bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deviations and similarities between landauer’s approach and the multi-electronic classical master equation in describing nanoscale transport
Authors: Moreira Augusto C L , de Melo Celso P 
Published: August 2023

Abstract
In this work, we show that the classical master equation (CME) treatment—with the rates obtained via the Fermi golden rule—and the elastic scattering (ES) approach give the same results for a system composed of two states/one level when considering the approximations of (i) non-interacting limit, i.e., the electronic structure of the N-particle states remains frozen even in the presence of an extra particle, (ii) wide-band limit (WBL) approximation, and (iii) excited states are discarded. Although the predictions of these two approaches ‘deviate’ from each other when more states and/or levels are considered, under the conditions of strong coupling limit and symmetric contacts both treatments capture the same physics involved in the transport process. For other situations—such as asymmetric coupling and/or weak metal–organic coupling—the predictions of these two theories do not agree with each other. Finally, even considering that in our treatment the electronic structure of the system is described at a tight binding level, the corresponding results clearly show the situations where the similarities and differences between the CME and ES approaches can be identified.
Shake-off effect on the portions of energy reemitted by gold atom upon the cascade decay of vacancies in its K to O shells
Authors: Chaynikov A P , Kochur A G , Dudenko A I , Yavna V A 
Published: August 2023

Abstract
Cascade decays of single vacancies in K to O shells of the gold atom are simulated by straightforward construction and analysis of the cascade decay trees. Portions of energies (a) absorbed by initially ionized Au atom, (b) reemitted by cascade-produced electrons, and (c) reemitted by cascade-produced photons are calculated with taking into account the shake-off processes caused by the change of atomic core potential during cascade transitions. Au atom absorbs noticeable amount of energy acquired in photoionization act only when ionized in its N and O shells, 33%–45% and 41%–54%, respectively. Except for the case of K-ionization, most of the energy is reemitted by cascade electrons: 57%–64%, 77%–85%, 55%–67%, and 46%–59% during the decay of vacancies in L, M, N, and O shells. Energies carried away by the cascade photons are only important for initial vacancies in K (89%) and L (29%–39%) shells. Inclusion of the shake-off branches in the decay trees increase substantially their complexity, however it leads to comparatively small corrections to calculated portions of energy redistributed through channels a, b, and c. This supports earlier qualitative prediction of small possible effect of the SO processes on the cascades in heavy atoms.
Sensing and control the static deflection of a cantilever beam by using piezoelectric patches
Authors: Kumar Lokesh , Bagha Ashok Kumar , Singh Kiran , Kumar Sanjay , Kumar Sanjeev 
Published: August 2023

Abstract
Different mechanical structures when comes under static and dynamic loadings then they respond. It is very important to sense it so that the dynamic behavior of the structure in terms of natural frequencies, its mode shapes, and viscous damping coefficients can be successfully predicted or measured. The accurate prediction of the dynamic response of the oscillating structure always plays an important role to design its physical parameters. However, in this paper, the simulated and experimental study is conducted to accurately sense the static deflection of the cantilever beam by using piezoelectric patches. The accurate prediction of the static deflection of the beam and its control through piezoelectric patches is the novelty of the present work. Mostly, the finite element model of the beam is developed to predict its dynamic behavior. The finite element modeling provides an approximate solution. In this regard, the finite element model updating technique such as the direct updating algorithm is used in this study to correct the simulated finite element model of the beam. The updated simulated finite element model is then used to predict the accurate value of the static deflection. It is observed that the maximum percentage error between the predicted and measured static deflection is 29.1%. The updated simulated finite element model is also used to design the controller. The direct output feedback controller is developed and it is found that the static deflection of the beam has been reduced by 46.65%.
Some physical analysis of quaternary CuNiSbS powder for optoelectronic applications
Authors: Saleh Hisham A , Azab A A , Dahy T M 
Published: August 2023

Abstract
Novel quaternary CuNiSbS chalcogenide material has been successfully prepared using a simple co-precipitation method using a mixture of solutions of the constituent elements in a chemical formula.The structure and morphological characterizations of the prepared material in powder form wereperformed via x-ray diffraction, a High-resolution transmission electron microscope (HRTEM), and a Scanning electron microscope (SEM). FTIR and diffuse reflectance spectrum of the prepared material were conducted to provide valuable information about the main absorption bands besides the energy optical band gap of the material. ACconductivity and the dielectric properties of the prepared materialusingbroadband dielectricspectroscopy (BDS) besides a magnetic analysis via a vibrating sample magnetometer (VSM) were also investigated.
A foreground-immune CMB-cluster lensing estimator
Authors: Levy Kevin , Raghunathan Srinivasan , Basu Kaustuv 
Published: August 2023

Abstract
Galaxy clusters induce a distinct dipole pattern in the cosmic microwave back-ground (CMB) through the effect of gravitational lensing.
Extracting this lensing signal will enable us to constrain cluster masses, even for high redshift clusters (z ≳ 1) that are expected to be detected by future CMB surveys.
However, cluster-correlated foreground signals, like the kinematic and thermal Sunyaev-Zel'dovich (kSZ and tSZ) signals, present a challenge when extracting the lensing signal from CMB temperature data.
While CMB polarization-based lensing reconstruction is one way to mitigate these foreground biases, the sensitivity from CMB temperature-based reconstruction is expected to be similar to or higher than polarization for future surveys.
In this work, we extend the cluster lensing estimator developed in [1] to CMB temperature and test its robustness against systematic biases from foreground signals.
We find that the kSZ signal only acts as an additional source of variance and provide a simple stacking-based approach to mitigate the bias from the tSZ signal.
Additionally, we study the bias induced due to uncertainties in the cluster positions and show that they can be easily mitigated.
The estimated signal-to-noise ratio (SNR) of this estimator is comparable to other standard lensing estimators such as the maximum likelihood (MLE) and quadratic (QE) estimators.
We predict the cluster mass uncertainties from CMB temperature data for current and future cluster samples to be: 6.6% for SPT-3G with 7,000 clusters, 4.1% for SO and 3.9% for SO + FYST with 25,000 clusters, and 1.8% for CMB-S4 with 100,000 clusters.
Rotating black holes embedded in a cosmological background for scalar-tensor theories
Authors: Babichev Eugeny , Charmousis Christos , Lecoeur Nicolas 
Published: August 2023

Abstract
We present solutions of DHOST theories describing a rotating black hole embedded in an
expanding universe. The solution is constructed by conformal transformation of a stealth Kerr(-de
Sitter) black hole. The conformal factor depends explicitly on the scalar field — but not on its
derivative — and defines the new theory. The scalar field of the stealth Kerr(-de Sitter)
solution depends on time, leading to the time-dependence of the obtained conformal metric, with
cosmological asymptotics at large distances. We study the properties of the obtained metric by
considering regular null geodesic congruences, and identify trapping black hole and
cosmological horizons.
Localized estimation of electromagnetic sources underlying event-related fields using recurrent neural networks
Authors: O’Reilly Jamie A , Zhu Judy D , Sowman Paul F 
Published: August 2023

Abstract

Objective. To use a recurrent neural network (RNN) to reconstruct neural activity responsible for generating noninvasively measured electromagnetic signals. Approach. Output weights of an RNN were fixed as the lead field matrix from volumetric source space computed using the boundary element method with co-registered structural magnetic resonance images and magnetoencephalography (MEG). Initially, the network was trained to minimise mean-squared-error loss between its outputs and MEG signals, causing activations in the penultimate layer to converge towards putative neural source activations. Subsequently, L1 regularisation was applied to the final hidden layer, and the model was fine-tuned, causing it to favour more focused activations. Estimated source signals were then obtained from the outputs of the last hidden layer. We developed and validated this approach with simulations before applying it to real MEG data, comparing performance with beamformers, minimum-norm estimate, and mixed-norm estimate source reconstruction methods. Main results. The proposed RNN method had higher output signal-to-noise ratios and comparable correlation and error between estimated and simulated sources. Reconstructed MEG signals were also equal or superior to the other methods regarding their similarity to ground-truth. When applied to MEG data recorded during an auditory roving oddball experiment, source signals estimated with the RNN were generally biophysically plausible and consistent with expectations from the literature. Significance. This work builds on recent developments of RNNs for modelling event-related neural responses by incorporating biophysical constraints from the forward model, thus taking a significant step towards greater biological realism and introducing the possibility of exploring how input manipulations may influence localised neural activity.
Core transport modelling of the DTT full power scenario using different fuelling strategies
Authors: Baiocchi B. , Aucone L. , Casiraghi I. , Figini L. , Koechl F. , Mantica P. 
Published: August 2023

Abstract
A theory-based integrated modelling work of plasma response to deuterium fuelling in the new Divertor Tokamak Test facility (DTT) is performed, using the 1.5D transport code JETTO with the quasi-linear anomalous transport model QuaLiKiz for the core region. The full power DTT scenario E1 is investigated. It is characterised by 28.8 MW of Electron Cyclotron Resonance Heating, 10 MW of Neutral Beam Injection and 6 MW of Ion Cyclotron Resonance Heating to the plasma. Plasma density and temperature profile evolution is calculated up to the separatrix using two different fuelling methods, gas puffing and pellet injection, and two different seeding gases, argon and neon. To sustain the desired pedestal density level with gas puffing a big amount of neutral flux at the separatrix is needed. The feasibility limits of the pumping system are exceeded, regardless of the type of impurity introduced, thus making the use of pellets mandatory. The simulations performed with pellet injection as fuelling method predict that the pedestal density is well sustained with realistic parameters foreseen for the DTT pellet injector. Strong dependence of the core density on the electron cyclotron resonance (ECR) power deposition profile is found. Trapped Electron Modes dominance, low outward flux and strongly hollow density in the inner core region are foreseen with central peaked ECR power deposition profile. Ion Temperature Gradient modes dominance, inward flux and robust density sustainment on the whole radial interval are predicted for spread ECR power deposition, though with central density close to the ECR cut-off limit and with peaked impurity densities. An intermediate deposition extension is found to sustain the whole density profile and to obtain flatter core densities, as previously predicted for the reference full power DTT scenario by fixed pedestal simulations. The ECR deposition is negligibly modified by refraction changes both during a single pellet cycle and after several pellet cycles, indicating full compatibility between the ECR system and the pellet injection system.
Transition in particle transport under resonant magnetic perturbations in a tokamak
Authors: Kim S.K. , Logan N.C. , Becoulet M. , Hoelzl M. , Hu Q. , Huijsmans G.T.A. , Pamela S.J.P. , Yu Q. , Yang S.M. , Paz-soldan C. , Kolemen E. , Park J.-K. 
Published: August 2023

Abstract
Nonlinear 3D MHD simulations and validations reveal that the hybrid particle-MHD transport is a key process for driving the pump-out in the presence of Resonant Magnetic Perturbations (RMPs) in the KSTAR tokamak. Particle transport and the resulting density pump-out by RMPs are shown to be composed of not only the classical flow convection near magnetic islands due to polarization but also the neoclassical ion diffusion across perturbed magnetic surfaces. The latter is known as the Neoclassical Toroidal Viscosity (NTV) and is integrated into nonlinear MHD simulations here for the first time, revealing that the two-stage pump-outs observed in KSTAR experiments are reproduced only with such integrated nonlinear MHD and transport evolution. Near-resonant responses, which have received less attention than the resonant response, play distinct roles in the pump-out along with the island formation. In addition, this modeling is used to investigate the pump-outs in double-null-like plasmas and numerically capture the effect of the double-null shape on the pump-outs, which may explain the difficulty of Edge Localized Mode (ELM) suppression access in double-like plasmas. This reveals new aspects of the impact toroidal geometry and mode coupling have on 3D physics and reveals the importance of near-resonant components in suppressing ELMs.
3D vascularized microphysiological system for investigation of tumor-endothelial crosstalk in anti-cancer drug resistance
Authors: Kim Seunggyu , Park Joonha , Ho Jin-Nyoung , Kim Danhyo , Lee Sangchul , Jeon Jessie S 
Published: August 2023

Abstract
Despite the advantages of microfluidic system in drug screening, vascular systems responsible for the transport of drugs and nutrients have been hardly considered in the microfluidic-based chemotherapeutic screening. Considering the physiological characteristics of highly vascularized urinary tumors, we here investigated the chemotherapeutic response of bladder tumor cells using a vascularized tumor on a chip. The microfluidic chip was designed to have open-top region for tumor sample introduction and hydrophilic rail for spontaneous hydrogel patterning, which contributed to the construction of tumor-hydrogel-endothelium interfaces in a spatiotemporal on-demand manner. Utilizing the chip where intravascularly injected cisplatin diffuse across the endothelium and transport into tumor samples, chemotherapeutic responses of cisplatin-resistant or -susceptible bladder tumor cells were evaluated, showing the preservation of cellular drug resistance even within the chip. The open-top structure also enabled the direct harvest of tumor samples and post analysis in terms of secretome and gene expressions. Comparing the cisplatin efficacy of the cisplatin-resistant tumor cells in the presence or absence of endothelium, we found that the proliferation rates of tumor cells were increased in the vasculature-incorporated chip. These have suggested that our vascularized tumor chip allows the establishment of vascular-gel-tumor interfaces in spatiotemporal manners and further enables investigations of chemotherapeutic screening.
15 MeV proton damage in NiO/β-Ga2O3vertical rectifiers
Authors: Li Jian-Sian , Chiang Chao-Ching , Xia Xinyi , Wan Hsiao-Hsuan , Kim Jihyun , Ren Fan , Pearton S J 
Published: August 2023

Abstract15 MeV proton irradiation of vertical geometry NiO/β-Ga2O3heterojunction rectifiers produced reductions in reverse breakdown voltage from 4.3 kV to 3.7 kV for a fluence of 1013ions·cm−2and 1.93 kV for 1014ions·cm−2. The forward current density was also decreased by 1–2 orders of magnitude under these conditions, with associated increase in on-state resistanceRON. These changes are due to a reduction in carrier density and mobility in the drift region. The reverse leakage current increased by a factor of ∼2 for the higher fluence. Subsequent annealing up to 400 °C further increased reverse leakage due to deterioration of the contacts, but the initial carrier density of 2.2 × 1016cm−3was almost fully restored by this annealing in the lower fluence samples and by more than 50% in the 1014cm−2irradiated devices. Carrier removal rates in the Ga2O3were in the range 190–1200 for the fluence range employed, similar to Schottky rectifiers without the NiO.
CMOS-compatible neuromorphic devices for neuromorphic perception and computing: a review
Authors: Zhu Yixin , Mao Huiwu , Zhu Ying , Wang Xiangjing , Fu Chuanyu , Ke Shuo , Wan Changjin , Wan Qing 
Published: August 2023

Abstract
Neuromorphic computing is a brain-inspired computing paradigm that aims to construct efficient, low-power, and adaptive computing systems by emulating the information processing mechanisms of biological neural systems. At the core of neuromorphic computing are neuromorphic devices that mimic the functions and dynamics of neurons and synapses, enabling the hardware implementation of artificial neural networks. Various types of neuromorphic devices have been proposed based on different physical mechanisms such as resistive switching devices and electric-double-layer transistors. These devices have demonstrated a range of neuromorphic functions such as multistate storage, spike-timing-dependent plasticity, dynamic filtering, etc. To achieve high performance neuromorphic computing systems, it is essential to fabricate neuromorphic devices compatible with the complementary metal oxide semiconductor (CMOS) manufacturing process. This improves the device’s reliability and stability and is favorable for achieving neuromorphic chips with higher integration density and low power consumption. This review summarizes CMOS-compatible neuromorphic devices and discusses their emulation of synaptic and neuronal functions as well as their applications in neuromorphic perception and computing. We highlight challenges and opportunities for further development of CMOS-compatible neuromorphic devices and systems.
Spherical acquisition trajectories for x-ray computed tomography with a robotic sample holder
Authors: Pekel Erdal , Dierolf Martin , Pfeiffer Franz , Lasser Tobias 
Published: August 2023

Abstract
This work presents methods for the seamless execution of arbitrary spherical trajectories with a seven-degree-of-freedom robotic arm as a sample holder. The sample holder is integrated into an existing x-ray computed tomography setup. We optimized the path planning and robot control algorithms for the seamless execution of spherical trajectories. A precision-manufactured sample holder part is attached to the robotic arm for the calibration procedure. Different designs of this part are tested and compared to each other for optimal coverage of trajectories and reconstruction image quality. We present experimental results with the robotic sample holder where a sample measurement on a spherical trajectory achieves improved reconstruction quality compared to a conventional circular trajectory. Our results demonstrate the superiority of the discussed system as it outperforms single-axis systems by reaching nearly 82% of all possible rotations. The proposed system is a step towards higher image reconstruction quality in flexible x-ray CT systems. It will enable reduced scan times and radiation dose exposure with task-specific trajectories in the future, as it can capture information from various sample angles.
Stochastic robust predictive fault-tolerant control for discrete systems with actuator faults
Authors: Shi Huiyuan , Zuo Lanshuang , Wang Shiqi , Su Chengli , Li Ping 
Published: August 2023

Abstract
A stochastic robust predictive fault-tolerant control approach is proposed for a class of industrial processes with uncertainties, external disturbances and the random failure of actuators. First, a process model of the above system is established in terms of state space. It is further converted into a new augmented form containing the state deviation and output tracking error. By means of the augmented model, the designed control law is given. Then the related theorem and corollary in the form of linear matrix inequality constraints are provided for solving the gain of the control law under different probabilities of failure. Under a certain probability, the occurrence of a failure is regarded as a switching condition. Conventional control is adopted when the failure does not occur, while fault-tolerant control is performed when the failure occurs. Finally, a pressure holding phase case is provided for verifying the feasibility of the given approach.
Exploring 3D community inconsistency in human chromosome contact networks
Authors: Bernenko Dolores , Lee Sang Hoon , Lizana Ludvig 
Published: August 2023

Abstract
Researchers have developed chromosome capture methods such as Hi-C to better understand DNA’s 3D folding in nuclei. The Hi-C method captures contact frequencies between DNA segment pairs across the genome. When analyzing Hi-C data sets, it is common to group these pairs using standard bioinformatics methods (e.g. PCA). Other approaches handle Hi-C data as weighted networks, where connected node pairs represent DNA segments in 3D proximity. In this representation, one can leverage community detection techniques developed in complex network theory to group nodes into mesoscale communities containing nodes with similar connection patterns. While there are several successful attempts to analyze Hi-C data in this way, it is common to report and study the most typical community structure. But in reality, there are often several valid candidates. Therefore, depending on algorithm design, different community detection methods focusing on slightly different connectivity features may have differing views on the ideal node groupings. In fact, even the same community detection method may yield different results if using a stochastic algorithm. This ambiguity is fundamental to community detection and shared by most complex networks whenever interactions span all scales in the network. This is known as community inconsistency. This paper explores this inconsistency of 3D communities in Hi-C data for all human chromosomes. We base our analysis on two inconsistency metrics, one local and one global, and quantify the network scales where the community separation is most variable. For example, we find that TADs are less reliable than A/B compartments and that nodes with highly variable node-community memberships are associated with open chromatin. Overall, our study provides a helpful framework for data-driven researchers and increases awareness of some inherent challenges when clustering Hi-C data into 3D communities.