bluuebunny/crossref_metadata_2025 huggingface dataset:
A broad survey of choanoflagellates revises the evolutionary history of the Shaker family of voltage-gated K
+
channels in animals
Authors: Jegla Timothy , Simonson Benjamin T. , Spafford J. David
Published: July 2024

The Shaker family of voltage-gated K
+
channels has been thought of as an animal-specific ion channel family that diversified in concert with nervous systems. It comprises four functionally independent gene subfamilies (Kv1-4) that encode diverse neuronal K
+
currents. Comparison of animal genomes predicts that only the Kv1 subfamily was present in the animal common ancestor. Here, we show that some choanoflagellates, the closest protozoan sister lineage to animals, also have Shaker family K
+
channels. Choanoflagellate Shaker family channels are surprisingly most closely related to the animal Kv2-4 subfamilies which were believed to have evolved only after the divergence of ctenophores and sponges from cnidarians and bilaterians. Structural modeling predicts that the choanoflagellate channels share a T1 Zn
2+
binding site with Kv2-4 channels that is absent in Kv1 channels. We functionally expressed three Shakers from
Salpingoeca helianthica
(SheliKvT1.1-3) in
Xenopus
oocytes. SheliKvT1.1-3 function only in two heteromultimeric combinations (SheliKvT1.1/1.2 and SheliKvT1.1/1.3) and encode fast N-type inactivating K
+
channels with distinct voltage dependence that are most similar to the widespread animal Kv1-encoded A-type Shakers. Structural modeling of the T1 assembly domain supports a preference for heteromeric assembly in a 2:2 stoichiometry. These results push the origin of the Shaker family back into a common ancestor of metazoans and choanoflagellates. They also suggest that the animal common ancestor had at least two distinct molecular lineages of Shaker channels, a Kv1 subfamily lineage predicted from comparison of animal genomes and a Kv2-4 lineage predicted from comparison of animals and choanoflagellates.
Ray tracing through absorbing dielectric media in the Schwarzschild spacetime
Authors: Rogers Adam
Published: July 2024

General Relativity describes the trajectories of light-rays through curved spacetime near a massive object. In addition to gravitational lensing, we include an absorbing dielectric medium given by a complex refractive index known as the Drude model. When absorption is included the eikonal becomes complex, with the imaginary part related to the absorption along a ray between emission and observation points. We extend results from the literature to include dispersion in the index of refraction. The complex Hamiltonian splits into a real part that describes the equations of motion and a constraint equation that governs the momentum loss in the system. We work in coordinates which are fully real, with a real metric in physical spacetime. We assume the dust and plasma distributions of the Drude matter to coincide and vary as a power-law

1

/

r
h

. We find that transmission requires h > 1, otherwise exponential absorption occurs along ray paths. We use ray-tracing through strongly absorbing matter near the surface of the compact star, as well as specializing to a point-lens in the weak-field limit with weakly absorbing matter to generate potentially observable light curves for distant observers. In the appropriate limits, our theory reproduces results from the literature.
Artificial optoelectronic synapses based on flexible and transparent oxide transistors
Authors: Sadiq Muhammad Irfan , Zahid Muhammad , Jin Chenxing , Shi Xiaofang , Liu Wanrong , Xu Yunchao , Tahir Muhammad , Aslam Fawad , Yang Junliang , Sun Jia
Published: July 2024

The development of artificial optoelectronic synapses utilizing flexible, and transparent oxide transistors is crucial for advancing neuromorphic computing and wearable electronics. Here, we propose artificial optoelectronic synapses on flexible and transparent devices based on an ion-gel gated oxide transistor. The device consists of indium-tin-oxide/ion-gel thin film conformity fabricated on a polyethylene terephthalate substrate. The device exhibited a loop opening in current–voltage properties, and its operating mechanism was ascribed to charge trapping and de-trapping. The neuromorphic behaviors can also be simulated by this device for instance, namely ultraviolet (UV) induced short-term memory, long-term memory, paired-pulse facilitation, and learning/forgetting behaviors. Additionally, electrical habituation and UV potentiation were executed. This work paves the way for the realization of low-cost flexible and transparent synaptic wearable electronics.
Study on the effect of heat treatment on the structure, mechanical and electrical properties of alumina fiber insulation
Authors: Xie Li , Han Yongjin , Huang Yang
Published: July 2024

In this paper, the heat treatment of alumina fiber was studied. The infiltration agent on the fiber surface was removed after heat treatment at 450 °C for 6 h. TG-DSC, scanning electron microscope, x-ray diffraction, Fourier infrared spectrometer, energy dispersive spectrometer, and patterning were used to analyze the thermal weight loss, fiber surface morphology, crystal structure, and composition of alumina fibers. The results show that the aluminum oxide fiber has excellent temperature resistance and does not undergo crystal phase transformation during thermal weight loss. After heat treatment, the fiber surface infiltration agent ablates and dissolves from the fiber surface, and the internal crystal structure of the fiber remains stable. The tensile testing machine was utilized to test the breaking strength of alumina fiber. The fiber still maintained high strength after heat treatment, and the retention rate of breaking strength was greater than 74%. ZC-90G high insulation resistance measuring instrument and WDY-Ⅱ automatic voltage tester were utilized to analyze the insulation resistivity and breakdown strength of alumina fiber before and after heat treatment. The results show that heat treatment can effectively improve the insulation performance and breakdown strength of alumina fiber.
Enhancement of DDST-MFAC for tracking performance by using dynamic data reconciliation
Authors: Wang Zhiwen , Syafiq Sadun Amirul , Lv Mingxu , Chen Chongcheng , Cui Peng , Fauri Muhammad Ashraf
Published: July 2024

Model-free adaptive control (MFAC) stands out as an effective data-driven method for addressing nonlinear problems in industrial processes. To maintain good control performance, a data-driven set-point tuning (DDST) method is used to update the virtual set-point of the MFAC system. The DDST-based MFAC (i.e. DDST-MFAC) constantly approaches the target of the process through the nonlinear set-point tuning method. However, due to equipment errors and external interference, industrial sensors often suffer from measurement noise, which can have adverse effects on the control performance. In this article, an available dynamic data reconciliation technique is adopted to improve the tracking performance of the DDST-MFAC, which suppresses the impact of process noise by using predicted information and measured data to achieve high-precision requirements for controlling nonlinear processes. Finally, considering both Gaussian and non-Gaussian distribution of measurement noise, the effectiveness of the proposed method was verified through the simulation of a nonlinear nonaffine plant. It is also applied to the steam-water heat exchange process, the control result is improved ultimately.
Multi-factor quality assessment of digital speckle pattern for speckle projection profilometry
Authors: Dong Yanzhen , Wu Haitao , Chen Xiaobo , Xi Juntong
Published: July 2024

The digital speckle pattern (DSP) is an essential component in the speckle projection profilometry (SPP) task, its quality directly affects the results of three-dimensional (3D) shape reconstruction. However, the SPP field lacks specialized numerical metrics for evaluating speckle quality. To address this issue, this study introduces a multi-factor metric (MFM) for comprehensive DSP assessment. Through comparing the metric, optimal parameter ranges for DSP design and the advisable matching subset size can be determined for SPP algorithm. A global indicator named valid feature distribution (VFD) based on scale-invariant feature transform (SIFT) and Delaunay triangulation, is defined to analyze the overall information distribution in DSPs. In addition, MFM incorporates a local metric called mean subset intensity gradient (MSIG), which aids in selecting the suitable radius for different DSPs to balance the accuracy and efficiency. The quality assessment targets the speckle scene images, allowing for the reverse adjustment of the most suitable DSP according to different scenes. The performance of DSPs can be evaluated based on the accuracy and completeness of 3D reconstruction results. By conducting simulation experiments on the 3ds Max platform, the recommended parameter range for DSP can be inferred, including speckle density ratio, speckle diameter, and random variation rate. Appropriate subset sizes for different scenes are also investigated. Furthermore, the MFM is verified on a real binocular speckle device, demonstrating that the measurement standard deviation of a complex workpiece can be reduced to 0.078 mm using the recommended DSP.
Characterising and tackling thermally induced zero-drift in displacement measuring interferometry using temperature-controlled enclosure
Authors: Rerucha Simon , Hola Miroslava , Cip Ondrej , Lazar Josef , Oulehla Jindrich , Mikel Bretislav
Published: July 2024

Our research efforts in displacement measurement interferometry focused on long-term drifts initiated an extended experimental investigation in the interferometric assemblies of our design. We aimed to analyze, characterize and tackle the long-term measurement stability, expressed as the zero-drift, with particular attention to the thermal effects. For the experimentation, we developed a thermostatic chamber equipped with active temperature regulation, an array of sensors and control electronics. With either the finely stabilized temperature or with the thermal cycling, we can carry out a range of investigations: verification of modified design or prototype interferometers, testing of production pieces, characterization of integrated assemblies and units in terms of the zero drift and the susceptibility to thermal effects—the temperature sensitivity (

δ
L

/

δ
T

, expressed in nm

⋅

 K−1). With these experimental studies, we demonstrate the potential of the zero drift studies to contribute to the development and broader expansion of interferometric instrumentation.
Precipitable water vapor retrieval for rainfall forecasting using BDS-3 PPP-B2b signal in the coastal region of China
Authors: Xu Ying , Zhao Panpan , Wang Jin
Published: July 2024

Currently, rainfall cannot be accurately forecast because of poor network communication at the ocean. The advantage of the BeiDou Global Navigation Satellite System (BDS-3) precise point positioning (PPP-B2b) signal, which does not rely on network communication to receive data, is that it can provide precipitable water vapor (PWV) retrieval application services for the open seas in eastern China, where the communication system presents difficulties. In this study, data from stations in the coastal region of China were used to establish a rainfall forecasting method for monitoring extreme weather on the sea. First, the service performance of PPP-B2b was explored. Then, based on 17 Chinese coastal stations, the PWV accuracy was evaluated. Finally, based on an analysis of the relationship between PWV and actual rainfall, a threshold rainfall forecasting method based on a sliding window was constructed. The experimental results show that the PWV accuracy varies slightly depending on the geographic location, in which the mean absolute error in the North Sea region is the smallest (2.1 mm), that of the South China Sea region is the largest (2.60 mm), and that of the East China Sea region is in the middle (2.48 mm). The optimal predictors of the constructed 12 h sliding-window threshold rainfall prediction method are a PWV maximum of 49 mm, PWV increase of 5 mm, and PWV increase rate of 1.2 mm h−1. The prediction results can reach a critical success index value of more than 45%, indicating high prediction accuracy and applicability to the coastal region of China during the same period.
Stable/unstable holonomies, density of periodic points, and transitivity for continuum-wise hyperbolic homeomorphisms
Authors: Carvalho B , Rego E
Published: July 2024

We discuss different regularities on stable/unstable holonomies of cw-hyperbolic homeomorphisms and prove that if a cw-hyperbolic homeomorphism has continuous joint stable/unstable holonomies, then it has a dense set of periodic points in its non-wandering set. For that, we prove that the hyperbolic cw-metric (introduced in Artigue et al (2024 J. Differ. Equ.
378 512–38)) can be adapted to be self-similar (as in Artigue (2018 Ergodic Theory Dyn. Syst.
38 2422–46)) and, in this case, continuous joint stable/unstable holonomies are pseudo-isometric. We also prove transitivity of cw-hyperbolic homeomorphisms assuming that the stable/unstable holonomies are isometric. In the case the ambient space is a surface, we prove that a cw
F
-hyperbolic homeomorphism has continuous joint stable/unstable holonomies when every bi-asymptotic sector is regular.
A framework for in-field and out-of-field patient specific secondary cancer risk estimates from treatment plans using the TOPAS Monte Carlo system
Authors: Meyer Isaac , Peters Nils , Tamborino Giulia , Lee Hoyeon , Bertolet Alejandro , Faddegon Bruce , Mille Matthew M , Lee Choonsik , Schuemann Jan , Paganetti Harald
Published: July 2024

Objective. To allow the estimation of secondary cancer risks from radiation therapy treatment plans in a comprehensive and user-friendly Monte Carlo (MC) framework. Method. Patient planning computed tomography scans were extended superior-inferior using the International Commission on Radiological Protection’s Publication 145 computational mesh phantoms and skeletal matching. Dose distributions were calculated with the TOPAS MC system using novel mesh capabilities and the digital imaging and communications in medicine radiotherapy extension interface. Finally, in-field and out-of-field cancer risk was calculated using both sarcoma and carcinoma risk models with two alternative parameter sets. Result. The TOPAS MC framework was extended to facilitate epidemiological studies on radiation-induced cancer risk. The framework is efficient and allows automated analysis of large datasets. Out-of-field organ dose was small compared to in-field dose, but the risk estimates indicate a non-negligible contribution to the total radiation induced cancer risk. Significance. This work equips the TOPAS MC system with anatomical extension, mesh geometry, and cancer risk model capabilities that make state-of-the-art out-of-field dose calculation and risk estimation accessible to a large pool of users. Furthermore, these capabilities will facilitate further refinement of risk models and sensitivity analysis of patient specific treatment options.
Resolution limits for radiation-induced acoustic imaging for in vivo radiation dosimetry
Authors: Kumar Pandey Prabodh , Bjegovic Kristina , Gonzalez Gilberto , Wang Xinxin , Liu An , Chen Yong , Xiang Liangzhong
Published: July 2024

Objective. Radiation-induced acoustic (RA) computed tomographic (RACT) imaging is being thoroughly explored for radiation dosimetry. It is essential to understand how key machine parameters like beam pulse, size, and energy deposition affect image quality in RACT. We investigate the intricate interplay of these parameters and how these factors influence dose map resolution in RACT. Approach. We first conduct an analytical assessment of time-domain RA signals and their corresponding frequency spectra for certain testcases, and computationally validate these analyses. Subsequently, we simulated a series of x-ray-based RACT (XACT) experiments and compared the simulations with experimental measurements. In-silico reconstruction studies have also been conducted to demonstrate the resolution limits imposed by the temporal pulse profiles on RACT. XACT experiments were performed using clinical machines and the reconstructions were analyzed for resolution capabilities. Main results. Our paper establishes the theory for predicting the time- and frequency-domain behavior of RA signals. We illustrate that the frequency content of RA signal is not solely dependent on the spatial energy deposition characteristics but also on the temporal features of radiation. The same spatial energy deposition through a Gaussian pulse and a rectangular pulse of equal pulsewidths results in different frequency spectra of the RA signals. RA signals corresponding to the rectangular pulse exhibit more high-frequency content than their Gaussian pulse counterparts and hence provide better resolution in the reconstructions. XACT experiments with ∼3.2 us and ∼4 us rectangular radiation pulses were performed, and the reconstruction results were found to correlate well with the in-silico results. Significance. Here, we discuss the inherent resolution limits for RACT-based radiation dosimetric systems. While our study is relevant to the broader community engaged in research on photoacoustics, x-ray-acoustics, and proto/ionoacoustics, it holds particular significance for medical physics researchers aiming to set up RACT for dosimetry and radiography using clinical radiation machines.
Analysis of current and heat transfer in locations with reduced critical current in coated conductor tape
Authors: Gömöry Fedor , Šouc Ján
Published: July 2024

Variation of the critical current along the conductor length is a feature commonly encountered in industrially produced REBCO tapes called coated conductors (CCs). A reduction of the critical current exceeding several percent in portions a few millimetres long can be observed in the data obtained by reel-to-reel characterization provided by manufacturers. Metallic layers in the CC architecture can take over some current in such a ‘weak spot’, and help to keep the local temperature stable, preventing its thermal runaway and conversion to a ‘hot spot’. Understanding this phenomenon is particularly crucial when space and weight limitations do not allow for the addition of a metallic layer with a thickness that would be sufficient to match the lost transport capability of superconductors. For this purpose, we studied a set of samples, representing both standard as well as infrequent profiles of weak spots identified in direct transport experiments. Analytical theory is then utilized as a basic tool for recovering the properties serving as input for numerical modelling. Temperature profiles and current redistribution at weak-spot locations were found, and the effect of cooling conditions and metallic layer thickness on the weak-spot resistance against thermal runaway was analyzed. Quantitative assessment of the possibility to improve the performance of CC tape by adding a Cu stabilizing layer or improving cooling settings could help to optimize the architecture of CCs intended for use in electrical transport.
A formulation of quantum fluid mechanics and trajectories
Authors: Finley James P
Published: July 2024

A formalism of classical mechanics is given for time-dependent many-body states of quantum mechanics, describing both fluid flow and point mass trajectories. The familiar equations of energy, motion, and those of Lagrangian mechanics are obtained. An energy and continuity equation is demonstrated to be equivalent to the real and imaginary parts of the time dependent Schrödinger equation, respectively, where the Schrödinger equation is in density matrix form. For certain stationary states, using Lagrangian mechanics and a Hamiltonian function for quantum mechanics, equations for point-mass trajectories are obtained. For 1-body states and fluid flows, the energy equation and equations of motion are the Bernoulli and Euler equations of fluid mechanics, respectively. Generalizations of the energy and Euler equations are derived to obtain equations that are in the same form as they are in classical mechanics. The fluid flow type is compressible, inviscid, irrotational, with the nonclassical element of local variable mass. Over all space mass is conserved. The variable mass is a necessary condition for the fluid flow to agree with the zero orbital angular momentum for s states of hydrogen. Cross flows are examined, where velocity directions are changed without changing the kinetic energy. For one-electron atoms, the velocity modification gives closed orbits for trajectories, and mass conservation, vortexes, and density stratification for fluid flows. For many body states, under certain conditions, and by hypotheses, Euler equations of orbital-flows are obtained. One-body Schrödinger equations that are a generalization of the Hartree–Fock equations are also obtained. These equations contain a quantum Coulomb’s law, involving the 2-body pair function of reduced density matrix theory that replace the charge densities.
Enhancing sideband cooling by initial photon-phonon correlation
Authors: Niu Wei , Yang Wen-Quan , Ma Yong-Hong , Shu Chuan-Cun , Zhang Wen-Zhao
Published: July 2024

We propose an optimized sideband cooling protocol for an optomechanical system coupled to a mechanical non-Markovian reservoir, considering the presence of initial system correlations. By incorporating the effect of initial correlations in the Heisenberg equations, we derive a more stringent dependence on the initial conditions and time-dependent evolution of the phonon numbers. Our findings demonstrate that considering the initial correlations can significantly reduce the number of phonons during the cooling process. Moreover, by adjusting the strength and phase of the initial correlation, the ground-state cooling process can be accelerated. We observe a characterization of this cooling optimization process that resembles the phenomenon of entanglement death and revival. This work provides a promising platform for effectively manipulating phonons and facilitating quantum information processing in optomechanical systems.
Eight element MIMO antenna for sub 6 GHz 5G cellular devices
Authors: Abubakar Hassan Sani , Zhao Zhiqin , Kiani Saad Hassan , Khan Salahuddin , Ali Tanweer , Bashir Muhammad Adil , Cengiz Korhan , Kamal Mian Muhammad
Published: July 2024

This article introduces a wide-band MIMO antenna system with eight elements specifically designed for future handheld devices. The antenna is integrated into a 150 × 75 mm2 main board with a DGS antenna beneath it, connected to feed lines, and etched onto the ground plane. Covering two distinct 5G bands from 3 GHz to 3.6 GHz and from 3.6 GHz to 3.9 GHz, with 900 MHz impedance bandwidths, this antenna enables efficient data transmission and reception across these crucial frequency ranges. The system exhibits pattern and spatial diversity characteristics, achieving an overall efficiency of 40%–60% and a peak gain of 5.3 dBi, ensuring robust signal strength and isolation exceeding 10 dB among radiating elements. Furthermore, the antenna excels in key MIMO parameters, with an envelope correlation coefficient (ECC) below 0.19, well within the industry standard of less than 0.5, and it delivers more than 9.99 dB of diversity gain. Furthermore, Channel capacity Loss (CCL), Mean Effective Gain (MEG) and Total Active Reflection Co-efficient (TARC) across the entire operational band ensure good performance, promising enhanced diversity performance, superior data throughput, and heightened signal reliability. are The SAR analysis conducted yielded positive results within the human vicinity. The measurements obtained from the prototype matched well with simulations and through measurements obtained the proposed MIMO system can be termed as a potential candidate for future 5G Mobile Phones.
Effectiveness of thermoviscoplastic material models in predicting the thermomechanical behavior of rolled homogenous armor steel
Authors: Gangwar Vaibhav , Bhattacharjee Snehasish , Acharyya Sanjib Kumar , Dhar Sankar , Banerjee Arkadeb , Chakraborty Santu
Published: July 2024

This paper studies the dynamic and elevated temperature behavior of rolled homogeneous armor steel, which is crucial for applications such as blast, impact, crash, and ballistic resistance. The deformation behavior is analyzed through tensile tests. The tensile tests of RHA steel are conducted at quasi-static

10

−
4

s

−
1

≤

ε
p

̇

≤

10

−
1

s

−
1

to dynamic

10

−
1

s

−
1

≤

ε

p

̇

≤
36.439

s

−
1

strain-rates and at high temperatures ranging from room temperature

(
RT
,

27

°
C
)

to

5
00

°
C
.

Phenomenological Johnson-Cook (JC) models and semi-physical Rusinek-Klepaczko (RK) material models are employed in finite element (FE) simulations of tensile tests. The JC failure model, with a small modification, is used along with the material models to simulate the loss of load-bearing capacity of the component. All necessary material parameters are extracted from the test data. The material models and the damage model are integrated into ABAQUS CAE FE software through a user-defined material subroutine (UMAT). The simulated outcomes acquired from diverse material models are validated with relevant experimental findings, and the effectiveness of each material model is evaluated through qualitative and quantitative assessments. Observations reveal limitations in the existing models to accurately replicate material behavior under tension, particularly in the dynamic strain rate, and elevated temperature range. Consequently, a modified version of the JC model (MJC) is explored to better account for the impact of temperature on strain hardening and strain rate hardening. The proposed modification in the material model significantly enhances the predictive accuracy of FE simulations of tensile deformation across the entire spectrum of studied strain rates and temperatures compared to the original JC and RK models.
Effect of ARB process on the plane stress fracture toughness, creep properties and forming limit diagram of Aluminum/BN/Copper composite strips
Authors: Bandhu Din , Jasim Saade Abdalkareem , Khan Ahmad Raza , Kaur Mandeep , Kaur Harpreet , Reddy R Meenakshi , Naderian F
Published: July 2024

In the present study, Al/BN/Cu bimetal composite strips were fabricated via the accumulative roll bonding (ARB) process. Then, fracture toughness, mechanical properties, bonding strength, forming limit diagram (FLD), and creep properties have been studied via experimental techniques. The study of creep behavior and mechanical properties showed a formation of a 17 μm atomic diffusion layer at the interface during

ARB

under three creep loading conditions namely 35 MPa at 225 °C, 35 MPa at 275 °C, and 30 MPa at 225 °C. The tensile strength of samples improved to 144 MPa which was about 234% in comparison with the primary Al monolithic sample. It was observed by the SEM that the fracture types changed to shear kind after higher passes including prominent effects on the fracture morphology. FLD curve dropped severely after the first ARB pass and then began to enhance at higher passes. The fracture toughness value of 30 MPa m1/2 was achieved after ten ARB passes. An intermetallic composition was created near Al. The creep failure time did decline by 44% and the stress level decreased by 13% at a constant temperature. It can be concluded that applied temperature and stress effect on creep properties especially leads to increasing the slope of creep curves with higher stresses. This trend was opposite for the creep temperature at higher temperature levels. Moreover, dynamic recrystallization was observed through the crystalline structure of samples.
Tensorized Pauli decomposition algorithm
Authors: Hantzko Lukas , Binkowski Lennart , Gupta Sabhyata
Published: July 2024

This paper introduces a novel general-purpose algorithm for Pauli decomposition that employs matrix slicing and addition rather than expensive matrix multiplication, significantly accelerating the decomposition of multi-qubit matrices. In a detailed complexity analysis, we show that the algorithm admits the best known worst-case scaling and more favorable runtimes for many practical examples. Numerical experiments are provided to validate the asymptotic speed-up already for small instance sizes, underscoring the algorithm’s potential significance in the realm of quantum computing and quantum chemistry simulations.
Cosmological constraints from the eBOSS Lyman-α forest using the PRIYA simulations
Authors: Fernandez M.A. , Bird Simeon , Ho Ming-Feng
Published: July 2024

We present new cosmological parameter constraints from the eBOSS Lyman-α forest
survey. We use a new theoretical model and likelihood based on the PRIYA simulation suite. PRIYA
is the first suite to resolve the Lyman-α forest in a (120 Mpc/h)3 volume, using a
multi-fidelity emulation technique. We use PRIYA to predict Lyman-α forest observables
with ≲ 1% interpolation error over an 11 dimensional (9 simulated, 2 in
post-processing) parameter space. We identify an internal tension within the flux power spectrum
data. Once the discrepant data is removed, we find the primeval scalar spectral index measured at
a pivot scale of k
0 = 0.78 Mpc-1 to be nP
= 1.009+0.027
-0.018 at 68%
confidence. This measurement from the Lyman-α forest flux power spectrum alone is in
reasonable agreement with Planck, and in tension with earlier eBOSS analyses. The amplitude of
matter fluctuations is σ
8 = 0.733+0.026
-0.029 at 68% confidence, in agreement with
Dark Energy Survey weak lensing measurements and other small-scale structure probes and in tension
with CMB measurements from Planck and ACT. The effective optical depth to Lyman-α 
photons from our pipeline is in good agreement with earlier high resolution measurements. We find
a linear power at z = 3 and k = 0.009 s/km of Δ2

L
= 0.302+0.024
-0.027 with a
slope n
eff = -2.264+0.026
-0.018. Our flux power spectrum only chains prefer a
low level of heating during helium reionization. When we add IGM temperature data we find nP
=
0.983 ± 0.020 and σ
8 = 0.703+0.023
-0.027. Our chains prefer an early and long
helium reionization event, as suggested by measurements from the helium Lyman-α forest. In
the near future we will use our pipeline to infer cosmological parameters from the DESI
Lyman-α data.
Development of generic no-scale inflation
Authors: Wu Lina , Shen Jin-Ke , Li Tianjun , Pei Junle
Published: July 2024

We develop generalized no-scale supergravity models of inflation, and then study the
corresponding cosmological predictions as well as the formation of primordial black holes (PBHs)
and scalar-induced gravitational waves (SIGWs). With a new parameter 0 < a ≤ 1, the generalized
no-scale supergravity provides the continuous connections among the generic no-scale supergravity
from string theory compactifications. The resulting prediction of the CMB, spectrum index ns
,
and tensor-to-scalar ratio r can be highly consistent with the latest Planck/BICEP/Keck Array
observations. Notably, the models with a ≠ 1 give a smaller ratio r ≤ 10-3, which is
flexible even under the anticipated tighter observational constraints at the future experiments.
Additionally, these models have the potential to generate a broad-band stochastic gravitational
wave background, and thus explain the NANOGrav 15yr signal. Furthermore, they predict the
formation of PBHs with various mass scales, which could account for a significant portion of dark
matter relic density in the Universe.
Imaging through scattering layers using a near-infrared low-spatial-coherence fiber random laser
Authors: Shi 史 Anda 安达 , Wang 王 Zeyu 泽宇 , Duan 段 Chenxi 辰锡 , Wang 王 Zhao 昭 , Zhang 张 Weili 伟利
Published: July 2024

Optical memory effect-based speckle-correlated technology has been developed for reconstructing hidden objects from disordered speckle patterns, achieving imaging through scattering layers. However, the lighting efficiency and field of view of existing speckle-correlated imaging systems are limited. Here, a near-infrared low spatial coherence fiber random laser illumination method is proposed to address the above limitations. Through the utilization of random Rayleigh scattering within dispersion-shifted fibers to provide feedback, coupled with stimulated Raman scattering for amplification, a near-infrared fiber random laser exhibiting a high spectral density and extremely low spatial coherence is generated. Based on the designed fiber random laser, speckle-correlated imaging through scattering layers is achieved, with high lighting efficiency and a large imaging field of view. This work improves the performance of speckle-correlated imaging and enriches the research on imaging through scattering medium.
Cosmological test of dark energy parametrizations within the framework of Horava-Lifshitz gravity via baryon acoustic oscillation
Authors: Chaudhary Himanshu , Pacif Shibesh Kumar Jas , Debnath Ujjal , Rahaman Farook , Mustafa G.
Published: July 2024

We conduct an investigation to explore late-time cosmic acceleration through various dark energy parametrizations (Wettrich, Efstathiou, and Ma-Zhang) within the Horava-Lifshitz gravity framework. As an alternative to general relativity, this theory introduces anisotropic scaling at ultraviolet scales. Our primary objective is to constrain the key cosmic parameters and baryon acoustic oscillation (BAO) scale, specifically the sound horizon (rd
), by utilizing 24 uncorrelated measurements of BAOs derived from recent galaxy surveys spanning a redshift range from z = 0.106 to z = 2.33. Additionally, we integrate the most recent Hubble constant measurement by Riess in 2022 (denoted as R22) as an extra prior. For the parametrizations of Wettrich, Efstathiou, and Ma-Zhang, our analysis of BAO data yields sound horizon results of rd
= 148.1560 ± 2.7688 Mpc, rd
= 148.6168 ± 10.2469 Mpc, and rd
= 147.9737 ± 10.6096 Mpc, respectively. Incorporating the R22 prior into the BAO dataset results in rd
= 139.5806 ± 3.8522 Mpc, rd
= 139.728025 ± 2.7858 Mpc, and rd
= 139.6001 ± 2.7441 Mpc. These outcomes highlight a distinct inconsistency between early and late observational measurements, analogous to the H
0 tension. A notable observation is that, when we do not include the R22 prior, the outcomes for rd
tend to be in agreement with Planck and SDSS results. Following this, we conducted a cosmography test and comparative study of each parametrization within the Lambda Cold Dark Matter paradigm. Our diagnostic analyses demonstrate that all models fit seamlessly within the phantom region. All dark energy parametrizations predict an equation of state parameter close to

= –1, indicating a behavior similar to that of a cosmological constant. The statistical analysis indicates that neither of the two models can be ruled out based on the latest observational measurements.
A fully automatic multichannel neural spike sorting algorithm with spike reduction and positional feature
Authors: Mohammadi Zeinab , Denman Daniel J , Klug Achim , Lei Tim C
Published: July 2024

Objective: The sorting of neural spike data recorded by multichannel and high channel neural probes such as Neuropixels, especially in real-time, remains a significant technical challenge. Most neural spike sorting algorithms focus on sorting neural spikes post-hoc for high sorting accuracy—but reducing the processing delay for fast sorting, potentially even live sorting, is generally not possible with these algorithms. Approach: Here we report our Graph nEtwork Multichannel sorting (GEMsort) algorithm, which is largely based on graph network, to allow rapid neural spike sorting for multiple neural recording channels. This was accomplished by two innovations: In GEMsort, duplicated neural spikes recorded from multiple channels were eliminated from duplicate channels by only selecting the highest amplitude neural spike in any channel for subsequent processing. In addition, the channel from which the representative neural spike was recorded was used as an additional feature to differentiate between neural spikes recorded from different neurons having similar temporal features. Main results: Synthetic and experimentally recorded multichannel neural recordings were used to evaluate the sorting performance of GEMsort. The sorting results of GEMsort were also compared with two other state-of-the-art sorting algorithms (Kilosort and Mountainsort) in sorting time and sorting agreements. Significance: GEMsort allows rapidly sort neural spikes and is highly suitable to be implemented with digital circuitry for high processing speed and channel scalability.
Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches
Authors: Sánchez-Villar Á. , Bai Z. , Bertelli N. , Bethel E.W. , Hillairet J. , Perciano T. , Shiraiwa S. , Wallace G.M. , Wright J.C.
Published: July 2024

A real-time capable core Ion Cyclotron Range of Frequencies (ICRF) heating model on NSTX and WEST is developed. The model is based on two nonlinear regression algorithms, the random forest ensemble of decision trees and the multilayer perceptron neural network. The algorithms are trained on TORIC ICRF spectrum solver simulations of the expected flat-top operation scenarios in NSTX and WEST assuming Maxwellian plasmas. The surrogate models are shown to successfully capture the multi-species core ICRF power absorption predicted by the original model for the high harmonic fast wave and the ion cyclotron minority heating schemes while reducing the computational time by six orders of magnitude. Although these models can be expanded, the achieved regression scoring, computational efficiency and increased model robustness suggest these strategies can be implemented into integrated modeling frameworks for real-time control applications.
CIGALE: an innovative gas neutralizer based high efficiency neutral beam injector concept for future fusion reactors
Authors: Simonin A. , Bourvard H. , Pouradier Duteil B.
Published: July 2024

This paper outlines the main features of a new high efficiency (η > 62%) high power (∼18 MW D0) neutral beam (NB) concept based on pragmatic solutions suitable with the reactor requirements. The injector is modular (several beamlines in parallel) with independent ion sources referenced to the ground potential and gas neutralizers held at +1 MV. This topology leads to numerous simplifications; it overcomes the main issues of conventional NB systems, such as the complex 1 MV electrical setup, the difficult ion source remote maintenance, the high caesium consumption. The other key parameter is the gas neutralization concept which minimizes the amount of gas by operating at a low gas target and low neutralizer duct conductance. The implementation of an energy recovery system for the residual 1 MeV D− is essential to attain a high wall-plug efficiency. These specific features require thin laminar D− beams provided by a pre-acceleration up to 100 keV in slotted grid apertures to form thin blade-like beamlets, followed by the post-acceleration to 1 MeV by merging the beamlets in a single beam in five gaps (+200 kV per gap). All these specific aspects minimize the beams losses and thermal loads along the beamline and enhance the injector reliability and availability.
Impact of Gale Weather Events on Wind Power Generation
Authors: Zhang Yuanhe , Yang Ming , Wang Bo , Li Menglin , Yu Yixiao
Published: July 2024

Due to the influence of global warming, extreme wind weather occurs frequently, especially in extreme weather such as typhoons and cold waves, problems such as wind turbine shutdown, cutting out, and sudden changes in power generation power will occur, which brings great challenges to wind power forecast and safe and stable operation of the power grid. At present, the research and analysis of strong wind weather mostly stay at the single fan level, and the causes of abnormal changes in wind power output are mostly analyzed from the physical level. However, with the large-scale access of wind power to the power grid, the impact of extreme weather on power grid operation is becoming more and more significant, and it is particularly important to study the impact of strong wind weather events on wind power cluster output. This paper summarizes various types of wind power generation weather events, then screens key meteorological factors affecting power generation under different wind weather conditions based on Gaussian search and grey correlation weighting, and finally analyzes the meteorological impact on the actual operation of wind farm stations and clusters under typhoons and cold waves respectively, aiming at the problem of huge deviations in wind power forecast caused by wind. The next research direction and suggestions are put forward.
Design of On-line Monitoring and Fault Diagnosis Platform for Oil-immersed Shunt Reactor
Authors: Wang Yanhong , Su Mingran , Hu Yiru , Yang Wei
Published: July 2024

With the development of society and technology, the demand for power supply and reliability is increasing. In the power system, the reactor plays an important role as a key equipment. However, due to long-term operation, the reactor is affected by factors such as loss, aging and hidden faults, and its reliability gradually decreases. The operation state of the reactor is directly related to the operation effect of the power grid and the quality of the user’s electricity. Therefore, the application of reactor online monitoring and fault diagnosis in real life is very important. This paper considers the actual operation of the coastal power grid. Based on Qt software development platform, C + + language and MySQL database, an online monitoring and fault diagnosis platform for oil-immersed shunt reactors is developed. The application of the platform takes the online monitoring and fault diagnosis method of dissolved gas in oil as the core. The platform realizes the basic information management, online monitoring, fault diagnosis and suggestions for operation and maintenance of the reactor.
A Short-Term Power Load Forecasting Approach Based on EMD-SSA-LSTM
Authors: Su Zhiyin , Zeng Jinhui , Liu Jie , Wang Jing , Li Changxue
Published: July 2024

Accurate power load forecasting is the foundation of the power system. However, economic, weather, and geographic factors can affect short-term electric load forecasting and can make it difficult to enhance load forecasting accuracy. To solve the problem, a novel load forecasting method based on empirical mode decomposition (EMD) and long short-term memory (LSTM) neural networks has been proposed. Firstly, the EMD algorithm is utilized to decompose the original signal into elementary components and a series of intrinsic mode functions (IMF). Subsequently, all components are input into the LSTM neural networks for load prediction. Moreover, to further improve the prediction accuracy, the sparrow search algorithm (SSA) is introduced to optimize the parameters of LSTM for the prediction of basic components. Integrating SSA and EMD-LSTM, the EMD-SSA-LSTM model is further proposed for short-term power load forecasting. Finally, the proposed model is validated by several experiments, and the results show that the coefficient of determination (R2) under the proposed model can reach 0.98, the mean absolute error (MAE) is 0.015, and the root mean square error (RMSE) is 0.02. It is verified that the proposed model can improve the accuracy of load forecasting.
Distributed Photovoltaic Output Prediction Using Machine Learning and Numerical Model Combined Method
Authors: Wang Lei , Kang Wenjun , Feng Tao , Li Li
Published: July 2024

In recent years, distributed photostatic (PV) has developed rapidly. Accurate prediction of distributed PV output can improve the reliable, efficient and economical grid-connected operation of distributed PV, and enhance the reliability of power supply. In this study, we first collected the datasets of distributed PV output and centralized PV station output in Dongan County, Yongzhou City, Hunan Province. Then, we analyzed the relationship between distributed PV station output and centralized PV output under different weather conditions, and constructed the centralized PV output prediction curve by combining machine learning and numerical prediction model, and finally obtained the distributed PV output prediction of the whole county. The results show that the correlation coefficient changes between the output of distributed PV stations and that of centralized PV stations under different weather scenarios (sunny, cloudy, etc.), but they all show a good consistency (the correlation coefficient of more than 0.6 accounts for more than 95% of the PV stations), indicating that the output change of centralized PV stations in one county can be used to characterize the output change of distributed stations. The distributed PV output prediction model built by LSTM and numerical model combined method has achieved a prediction accuracy of 90.4% for a single station and 94.31% for the whole county within 24 hours, both of which are 4%˜5% higher than the requirements of national standards. The model can be further extended to forecast the distributed PV output of the whole province.
Dynamic Identification Method of Load Adjustable Capacity Based on Load Dynamic Characteristic Generation
Authors: Zhang Jie , Lin Ruiyu , Shen Nuoqing , Du Jingmei , Liao Siyang
Published: July 2024

With the continuous establishment of the energy internet, there are already regions carrying out demand response pilots by installing smart meters. In the case that complete communication has not yet been established, how to mine the potential value of collected smart meter data based on the existing pilot areas to obtain the real response potential of regional temperature control equipment at each moment is a common focus of attention in both academia and industry. In this paper, we propose a method for dynamically identifying load adjustable capacity based on generated load dynamic characteristics, which enhances the load feature library and dynamically identifies load adjustable capacity based on generated load dynamic characteristics. The method only installs a smart energy measuring device at the customer’s entrance line to obtain the customer’s total load power information and dynamically recognizes the adjustable capacity of the load based on the generation of load dynamic characteristics.
Distributed Photovoltaic Site Selection and Capacity Planning Considering Power Mutual Support in Multiple Power Distribution Areas
Authors: Gu Taiyu , Tian Ye , Zhu Yidong , Du Wei , Liu Zhaochen , Shang Lei
Published: July 2024

With the rapid development of local economy, the form of independent power supply from a single power supply in the power distribution area is difficult to meet the demand for high reliability. The interconnection and power mutual assistance planning of power distribution areas under large-scale distributed photovoltaic access have attracted widespread attention. Due to the randomness and volatility of distributed photovoltaics, its different access methods and capacities will affect the safe and stable operation and power mutual assistance capabilities of the distribution area. In order to study the site selection and capacity planning problem of distributed photovoltaics, this paper builds a site selection and capacity model based on the three-phase power flow equation with the maximum external power of the station area as the optimization goal and the safe operation of the distribution area as constraints. Furthermore, an optimization method for distributed photovoltaic site selection and capacity based on improved particle swarm algorithm is proposed. Finally, this paper verified the effectiveness of the optimization method through simulation analysis on the IEEE33 three-phase grid model. The simulation results show that this method of site selection and capacity determination can achieve maximum power transmission in the power distribution area while ensuring the safe and stable operation of the area.