new strategy for fabricating freestanding monolayer SiC within nanopores of a graphene membrane. By regulating the energy of the incident electron beam and the in-situ heating temperature in a scanning transmission electron microscope (STEM), we can effectively control the patterning of nanopores and subsequent growth of monolayer SiC within the graphene lattice. The resultant SiC monolayers seamlessly connect with the graphene lattice, forming a planar structure distinct by a wide direct bandgap. Our in-situ STEM observations further uncover that the growth of monolayer SiC within the graphene nanopore is driven by a combination of bond rotation and atom extrusion, providing new insights into the atom-by-atom self-assembly of freestanding two-dimensional (2D) monolayers.
MRGazer: decoding eye gaze points from functional magnetic resonance imaging in individual space
Authors: Wu Xiuwen , Hu Rongjie , Liang Jie , Wang Yanming , Qiu Bensheng , Wang Xiaoxiao
Published: July 2024

Objective. Eye-tracking research has proven valuable in understanding numerous cognitive functions. Recently, Frey et al provided an exciting deep learning method for learning eye movements from functional magnetic resonance imaging (fMRI) data. It employed the multi-step co-registration of fMRI into the group template to obtain eyeball signal, and thus required additional templates and was time consuming. To resolve this issue, in this paper, we propose a framework named MRGazer for predicting eye gaze points from fMRI in individual space. Approach. The MRGazer consists of an eyeball extraction module and a residual network-based eye gaze prediction module. Compared to the previous method, the proposed framework skips the fMRI co-registration step, simplifies the processing protocol, and achieves end-to-end eye gaze regression. Main results. The proposed method achieved superior performance in eye fixation regression (Euclidean error, EE = 2.04°) than the co-registration-based method (EE = 2.89°), and delivered objective results within a shorter time (∼0.02 s volume−1) than prior method (∼0.3 s volume−1). Significance. The MRGazer is an efficient, simple, and accurate deep learning framework for predicting eye movement from fMRI data, and can be employed during fMRI scans in psychological and cognitive research. The code is available at https://github.com/ustc-bmec/MRGazer.
DP-MP: a novel cross-subject fatigue detection framework with DANN-based prototypical representation and mix-up pairwise learning
Authors: He Xiaopeng , Li Haoyu , Yu Peng , Wu Hao , Chen Badong
Published: July 2024

Abstract. Objective. Electroencephalography (EEG) is widely recognized as an effective method for detecting fatigue. However, practical applications of EEG for fatigue detection in real-world scenarios are often challenging, particularly in cases involving subjects not included in the training datasets, owing to bio-individual differences and noisy labels. This study aims to develop an effective framework for cross-subject fatigue detection by addressing these challenges. Approach. In this study, we propose a novel framework, termed DP-MP, for cross-subject fatigue detection, which utilizes a Domain-Adversarial Neural Network (DANN)-based prototypical representation in conjunction with Mix-up pairwise learning. Our proposed DP-MP framework aims to mitigate the impact of bio-individual differences by encoding fatigue-related semantic structures within EEG signals and exploring shared fatigue prototype features across individuals. Notably, to the best of our knowledge, this work is the first to conceptualize fatigue detection as a pairwise learning task, thereby effectively reducing the interference from noisy labels. Furthermore, we propose the Mix-up pairwise learning (MixPa) approach in the field of fatigue detection, which broadens the advantages of pairwise learning by introducing more diverse and informative relationships among samples. Results. Cross-subject experiments were conducted on two benchmark databases, SEED-VIG and FTEF, achieving state-of-the-art performance with average accuracies of 88.14% and 97.41%, respectively. These promising results demonstrate our model’s effectiveness and excellent generalization capability. Significance. This is the first time EEG-based fatigue detection has been conceptualized as a pairwise learning task, offering a novel perspective to this field. Moreover, our proposed DP-MP framework effectively tackles the challenges of bio-individual differences and noisy labels in the fatigue detection field and demonstrates superior performance. Our work provides valuable insights for future research, promoting the application of brain-computer interfaces for fatigue detection in real-world scenarios.
Gibbs measures for hardcore-solid-on-solid models on Cayley trees
Authors: Jahnel Benedikt , Rozikov Utkir
Published: July 2024

We investigate the finite-statep-solid-on-solid (p-SOS) model forp=∞on Cayley trees of orderk⩾2and establish a system of functional equations where each solution corresponds to a (splitting) Gibbs measure of the model. Our main result is that, for three states,k=2,3and increasing coupling strength, the number of translation-invariant Gibbs measures behaves as1→3→5→6→7. This phase diagram is qualitatively similar to the one observed for three-statep-SOS models withp > 0 and, in the case ofk = 2, we demonstrate that, on the level of the functional equations, the transitionp→∞is continuous.
On the acceptance of high carbon taxes in low- and middle-income countries: a conjoint survey experiment
Authors: Malerba Daniele , Never Babette , Fesenfeld Lukas , Fuhrmann-Riebel Hanna , Kuhn Sascha
Published: July 2024

Changing consumption patterns from growing middle-classes with consequent rising energy use and emissions in low- and middle-income countries (LMICs) present key challenges for the energy transition and climate change mitigation. Carbon taxes are an effective policy instrument to counter these developments, yet concerns about low public acceptability hinder their introduction. Here, we seek to fill a research gap and identify publicly acceptable carbon tax designs in LMICs. We provide novel evidence from three conjoint experiments with 2700 middle-class respondents in Ghana, Peru, and the Philippines. We show that overall, the majority in all three countries supports even high taxes of USD-PPP 75/tCO2 per year, irrespective of specific policy design features. The support for a very high tax rate is especially high if revenues are recycled for environmental purposes. Thus, governments in LMICs have political leeway to finance the transition to a low-carbon economy via carbon taxes. Moreover, revenue recycling for the poorest receives high support from important subgroups. These insights are crucial to achieving an effective, acceptable, and just carbon tax policy design.
Spermatogenesis in mouse testicular organoids with testis-specific architecture, improved germ cell survival and testosterone production
Authors: Richer Guillaume , Goyvaerts Cleo , Marchandise Lorna , Vanhaecke Tamara , Goossens Ellen , Baert Yoni
Published: July 2024

This study presents a biphasic approach to overcome the limitations of current testicular organoid (TO) cultures, including histological heterogeneity, germ cell loss and absence of spermatogenesis. Agarose microwells were utilized to create TOs from prepubertal C57BL/6 J testicular cells. First emphasis was on improving germ cell survival during the initial 2-week reorganization phase by comparing α-MEM + 10% knockout serum replacement (KSR) medium, known to support TO generation in mice, to three optimized media (1–3). Cell densities and culture dynamics were also tested to recreate histological resemblance to testes. After optimizing germ cell survival and cell organization, the effect of growth factors and immunomodulation through CD45+ immune cell depletion or dexamethasone (DEX) supplementation were assessed for enhancing spermatogenesis during the subsequent differentiation phase. Testicular cells self-reorganized into organoids resembling the testicular anatomical unit, characterized by one tubule-like structure surrounded by interstitium. Media 1–3 proved superior for organoid growth during the reorganization phase, with TOs in medium 3 exhibiting germ cell numbers (7.4% ± 4.8%) comparable to controls (9.3% ± 5.3%). Additionally, 37% ± 30% demonstrated organized histology from 32 × 103 cells under static conditions. Switching to α-MEM + 10% KSR during the differentiation phase increased formation efficiency to 85 ± 7%, along with elevated germ cell numbers, testosterone production (3.1 ± 0.9 ng ml−1) and generation of γ-H2AX+ spermatid-like cells (steps 8–11, 1.2% ± 2.2% of the total). Adding differentiation factors to the α-MEM increased spermatid-like cell numbers to 2.9% ± 5.9%, confirmed through positive staining for CREM, transition protein 1, and peanut agglutinin. Although, these remained diploid with irregular nuclear maturation. DEX supplementation had no additional effect, and immune cell depletion adversely impacted TO formation. The manipulability of TOs offers advantages in studying male infertility and exploring therapies, with scalability enabling high-throughput chemical screening and reducing animal usage in reproductive toxicity and drug discovery studies.
Quantitative and deep learning based fourier transform infrared radiation and tensile characteristics study on chemically treated hibiscus rosa-sinensis plant fibers
Authors: J P Supriya , Shetty Sawan , Shetty Raviraj , Nayak Rajesh , Maddasani Srinivasulu , Hegde Adithya
Published: July 2024

Incorporation of natural fibers with Fiber Reinforced Polymers (FRPs) is a promising avenue for sustainable and high-performance composite materials. The fibers, derived from outer bark portion of plants, offer significant merits such as renewability, low cost, and eco-friendly. Unique mechanical and physical properties, and widespread availability of Hibiscus Rosa-sinensis have made them subject of intense research interest. The present study investigated the chemically treatment of HRS Fibers using Sodium Hydroxide (NaOH), Potassium Permanganate (KMnO4), and Acetic Acid (CH3COOH) bat varying weight percentages (3, 4, 5 Wt%) and solutionizing times (1, 2, 3 h) based on Taguchi’s L27 orthogonal array. Fourier Transform Infrared (FT-IR) analysis revealed significant changes in O–H, C–H stretching, C=O moiety, aromatic ring, and C–O/C–C stretching. Potassium Permanganate treatment at 4 Wt% and 3 h of solutionizing time has yielded the best results. Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) has been successfully applied to accurately predict the output physical characteristics of chemically treated HRS fibers using experimental data. Further Single Fiber Pull-out test results in Potassium Permanganate at 4 Wt% and 3 h solutionizing time as best sample with highest Tensile Strength and Modulus. This research underscores the effectiveness of the chemical treatment process in enhancing the properties of HRS plant fibers for potential composite applications.
Edge and dense attention U-net for atrial scar segmentation in LGE-MRI
Authors: Li Gaoyuan , Liu Mingxin , Lu Jun , Ma Jiquan
Published: July 2024

The segmentation of atrial scars in LGE-MRI images has huge potential value for clinical diagnosis and subsequent treatment. In clinical practice, atrial scars are usually manually calibrated by experienced experts, which is time-consuming and prone to errors. However, automatic segmentation also faces difficulties due to myocardial scars’ small size and variable shape. The present study introduces a dual branch network, incorporating edge attention, and deep supervision strategy. Edge attention is introduced to fully utilize the spatial relationship between the scar and the atrium. Besides, dense attention is embedded in bottom layer to solve feature disappearance. At the same time, deep supervision accelerates the convergence of the model and improves segmentation accuracy. The experiments were conducted on the 2022 atrial and scar segmentation challenge dataset. The results demonstrate that the proposed method has achieved superior performance.
Stress tolerance activity and diversification of endophytic fungi from the medicinal plant Abutilon indicum
Authors: M Haseena , Arumugam Sabaridasan , Gopal Suresh , Salmen Saleh H , Aljawdah Hossam M , Munusamy Murugan A
Published: July 2024

This study aimed to assess the diversity of endophytic fungi isolated from Abutilon indicum using morphological and molecular techniques. The isolates were exposed to various levels of salinity, temperatures, and heavy metals, including Ag2+ and Zn2+, at concentrations of 3.6 and 11.5 mM. Thirty root segments were isolated from each plant and cultured on potato dextrose agar plates. Four endophytic fungi were randomly isolated from infected root segments, belonging to the genera Aspergillus, Meyerozyma, and Penicillium. The phylogenetic analysis revealed significant diversity among the isolates of Aspergillus welwitschiae, Aspergillus indologenus, Meyerozyma carpophila, and Penicillium citrinum, with a 99% similarity in their sequences. Most isolates were able to thrive under salt stress conditions at NaCl concentrations of 200 mM (26%), 400 mM (24%), 600 mM (21%), 800 mM (13%), and 1000 mM (16%). Tolerant to temperature, endophytes could survive in the range of 25 °C to 35 °C but could not survive above 50 °C. Heavy metals tolerance of 89% of these isolates led to a significant decrease in biomass production when exposed to Ag2+. Endophytic fungal isolates showed decreased sensitivity to Zn2+, but between 33% and 60% showed strong growth in conditions with high levels of Zn2+. These findings revealed that endophytic fungi of A. welwitschiae enhanced growth when exposed to various stress conditions. Our findings indicate that the presence of fungal endophytes in different stress conditions leads to significant growth, and this could be useful for phytoremediation purposes.
Where ideology meets private interest: the three-part composition of climate obstruction in the United States
Authors: Hall Galen , Loy Loredana , Brulle Robert J , Schell-Smith Kennedy , Hu Ming-May , Trollback Stina
Published: July 2024

A network of organizations working to oppose climate action, called the climate change countermovement (CCCM), has long been a critical yet highly opaque subject of study for social scientists concerned with climate politics. We leverage a new combined dataset of boards of directors, financial contributions, and texts produced by CCCM members to characterize its sources of support and social structure. We show that foundations tend to make more frequent and larger donations to CCCM nonprofits when they are linked through a board member. We also show that CCCM nonprofits which are more distant from each other in the social network of board members produce different climate change discourses. Community detection methods robustly detect three communities within the CCCM: conservative think tanks (CTT), oil and gas trade associations, and utility, coal, and manufacturing trade associations, each with unique goals within the countermovement. The findings suggest that the climate countermovement is an interface among these communities which together ensure that climate action obstruction is achieved on different but complementary fronts, through both discursive and more concrete policy efforts. This paper also introduces a new way of understanding organized climate obstruction and makes significant methodological contributions in the study of social movements and countermovements.
Indirect magneto-ionic effect in FeSi2/Si nanocomposite induced by electrochemical lithiation and delithiation
Authors: Prasch M , Würschum R , Topolovec S
Published: July 2024

A nanocomposite consisting of iron disilicide nanocrystals embedded in a Si matrix was prepared from industry-grade ferrosilicon by ball milling and subsequent heat treatment. By tailoring the heat treatment temperature either the metallic α-FeSi2 or the semiconducting β-FeSi2 phase could be made the dominant one, as indicated by x-ray diffraction. Magnetization curve and zero-field cooled/field cooled measurements revealed that ferromagnetic and superparamagnetic centers are present in the nanocomposites, which could be attributed to Fe-rich defective regions at the surface of the iron disilicide nanocrystals. For both nanocomposites, containing either mainly the α or β phase, we could show that the magnetization can be varied by about 40% by electrochemical lithiation and delithiation of the surrounding Si matrix, with up to 6.5% of the magnetization change being reversible. These variations could be attributed to the formation of additional Fe-rich magnetic regions, induced by a local change of the Fe/Si fraction at the FeSi2/Si interfaces, and their subsequent partial elimination. Thus, this work demonstrates a new concept for how an ‘indirect magneto-ionic effect’ can be obtained in composite materials consisting of a phase prone to the electrochemical ion uptake (i.e. the Si matrix) and a magnetic phase (i.e. the FeSi2 nanocrystals).
Optimal path planning using bidirectional rapidly-exploring random tree star-dynamic window approach (BRRT*-DWA) with adaptive Monte Carlo localization (AMCL) for mobile robot
Authors: Ayalew Wubshet , Menebo Muluken , Merga Chala , Negash Lebsework
Published: July 2024

Path planning is an important task for mobileF service robots. Most of the available path-planning algorithms are applicable only in static environments. Achieving path planning becomes a difficult task in an unknown, dynamic environment. To solve the path planning problem in an unknown dynamic environment, this paper proposes a Bidirectional Rapidly-exploring Random Tree Star-Dynamic Window Approach (BRRT*-DWA) algorithm with Adaptive Monte Carlo Localization (AMCL). Bidirectional Rapidly-exploring Random Tree Star(BRRT*) is used to generate an optimal global path plan, Dynamic Window Approach(DWA) is a local planner and Adaptive Monte Carlo Localization(AMCL) is used as a localization technique. The robot can navigate using the map file of the unknown environment created by Simultaneous Localization And Mapping (SLAM) and the data from the Light Detection and Ranging (LiDAR) sensor while avoiding dynamic and static obstacles. In addition, the object identification algorithm You Only Look Once (YOLO) was adopted, trained, and used for the robot to recognize objects and people. Results obtained from both simulation and experiment show the proposed method can achieve better performance in a dynamic environment compared with other state-of-the-art algorithms.
Nitrogen-vacancy centers in diamond: discovery of additional electronic states
Authors: Luu Minh Tuan , Tayefeh Younesi Ali , Ulbricht Ronald
Published: July 2024

Nitrogen-vacancy (NV) defect centers in diamond are key to applications in quantum sensing and quantum computing. They create localized electronic states in the diamond lattice with distinct population relaxation pathways following photoexcitation that ultimately enable its unique properties. The defect is known to exist in two charge states: neutral and negative, with respectively one and two known optically-active electronic transitions. Here, we report on the observation of a large number of hitherto undiscovered excited electronic states in both charge states as evidenced by distinct optical transitions in the infrared to ultraviolet part of the spectrum. These transitions are observed by monitoring the electronic relaxation of NV centers after photoexcitation using transient absorption spectroscopy, directly probing transient phenomena occurring on timescales from femtoseconds to microseconds. We also for the first time probed the electron transfer dynamics from the

3

E

state of NV− to nearby single-substitutional nitrogen defects (N

s

) that leads to the well-known effect of NV photoluminescence quenching.
Rhodian Associations and Religious Experience
Authors: Zachhuber Juliane
Published: July 2024

This chapter moves away from the overwhelmingly civic focus of the previous sections and examines the lively world of Rhodian associations. Although these are often named after gods, their religious activities are little known. Building on their naming conventions, the chapter compares the religious tastes and cultic affiliations of these groups against the backdrop of Rhodian religion, as established in the rest of the book. Religious spaces and festivals allow an insight into the intersection between public and private religious experience, leading us to question the usefulness of this distinction. Finally, the chapter looks at the religious models these associations might offer for other spheres of Rhodian life, in particular the navy, and to what extent these spaces offered access to new religious experiences (such as initiation).
Concluding Remarks: Themes in Rhodian Religion
Authors: Zachhuber Juliane
Published: July 2024

The conclusion reflects on the value of local religious studies, and points to several themes that have emerged from the book that have a bearing on our broader understanding of Greek and Hellenistic religion. In turn, it considers how Rhodian religion informs us on the following themes: ‘polis religion’, epigraphic memory and sacred space, gender and religion, the sea and religion, and finally Hellenistic religion. An overarching conclusion is that this study of Rhodian religion in the Hellenistic period illustrates the continued vitality of polytheism, against the common perception of trends moving in the opposite direction. Other religious aesthetics can be seen to fit the Hellenistic mould better, albeit with their own idiosyncrasies.
Pattern of heterogeneity in normal brain ageing: screening for mild cognitive impairment and its risk of progression with a radiomics model
Authors: Yan Yuting , He Xiaodong , Xu Yuyun , Zhao Fanfan , Peng Jiaxuan , Shao Yuan
Published: July 2024

Purpose

This study aimed to develop a normal brain ageing model based on magnetic resonance imaging and radiomics, therefore identifying radscore, an imaging indicator representing white matter heterogeneity and exploring the significance of radscore in detecting people’s cognitive changes.

Methods

Three hundred sixty cognitively normal (CN) subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database and 105 CN subjects from the Parkinson’s Progression Markers Initiative database were used to develop the model. In ADNI, 230 mild cognitive impairment (MCI) subjects were matched with 230 CN old-aged subjects to evaluate their heterogeneity difference. One hundred four MCI subjects with 48 months of follow-up were divided into low and high heterogeneity groups. Kaplan–Meier survival curve analysis was used to observe the importance of heterogeneity results for predicting MCI progression.

Results

The area under the receiver operating characteristic curve of the model in the training, internal test and external test sets was 0.7503, 0.7512 and 0.7514, respectively. There was a significantly positive correlation between age and radscore of CN subjects (r = 0.501; P < .001). The radscore of MCI subjects was significantly higher than that of matched CN subjects (P < .001). The median radscore ratios of MCI to CN from four age groups (66–70y, 71–75y, 76–80y and 81–85y) were 1.611, 1.760, 1.340 and 1.266, respectively. The probability to progression of low and high heterogeneity groups had a significant difference (P = .002).

Conclusion

When radscore is significantly higher than that of normal ageing, it is necessary to alert the possibility of cognitive impairment and deterioration.