bluuebunny/crossref_metadata_2025 huggingface dataset:
Neutralized, intense-ion beams for fusion
Authors: Wessel Frank J , Egly Andrew , Rogers Joel
Published: April 2024

A charge- and current-neutralized, intense-ion beam (IIB) will propagate undeflected in a magnetized plasma by the

E
×
B

, or diamagnetic, drift for a distance large compared to the beam-ion gyro-radius. This propagation occurs because of collective plasma effects when the beam-energy density is sufficient to sustain the polarization-electric field, or diamagnetic-screening currents. Our principal interest is the

E
×
B

drift, with

β
=

E

beam

/

E

field

<
1

. IIBs are characterized by parameters in the range: 0.1–2 MeV ion energy, 1–100 MA m−2 ion-current density, and 17–350 kW average power produced on repetitively-pulsed systems. Multi-MW average-beam power is possible with appropriate modifications to the power supply and ion-source/accelerator. IIBs can be focused geometrically, and/or magnetically, to spot sizes of the order of a few cm’s and their angular divergence is typically, ∼15 mRadians, suitable for long-range propagation in a vacuum beam-line. IIBs lose energy and momentum in the same manner as particles injected by a neutral-beam injector (NBIs), hence could be useful for fusion applications, including: heating, current drive, fueling, profile modifications, etc and such applications have yet to be thoroughly studied. Summarized here are the physical principles accounting for IIB propagation; ion-source designs used to produce the IIB; and pulsed-power methods for energizing the IIB accelerator. This technology base informs scalable metrics for the ion-source/accelerator (excluding the HV power supply and interconnects) used in a conceptual injector that provides the same ion energy and injected power (1 MeV, 17 MW) as NBIs used on ITER. A comparison indicates that the IIB injector would be much smaller in size, lower cost, and have much greater efficiency, while also providing for real-time modulation of the beam energy and intensity and the use of small-diameter injection ports that could minimize fuel contamination and magnetic-field leakage between the IIB injector and tokamak.
Understanding the trap-induced frequency dispersion in the C–V curve of AlGaN/GaN hetero-structure
Authors: Nautiyal Priyanka , Pande Peyush , Kundu Virender , Joshi Vikas , Chaturvedi Mayank
Published: April 2024

This article investigates the trapping mechanism in AlGaN/GaN heterostructure. For our study, the traps within the AlGaN layer are introduced at the interface and near the interface of AlGaN/GaN, in the SILVACO TCAD tool. Frequency-dependent capacitance-Voltage (CVF) curves are obtained to study the impact of traps on device performance. From the CVF curve, it is found that the existence of interface traps introduces a shift in capacitance along the gate voltage axis. These traps introduce the threshold voltage (

V

TH

) shift. Furthermore, a detailed study of near-interface traps (NITs) is done based on tunneling mechanisms. For our investigation, the NITs are positioned at 0.5 nm, 1 nm, and 1.5 nm away from the AlGaN/GaN interface. The response of the NITs reduces the capacitance value in the accumulation region. The response of the NITs is explained through the capacitance charge model and border trap model. For NITs placed 0.5 nm away from the interface, the frequency dispersion in the accumulation region becomes evident. On the contrary, the dispersion reduces significantly, as the NITs goes deeper upto 1.5 nm. The results indicate that the NITs nearer to the interface respond to high frequencies. Further, the temperature dependent capacitance–voltage analysis is done for both interface and NITs, to understand the effect of temperature on frequency dispersion.
Realization of an ultra-scaled novel Ga2O3 FinFET for sub-terahertz applications
Authors: Goyal Priyanshi , Kaur Harsupreet
Published: April 2024

This study involves in-depth simulations focused on gate-electrode and channel-doping engineering in ultra-scaled Ga2O3 FinFETs. Silvaco TCAD software was employed as a simulation tool to explore the suitability of these designs for sub-terahertz applications. The focus of the present study is the simultaneous enhancement in current drivability as well as the reduction in parasitic capacitances without any trade-off, to achieve superior performance for sub-terahertz applications. Along with the analog characteristics of the proposed device, various critical high-frequency figures of merit have also been evaluated. Furthermore, scattering parameters have also been studied with variations in frequency to gain insights into the performance of the proposed device at high frequencies. In addition, a thorough comparison of the proposed device with the conventional device has been carried out. It has been demonstrated that the proposed device is an excellent contender for ultra-high-frequency applications with remarkable high-frequency figures of merit.
On-demand fabrication of piezoelectric sensors for in-space structural health monitoring
Authors: White Amanda , Little Isaac , Artyuk Anastasiya , McKibben Nicholas , Rajabi Kouchi Fereshteh , Chen Claire , Estrada David , Deng Zhangxian
Published: April 2024

Inflatable structures, promising for future deep space exploration missions, are vulnerable to damage from micrometeoroid and orbital debris impacts. Polyvinylidene fluoride-trifluoroethylene (PVDF-trFE) is a flexible, biocompatible, and chemical-resistant material capable of detecting impact forces due to its piezoelectric properties. This study used a state-of-the-art material extrusion system that has been validated for in-space manufacturing, to facilitate fast-prototyping of consistent and uniform PVDF-trFE films. By systematically investigating ink synthesis, printer settings, and post-processing conditions, this research established a comprehensive understanding of the process-structure-property relationship of printed PVDF-trFE. Consequently, this study consistently achieved the printing of PVDF-trFE films with a thickness of around 40 µm, accompanied by an impressive piezoelectric coefficient of up to 25 pC N−1. Additionally, an all-printed dynamic force sensor, featuring a sensitivity of 1.18 V N−1, was produced by mix printing commercial electrically-conductive silver inks with the customized PVDF-trFE inks. This pioneering on-demand fabrication technique for PVDF-trFE films empowers future astronauts to design and manufacture piezoelectric sensors while in space, thereby significantly enhancing the affordability and sustainability of deep space exploration missions.
Structural seismic response reconstruction method based on multidomain feature-guided generative adversarial neural networks
Authors: Liu Bo , Xu Qiang , Chen Jianyun , Ye Ming , Wang Mingming
Published: April 2024

Structural seismic response reconstruction is important to assess the safety of structures. This study presents a novel multidomain feature-guided generative adversarial neural network model (MWGAN-TF) for reconstructing the seismic responses of structures, which takes into account the joint non-stationarity of the seismic response in the time-frequency statistical domain. It innovatively incorporates time, frequency, and statistical-domain feature constraints into the multiscale generative adversarial neural network, which guides the model to learn the multidomain feature information of the seismic response at different time scales. A statistical indicator (CNCSI) was proposed to evaluate the performance of the model in capturing nonstationary characteristics. The effectiveness of the MWGAN-TF was verified using response data from numerical models of a three-story moment-resisting frame and reinforced concrete frame structures, as well as the field measurement data of an actual building. Thereafter, the effects of different domain feature-guided models on the reconstruction response accuracy are discussed. The results show that embedding multidomain feature constraints can provide a more reliable response reconstruction by improving the ability of the model to capture nonstationary characteristics. Thus, the deep learning paradigm based on multidomain feature guidance outperforms the classical neural network guided only by time-domain features.
Vortex in superconducting thin-film strips of arbitrary width
Authors: Nakagawa Norio , Kogan Vladimir G
Published: April 2024

The currents and field distributions of a vortex in a thin superconducting strip of a width W are considered. It is shown that unlike infinite films where the vortex field crosses the film only in one direction (say, from the half-space under the film to the half-space above it), in strips (as well as in finite size film samples of any shape) the field lines go back to the lower half-space not only out of the sample but also through certain strip parts. The strip patches where the magnetic lines ‘dive’ back to the space under the strip are situated mostly near the strip edges, at the strip and out of it. The magnetic flux through the strip associated with the vortex is shown to be less than the flux quantum and depends on the vortex position. The suppression of the vortex flux is strong in narrow strips with

W
<<
Λ
=
2

λ
2

/

d

where λ is the bulk London penetration depth and d is the film thickness. The vortex energy scales roughly with

W

/

Λ

and depends on vortex position.
Nonlinear optical properties of tunable spherical quantum dots under like-screened Kratzer potential
Authors: Wang Xing , Li Xuechao , Cai Yawen , Yan Xiaolong
Published: April 2024

Using the effective mass approximation and the iterative procedure, we study the optical rectification (OR) coefficient of a spherical quantum dot (QD) system with like-screened Kratzer potential (LSKP), taking into account the influence of the confinement potential depth, quantum size and external environment. Our results show that the magnitude of the OR coefficient is strongly dependent on the magnitude of the tunable factor, whose peak value will be red-shifted or blue-shifted. Interestingly, the limiting potential depth and temperature have opposite effects on the OR coefficient in terms of peak location and size. Therefore, it is necessary to pay more attention to the influence of internal and external parameters on nonlinear optical effects, and apply the theory to practical experiments and the manufacture of optoelectronic devices.
Robust digital image watermarking scheme with a fractional-order discrete-time chaotic scheme and DWT-SVD transform
Authors: Hannoun Katia , Hamiche Hamid , Lahdir Mourad , Megherbi Ouerdia , Laghrouche Mourad , Bettayeb Maamar
Published: April 2024

A robust digital image watermarking system with a fractional-order discrete-time chaotic system and discrete wavelet transform-singular value decomposition is presented. The inclusion method inserts an encrypted image into the dynamics of an integer-order discrete-time chaotic system and the resulting cipher serves as a host image watermark. A watermarking function (DWT-SVD transform) watermarks a host image before the watermark is extracted and decrypted at the receiver. As a contribution, our suggested approach introduces a new watermarking system based on discrete-time chaotic systems, as well as a hybridization of integer and fractional-order systems to ensure the watermarking scheme’s robustness. Our method achieved good results in terms of robustness, with normalized cross correlation values above 0.99 when subjected to a range of attacks. Results of the simulation underline practicality and robustness achieved by this approach. They also indicate that the proposed system resists various attacks.
Towards galaxy cluster models in Aether-Scalar-Tensor theory: isothermal spheres and curiosities
Authors: Durakovic A. , Skordis C.
Published: April 2024

The Aether-Scalar-Tensor (AeST) theory is an extension of General Relativity (GR) which can support Modified Newtonian Dynamics (MOND) behaviour in its static
weak-field limit, and cosmological evolution resembling ΛCDM.
We consider static spherically symmetric weak-field solutions in this theory and show that the resulting equations can be reduced to a single equation for the gravitational potential.
The reduced equation has apparent isolated singularities at the zeros of the derivative of the potential and we show how these are removed
by evolving, instead, the canonical momentum of the corresponding Hamiltonian system that we find. We construct solutions in three cases: (i) in vacuum outside a bounded spherical object, (ii) within an extended prescribed source, and (iii) for an isothermal gas in hydrostatic equilibrium, serving as a simplified model for galaxy clusters.
We show that the oscillatory regime that follows the Newtonian and MOND regimes, obtained in previous works in the vacuum case, also persists for isothermal spheres, and we show that the gas density profiles in AeST can become more compressed than their Newtonian or MOND counterparts.
We construct the Radial Acceleration Relation (RAR) in AeST for isothermal spheres and find that it can display a peak, an enhancement with respect to the MOND RAR, at an acceleration range determined by the value of the AeST weak-field mass parameter, the mass of the system and the boundary value of the gravitational potential. For lower accelerations, the AeST RAR drops below the MOND expectation,
as if there is a negative mass density. Similar observational features of the galaxy cluster RAR have been reported. This illustrates the potential of AeST to address the shortcomings of MOND in galaxy clusters, but a full quantitative comparison with observations will require going beyond the isothermal case.
Microscopic ensemble bootstrap in phase space
Authors: Zhang Yu
Published: April 2024

The bootstrap method which has been studied under many quantum mechanical models turns out to be feasible in microcanonical ensembles as well. While the approach of Nakayama (2022 Mod. Phys. Lett. A 37 2250054) produces a sector when energy is negative, in this paper we report a method that has stronger constraints and results in a smaller region. We also study other models to demonstrate the effectiveness of our method.
Electronic structure and effective mass of pristine and Cl-doped CsPbBr3
Authors: Wei 魏 Zhiyuan 志远 , Wei 魏 Yu-Hao 愉昊 , Xu 徐 Shendong 申东 , Peng 彭 Shuting 舒婷 , Hashimoto Makoto , Lu 路 Donghui 东辉 , Pan 潘 Xu 旭 , Kuang 匡 Min-Quan 泯泉 , Xiao 肖 Zhengguo 正国 , He 何 Junfeng 俊峰
Published: April 2024

Organic–inorganic lead halide perovskites (LHPs) have attracted great interest owing to their outstanding optoelectronic properties. Typically, the underlying electronic structure would determinate the physical properties of materials. But as for now, limited studies have been done to reveal the underlying electronic structure of this material system, comparing to the huge amount of investigations on the material synthesis. The effective mass of the valance band is one of the most important physical parameters which plays a dominant role in charge transport and photovoltaic phenomena. In pristine CsPbBr3, the Fröhlich polarons associated with the Pb–Br stretching modes are proposed to be responsible for the effective mass renormalization. In this regard, it would be very interesting to explore the electronic structure in doped LHPs. Here, we report high-resolution angle-resolved photoemission spectroscopy (ARPES) studies on both pristine and Cl-doped CsPbBr3. The experimental band dispersions are extracted from ARPES spectra along both

Γ
¯

–

M
¯

–

Γ
¯

and

X
¯

–

M
¯

–

X
¯

high symmetry directions. DFT calculations are performed and directly compared with the ARPES data. Our results have revealed the band structure of Cl-doped CsPbBr3 for the first time, which have also unveiled the effective mass renormalization in the Cl-doped CsPbBr3 compound. Doping dependent measurements indicate that the chlorine doping could moderately tune the renormalization strength. These results will help understand the physical properties of LHPs as a function of doping.
Spectral micro-CT for simultaneous gold and iodine detection, and multi-material identification
Authors: Perion P. , Arfelli F. , Menk R.H. , Brombal L.
Published: April 2024

Multiple energy bin spectral micro-CT (SμCT) is an advanced imaging technique that allows multi-material decomposition according to their specific absorption patterns at a sub-100 μm scale. Typically, iodine is the preferred CT contrast agent for cardiovascular imaging, while gold nanoparticles have gained attention in recent years owing to their high absorption properties, biocompatibility and ability to target tumors.

In this work, we demonstrate the potential for multi-material decomposition through SμCT imaging of a test sample at the PEPI lab of INFN Trieste. The sample, consisting of gold, iodine, calcium, and water, was imaged using a Pixirad1/PixieIII chromatic detector with multiple energy thresholds and a wide spectrum (100 kV) produced by a micro-focus X-ray tube. The results demonstrate the simultaneous detection and separation of the four materials at a spatial scale of 35 μm, suggesting the potential of this technique in improving material detectability and quantification in a range of pre-clinical applications, including cardiovascular and oncologic imaging.
Detection of gastrointestinal foreign bodies in pets using single-grid-based dark-field X-ray imaging
Authors: Lee Jonghyeok , Lim Hyunwoo , Lee Hunwoo , Cho Hyosung
Published: April 2024

Gastrointestinal foreign bodies (GI-FBs) occur when pets consume non-digestible items that
do not readily pass through the stomach or intestines. While some GI-FBs pass through, many become
lodged along the gastrointestinal tract and cause discomfort, often leading to
sickness. Conventional absorption-based radiography is widely used to detect GI-FBs in
pets. However, detecting low-density FBs, such as wood, plastic, clothing, and sticks, is
typically difficult using conventional radiography. This study presents a novel approach for
detecting low-density GI-FBs in pets by using single-grid-based dark-field X-ray imaging
(SG-DFXI). It obtains microstructural information from small-angle X-ray scattering (SAXS) of the
sample using a conventional X-ray source and grid. SG-DFXI requires minimal exposure and system
setup and is specifically utilized to detect low-density materials that are invisible when using
conventional radiography. To validate the efficacy of the proposed method, an experiment was
conducted on a mouse phantom attached to a wooden chopstick as a low-density GI-FB. Quantitative
evaluation was performed using image quality metrics of the contrast-to-noise ratio (CNR) and
relative contrast gain (RCG). The CNR value measured in the dark-field image obtained with an
autocorrelation length of ξG
= 294 nm was 4.59, approximately 5.4
times larger than that of the absorption image obtained in the same imaging setup. In addition,
the RCG characteristics improved as the autocorrelation length of the system increased; the RCG
value for ξG
= 294 nm was 5.4, approximately 3.2 times larger than
that for ξG
= 194 nm. Thus, increasing the autocorrelation length of
the system is critical to improve its ability to detect low-density FBs. Consequently, SG-DFXI
appears to be a promising method that can be used effectively and easily to detect GI-FBs in pets,
which are barely visible in absorption images.
Data Processing Engine (DPE): data analysis tool for particle tracking and mixed radiation field characterization with pixel detectors Timepix
Authors: Marek L. , Granja C. , Jakubek J. , Ingerle J. , Turecek D. , Vuolo M. , Oancea C.
Published: April 2024

Hybrid semiconductor pixelated detectors from the Timepix family are advanced detectors for online particle tracking, offering energy measurement and precise time stamping capabilities for particles of various types and energies. This inherent capability makes them highly suitable for various applications, including imaging, medical fields such as radiotherapy and particle therapy, space-based applications aboard satellites and the International Space Station, and industrial applications. The data generated by these detectors is complex, necessitating the development and deployment of various analytical techniques to extract essential information.
For this purpose, and to aid the Timepix user community, it was designed and developed the
“Data Processing Engine” (DPE) as an advanced tool for data processing designed explicitly for Timepix detectors. The functionality of the DPE is structured into three distinct processing levels: i) Pre-processing: this phase involves clusterization and the application of necessary calibrations and corrections. ii) Processing: this stage includes particle classification, employing machine learning algorithms, and the recognition of radiation fields. iii) Post-processing: involves various analyses, such as directional analysis, coincidence analysis, frame analysis, Compton directional analysis, and the generation of physics products, are performed. The core of the DPE is supported by an extensive experimental database containing calibrations and referential radiation fields of typical environments, including protons, ions, electrons, gamma rays and X rays, as well as thermal and fast neutrons. To enhance accessibility, the DPE is implemented into various user interface platforms such as a command-line tool, an application programming interface, and as a graphical user interface in the form of a web portal. The DPE's broad utility is exemplified through its integration into various applications and developments.
Worldviews more than experience predict Californians’ support for wildfire risk mitigation policies
Authors: Howe Alexander A , Blomdahl Erika M , Smith-Eskridge Ellie , Pinto Dakoeta R , Brunson Mark W , Howe Peter D , Huntly Nancy J , Klain Sarah C
Published: April 2024

California must adapt to increasing wildfire activity concurrent with climate change and expanding housing development in fire-prone areas. Recent decades have seen record-breaking fire activity, economic costs, and human health impacts. Residents more frequently face home evacuations, prolonged periods of unhealthy air quality, and power shut-offs. Understanding how these experiences influence support for risk mitigation policies is essential to inform action on climate and fire adaptation. To better understand linkages between experience and policy support, we surveyed California residents (n = 645) about their wildfire-related experiences, risk perceptions, and support for 18 wildfire risk mitigation policies. To assess how the relationship between policy support and wildfire experience is modulated by preexisting worldviews, we measured the extent to which respondents are motivated by individualistic or communitarian values as proposed in the cultural theory of risk. We surveyed residents across a gradient of wildfire impacts, spatially stratifying residences based on wildland-urban-interface type and proximity to large 2020 wildfires. Support was generally high for most policies, though most respondents opposed incorporating future risk into insurance rates and coverage. Policy support models showed that communitarian worldviews were more consistently associated with greater support for diverse wildfire mitigation policies than were measures of recent experience with wildfire. These results suggest that California residents within our sample regions already support many wildfire risk mitigation strategies, and preexisting societal beliefs are a stronger predictor of these views than personal experiences with wildfire. Policy-makers can utilize this understanding to focus on crafting policies and messaging that resonates with individualistic values.
Satellite-detected large CO2 release in southwestern North America during the 2020–2021 drought and associated wildfires
Authors: Chen Hui , He Wei , Liu Jinxiu , Nguyen Ngoc Tu , Chevallier Frédéric , Yang Hua , Lv Yiming , Huang Chengcheng , Rödenbeck Christian , Miller Scot M , Jiang Fei , Liu Junjie , Johnson Matthew S , Philip Sajeev , Liu Zhiqiang , Zeng Ning , Basu Sourish , Baker David F
Published: April 2024

Southwestern North America (SWNA) continuously experienced megadroughts and large wildfires in 2020 and 2021. Here, we quantified their impact on the terrestrial carbon budget using net biome production (NBP) estimates from an ensemble of atmospheric inversions assimilating in-situ CO2 and Carbon Observatory–2 (OCO-2) satellite XCO2 retrievals (OCO-2 v10 MIP Extension), two satellite-based gross primary production (GPP) datasets, and two fire CO2 emission datasets. We found that the 2020–2021 drought and associated wildfires in SWNA led to a large CO2 loss, an ensemble mean of 95.07 TgC estimated by the satellite inversions using both nadir and glint XCO2 retrievals (LNLG) within the OCO-2 v10 MIP, greater than 80% of SWNA’s annual total carbon sink. Moreover, the carbon loss in 2020 was mainly contributed by fire emissions while in 2021 mainly contributed by drought impacts on terrestrial carbon uptake. In addition, the satellite inversions indicated the huge carbon loss was mainly contributed by fire emissions from forests and grasslands along with carbon uptake reductions due to drought impacts on grasslands and shrublands. This study provides a process understanding of how some droughts and following wildfires affect the terrestrial carbon budget on a regional scale.
SO(2,2) representations in polar coordinates and Pöschl-Teller potentials
Authors: Blazquez M , Negro Javier
Published: April 2024

This work is devoted to show the interest of polar coordinates in the description of some unitary irreducible representations (or uir’s) of the

S
O
(
2
,
2
)

group where the support space are functions on the three dimensional pseudosphere

H

R

2
,
2

. We will show that the differential equations associated to such uir’s can be interpreted as quantum systems including centrifugal terms; in our case these equations lead to one-dimensional Pöschl-Teller systems. The solutions to these equations are computed and the uir’s are characterized in terms of polar coordinates. We will also discuss briefly the more standard pseudospherical coordinates on

H

R

2
,
2

in order to appreciate some of the differences. We will consider as well the (maximally superintegrable) free classical systems defined on the real pseudosphere

H

R

2
,
2

symmetric under

S
O
(
2
,
2
)

. The constants of motion are found and they are applied to find some bounded (therefore periodic) and unbounded orbits also in terms of polar coordinates.
Thickness dependent tribological and magnetic behavior of two-dimensional cobalt telluride (CoTe2)
Authors: Slathia Surbhi , Wei Cencen , Tripathi Manoj , Tromer Raphael , Negedu Solomon Demiss , Boland Conor S , Sarkar Suman , Galvao Douglas S , Dalton Alan , Tiwary Chandra Sekhar
Published: April 2024

Two-dimensional (2D) layered transition-metal based tellurides (chalcogens) are known to harness their surface atoms’ characteristics to enhance topographical activities for energy conversion, storage, and magnetic applications. The gradual stacking of each sheet alters the surface atoms’ subtle features such as lattice expansion, leading to several phenomena and rendering tunable properties. Here, we have evaluated thickness-dependent mechanical properties (nanoscale mechanics, tribology, potential surface distributions, interfacial interaction) of 2D CoTe2 sheets and magnetic behavior using surface probe techniques. The experimental observations are further supported and explained with theoretical investigations: density functional theory and molecular dynamics. The variation in properties observed in theoretical investigations unleashes the crucial role of crystal planes of the CoTe2. The presented results are beneficial in expanding the use of the 2D telluride family in flexible electronics, piezo sensors, tribo-generators, and next-generation memory devices.
Effect of super absorbent polymer mixing method on shrinkage performance of cast-in-place concrete confined by existing concrete
Authors: Li Dajiang , Zuo Zhaonan , Huang Shaojie , Weng Yijian , Liu Xiaoyu , Rong Hongliu
Published: April 2024

To study the effect of different super absorbent polymer (SAP) mixing methods on mechanical and shrinkage properties of internal curing concrete, SAP mixing mode was used as the study variable, and simulated the bridge leveling structure. The flow performance test, mechanical performance test, free shrinkage test, restrained shrinkage test and scanning electron microscope observation test were carried out on the internal curing concrete. The influence of different mixing methods on the flow properties, mechanical properties, shrinkage properties and microstructure of internal curing concrete were analyzed. The results showed that the amount of mixing water had a great influence on the fluidity when adding pre-absorbent SAP; The effect of SAP on the mechanical properties is minimal when the dosage is 0.2% of the mass of cementing material; Pre-absorbent SAP has the best effect on improving shrinkage cracks of concrete; SAP stored water at the initial stage of hydration, promoted the generation of hydrolysis products, prolong the hydration process, filled the gap inside the concrete, and improved the anti-cracking performance. It is recommended that SAP should be partially pre-absorbed.
Processing-structure-property relationships in practical thin solid-electrolyte separators for all-solid-state batteries
Authors: Li Junhao , Kim Soochan , Mezzomo Lorenzo , Chart Yvonne , Aspinall Jack , Ruffo Riccardo , Pasta Mauro
Published: April 2024

Scalable processing of thin and robust solid-electrolyte (SE) separators is key for the commercialization of high-energy all-solid-state batteries (ASSBs). Herein, we report the preparation of Li6PS5Cl-based thin SE separators incorporating suitable binders for potential use in ASSBs by two scalable wet processing techniques: tape-casting with nitrile-butadiene rubber (NBR) and calendering with carboxylated nitrile butadiene rubber (XNBR). By means of tensile testing and electrochemical impedance spectroscopy, the influence of processing on the mechanical as well as the electrochemical properties of the resulting thin SE separators is investigated. A trade-off between the mechanical and electrochemical properties is observed, which is due to the inextricably linked microstructures (particle size, binder content and distribution, and porosity) induced by the two different processes. Thin SE separators prepared using the tape-casting method with the more well-distributed binder network demonstrate superior tensile mechanical properties compared to the ones prepared by the calendering method. The results provide insights into the processing-structure-property relationships of the thin SE separators, which will contribute to advancing the application of practical thin solid electrolytes in ASSBs.
A novel method for studying the wind speed probability distribution and estimating the average wind energy density
Authors: Wang Lingzhi , Zhang Xinbo
Published: April 2024

Traditional distribution models generally have large fitting errors at low wind speeds and poor fitting effects at multi-peak wind speed distributions. In this paper, a novel approach is proposed to fit different wind speed distributions, introducing a Gumbel distribution into common hybrid distribution models. The model parameters are solved by a combination of snake optimizer and nonlinear least squares (SO-NLS), using the optimal values obtained by the nonlinear least squares method as a set of initial input vectors for the snake optimizer. Simulation experiments were conducted using multi-peak wind speed distribution datasets with varying characteristics, comparing the fitting performance of the improved hybrid models against the conventional Weibull, Normal, and Rayleigh hybrid models. The results show that the proposed approach improved the model fit effects, particularly at low wind speeds, in all five experimental datasets. In most cases, the overall fitting effects were also improved. Furthermore, the validity and superiority of the improved hybrid models were further verified by comparing the estimated average wind energy density. Meanwhile, the experimental results also verified that SO-NLS not only yielded better optimization results but also accelerated the convergence speed than the snake optimizer. The improvements presented in this study effectively address the problem of large fitting errors at the low wind speed sections of the distribution, providing a theoretical basis for wind farm planning and design.
Sensitivity improvement in gate engineered technique dielectric modulated GaN MOSHEMT with InGaN notch for label-free biosensing
Authors: Mishra Girish Shankar , Mohankumar N , Singh Sankalp Kumar
Published: April 2024

This paper focuses on the impact of gate-engineered dielectric-modulated GaN MOSHEMT with InGaN notch on sensitivity enhancement for label-free biosensing. The novelty of this study utilizes the charge-plasma effect induced by the dual metal gate (DMG) technology adopted to realize the effect of sensitivity on different biomolecules. Moreover, the presence of an InGaN notch enhances carrier confinement in the 2DEG, subsequently improving the threshold voltage and device sensitivity at the AlGaN/GaN interface. The maximum drain current, IDS of 4.602 A mm−1, transconductance, gm of 18 mS/mm, and sensitivity has been improved by around 61% for the Uricase biomolecule by introducing the dual metal gate technology. The work function difference of the two metal gates suppresses the Short Channel Effects (SCEs) and hot carrier effects in DMG MOSHEMT, thereby screening the drain potential variations by the gate near the drain. In addition, increased carrier transport efficiency results from a more consistent electric field along the channel. All the simulations are carried out using the Sentaurus TCAD simulator, and the results imply the feasibility of gate-engineered GaN MOSHEMT for label-free biosensing.
Deep learning-based spatiotemporal multi-event reconstruction for delay line detectors
Authors: Knipfer Marco , Meier Stefan , Volk Tobias , Heimerl Jonas , Hommelhoff Peter , Gleyzer Sergei
Published: April 2024

Accurate observation of two or more particles within a very narrow time window has always been a challenge in modern physics. It creates the possibility of correlation experiments, such as the ground-breaking Hanbury Brown–Twiss experiment, leading to new physical insights. For low-energy electrons, one possibility is to use a Microchannel plate with subsequent delay lines for the readout of the incident particle hits, a setup called a Delay Line Detector. The spatial and temporal coordinates of more than one particle can be fully reconstructed outside a region called the dead radius. For interesting events, where two electrons are close in space and time, the determination of the individual positions of the electrons requires elaborate peak finding algorithms. While classical methods work well with single particle hits, they fail to identify and reconstruct events caused by multiple nearby particles. To address this challenge, we present a new spatiotemporal machine learning model to identify and reconstruct the position and time of such multi-hit particle signals. This model achieves a much better resolution for nearby particle hits compared to the classical approach, removing some of the artifacts and reducing the dead radius a factor of eight. We show that machine learning models can be effective in improving the spatiotemporal performance of delay line detectors.
Polymorphisms, their associated operator theory, self-similar fractals, and harmonic analysis
Authors: Jorgensen Palle , Tian James
Published: April 2024

In this paper we develop rigorously the theory and applications of Polymorphisms. The list of topics covered includes: areas of probability theory, analysis of Markov maps, transition operators, joinings of measure spaces, and applications to harmonic and stochastic analysis of self-similar (fractal) measures.
Fractal interpolation over curves
Authors: Massopust Peter
Published: April 2024

This paper introduces the novel concept of fractal interpolation over curves in Banach spaces. The contents are based on the usual methodologies involving the fractal interpolation problem over intervals but the current approach considerably extends and generalizes them and paves the way to fractal interpolation over Banach submanifolds.
Computability in dynamical systems
Authors: Burr Michael , Wolf Christian
Published: April 2024

We present an introduction to the area of computability in dynamical systems. One of the central questions in this area is if relevant dynamical objects can be algorithmically presented by a Turing machine. After providing an overview of the relevant objects we discuss recent results concerning the computability of the entropy for symbolic systems and the computability of Julia sets as well as their Brolin–Lyubich measures.
Recurrence properties of superadditive processes and universally good weights
Authors: Çömez Doğan
Published: April 2024

In this article recurrence properties of a class of strongly bounded superadditive processes are studied at some length. In particular, four generalizations of Fürstenberg’s multiple recurrence theorem are extended to the setting of such superadditive processes. Having these recurrence properties in hand, it is observed that such superadditive processes define universally good weights for various type of ergodic averages.
Unmating of expanding Thurston maps with Julia set 𝕊²
Authors: Wilkerson Mary
Published: April 2024

Every expanding Thurston map

f
f

without periodic critical points is known to have an iterate

f
n

f^n

which is the topological mating of two polynomials. This has been examined by Kameyama and Meyer; the latter has offered an explicit construction for finding two polynomials in the unmating of the iterate. Initializing Meyer’s algorithm depends on an invariant Jordan curve through the postcritical set of

f
f

–but we propose adjustments to this unmating algorithm for Kameyama’s more general case where there exists a curve which is fully

f
f

-invariant up to homotopy and not necessarily simple. When

f
f

is a critically pre-periodic expanding Thurston map, extending the algorithm to accommodate non-Jordan curves in this manner may allow us to unmate without iterates.
Locally trivial monodromy of moduli spaces of sheaves on K3 surfaces
Authors: Onorati Claudio , Perego Arvid , Rapagnetta Antonio
Published: April 2024

In this paper we study monodromy operators on moduli spaces

M
v

(
S
,
H
)

M_v(S,H)

of sheaves on K3 surfaces with non-primitive Mukai vectors

v
v

. If we write

v
=
m
w

v=mw

, with

m
>
1

m>1

and

w
w

primitive, then our main result is that the inclusion

M
w

(
S
,
H
)
→

M
v

(
S
,
H
)

M_w(S,H)\to M_v(S,H)

as the most singular locus induces an isomorphism between the monodromy groups of these symplectic varieties, allowing us to extend to the non-primitive case a result of Markman.
WHAMM functions in kidney reabsorption and polymerizes actin to promote autophagosomal membrane closure and cargo sequestration
Authors: Coulter Alyssa M. , Cortés Valerie , Theodore Corey J. , Cianciolo Rachel E. , Korstanje Ron , Campellone Kenneth G.
Published: April 2024

The actin cytoskeleton is essential for many functions of eukaryotic cells, but the factors that nucleate actin assembly are not well understood at the organismal level or in the context of disease. To explore the function of the actin nucleation factor WHAMM in mice, we examined how Whamm inactivation impacts kidney physiology and cellular proteostasis. We show that male WHAMM knockout mice excrete elevated levels of albumin, glucose, phosphate, and amino acids, and display structural abnormalities of the kidney proximal tubule, suggesting that WHAMM activity is important for nutrient reabsorption. In kidney tissue, the loss of WHAMM results in the accumulation of the lipidated autophagosomal membrane protein LC3, indicating an alteration in autophagy. In mouse fibroblasts and human proximal tubule cells, WHAMM and its binding partner the Arp2/3 complex control autophagic membrane closure and cargo receptor recruitment. These results reveal a role for WHAMM-mediated actin assembly in maintaining kidney function and promoting proper autophagosome membrane remodeling.
Bacterial growth dynamics in a rhythmic symbiosis
Authors: Yang Liu , Lawhorn Susannah , Bongrand Clotilde , Kosmopoulos James C. , Kuwabara Jill , VanNieuwenhze Michael , Mandel Mark J. , McFall-Ngai Margaret , Ruby Edward
Published: April 2024

The symbiotic relationship between the bioluminescent bacterium Vibrio fischeri and the bobtail squid Euprymna scolopes serves as a valuable system to investigate bacterial growth and peptidoglycan (PG) synthesis within animal tissues. To better understand the growth dynamics of V. fischeri in the crypts of the light-emitting organ of its juvenile host, we showed that, after the daily dawn-triggered expulsion of most of the population, the remaining symbionts rapidly proliferate for ∼6 h. At that point the population enters a period of extremely slow growth that continues throughout the night until the next dawn. Further, we found that PG synthesis by the symbionts decreases as they enter the slow-growing stage. Surprisingly, in contrast to the most mature crypts (i.e., Crypt 1) of juvenile animals, most of the symbiont cells in the least mature crypts (i.e., Crypt 3) were not expelled and, instead, remained in the slow-growing state throughout the day, with almost no cell division. Consistent with this observation, the expression of the gene encoding the PG-remodeling enzyme, L,D-transpeptidase (LdtA), was greatest during the slowly growing stage of Crypt 1 but, in contrast, remained continuously high in Crypt 3. Finally, deletion of the ldtA gene resulted in a symbiont that grew and survived normally in culture, but was increasingly defective in competing against its parent strain in the crypts. This result suggests that remodeling of the PG to generate additional 3–3 linkages contributes to the bacterium’s fitness in the symbiosis, possibly in response to stresses encountered during the very slow-growing stage.
Chinese Visceral Adiposity Index Predict Prehypertension Progression and Regression: A Prospective Cohort Study Involving Middle-Aged and Older Adults
Authors: Dai Senjie , Yang Yang , Wang Dongying
Published: April 2024

BACKGROUND

Limited data are published on the relationship of the Chinese visceral adiposity index (CVAI) with prehypertension progression or regression. Therefore, we investigated this association through the China Health and Retirement Longitudinal Study.

METHODS

Participants with prehypertension were assigned to two groups according to baseline CVAI, and after 4 years of follow-up, their blood pressure was analyzed for deterioration or improvement. We constructed logistic regression models for assessing the association of CVAI with the progression or regression of prehypertension. A restricted cubic spline (RCS) model was utilized for determining the dose–response association. Subgroup analysis and sensitivity analysis were also conducted.

RESULTS

The study included 2,057 participants with prehypertension. During the follow-up, 695 participants progressed to hypertension, 561 participants regressed to normotension, and 801 participants remained as prehypertensive. An association was observed between a high CVAI value and a higher incidence of progression to hypertension and between a high CVAI value and a lower incidence of regression to normotension (OR = 1.66 and 0.58, 95% CI: 1.35–2.05 and 0.47–0.73, respectively). The RCS model exhibited a linear association between CVAI and prehypertension progression and regression (all P for non-linear > 0.05). The results of the subgroup and sensitivity analyses agreed with those of the primary analysis.

CONCLUSIONS

A significant association was noted between CVAI and prehypertension progression and regression. Thus, as part of the hypertension prevention strategy, monitoring CVAI is crucial in individuals with prehypertension.
VirusPredictor: XGBoost-based software to predict virus-related sequences in human data
Authors: Liu Guangchen , Chen Xun , Luan Yihui , Li Dawei
Published: April 2024

Motivation

Discovering disease causative pathogens, particularly viruses without reference genomes, poses a technical challenge as they are often unidentifiable through sequence alignment. Machine learning prediction of patient high-throughput sequences unmappable to human and pathogen genomes may reveal sequences originating from uncharacterized viruses. Currently, there is a lack of software specifically designed for accurately predicting such viral sequences in human data.

Results

We developed a fast XGBoost method and software VirusPredictor leveraging an in-house viral genome database. Our two-step XGBoost models first classify each query sequence into one of three groups: infectious virus, endogenous retrovirus (ERV) or non-ERV human. The prediction accuracies increased as the sequences became longer, i.e. 0.76, 0.93, and 0.98 for 150–350 (Illumina short reads), 850–950 (Sanger sequencing data), and 2000–5000 bp sequences, respectively. Then, sequences predicted to be from infectious viruses are further classified into one of six virus taxonomic subgroups, and the accuracies increased from 0.92 to >0.98 when query sequences increased from 150–350 to >850 bp. The results suggest that Illumina short reads should be de novo assembled into contigs (e.g. ∼1000 bp or longer) before prediction whenever possible. We applied VirusPredictor to multiple real genomic and metagenomic datasets and obtained high accuracies. VirusPredictor, a user-friendly open-source Python software, is useful for predicting the origins of patients’ unmappable sequences. This study is the first to classify ERVs in infectious viral sequence prediction. This is also the first study combining virus sub-group predictions.

Availability and implementation

www.dllab.org/software/VirusPredictor.html.
rnaCrosslinkOO: an object-oriented R package for the analysis of RNA structural data generated by RNA crosslinking experiments
Authors: Price Jonathan L , Ziv Omer , Pinckert Malte L , Lim Andrew , Miska Eric A
Published: April 2024

RNA (ribonucleic acid) molecules have secondary and tertiary structures in vivo which play a crucial role in cellular processes such as the regulation of gene expression, RNA processing and localization. The ability to investigate these structures will enhance our understanding of their function and contribute to the diagnosis and treatment of diseases caused by RNA dysregulation. However, there are no mature pipelines or packages for processing and analyzing complex in vivo RNA structural data. Here, we present rnaCrosslinkOO (RNA Crosslink Object-Oriented), a novel software package for the comprehensive analysis of data derived from the COMRADES (Crosslinking of Matched RNA and Deep Sequencing) method. rnaCrosslinkOO offers a comprehensive pipeline from raw sequencing reads to the identification and comparison of RNA structural features. It includes read processing and alignment, clustering of duplexes, data exploration, folding and comparisons of RNA structures. rnaCrosslinkOO also enables comparisons between conditions, the identification of inter-RNA interactions, and the incorporation of reactivity data to improve structure prediction.

Availability and implementation

rnaCrosslinkOO is freely available to noncommercial users and implemented in R, with the source code and documentation accessible at https://CRAN.R-project.org/package=rnaCrosslinkOO. The software is supported on Linux, macOS, and Windows platforms.