bluuebunny/crossref_metadata_2025 huggingface dataset:
On the characteristics of DA shock waves in a polarized electron-depleted plasma with a mixed nonextensive high energy-tail ion distribution
Authors: Louamri Mohamed Messaoud , Merriche Abderrzak , Amour Rabia
Published: September 2023

A first theoretical attempt is made to understand the characteristics of dust acoustic shock waves (DASWs) in a polarized electron-depleted plasma with a mixed nonextensive high energy–tail ion distribution and to examine the impact of the generalized nonthermal polarization force on DASWs in an electron-depleted dusty plasma. First, a short numerical investigation illustrating the behavior of the mixed nonextensive high energy–tail (or Cairns–Tsallis) ion distribution and the domain of validity of its two parameters (q and [Formula: see text]) is carried out. Next, the generalized nonthermal polarization acting on dust grain in electron-depleted dusty plasma is determined within the context of Tsallis’ statistical mechanics. The behavior of this generalized polarization force is significantly affected by the nonextensive character of the nonthermal ions. Specifically, we have shown that, for both space and experimental dusty plasmas, the magnitude of the polarization force (in the case where [Formula: see text]) decreases as the nonextensivity of the nonthermal ions becomes significant. As an application, we have analyzed the changes caused by the nonthermal nonextensive polarization force on the main characteristics of DASW (viz. phase velocity, polarity, amplitude, width, etc.). Numerical results showed that our plasma model supports rarefactive and compressive DASWs that are significantly affected by the effects of nonthermal ion nonextensivity and polarization force. In particular, we have shown that for large values of the nonthermal parameter [Formula: see text], the increase in q allows the transition from rarefactive to compressive DASW structures. The present theoretical investigation is helpful to fully understand electrostatic disturbances in space and experimental dusty plasmas.
Kidney Stone Detection from CT Images Using ALEXNET and Hybrid ALEXNET-RF Models
Authors: Revathi M. , Raghuraman G.
Published: September 2023

Nowadays, kidney stone disease is one of the most common health issue which needs more attention for early diagnosis. Several imaging modalities are used for the detection of kidney stone. The gold standard CT scans are valuable for kidney stone detection. For kidney stone detection, machine and deep learning-based algorithms are widely used. In order to enhance the performance of earlier techniques, two techniques are developed. Initially, an AlexNet-based model is developed in this work. By using the enhanced recognition capability of Random Forest (RF), we developed a hybrid AlexNet-RF model. Both the models are tested against Kidney Stone Detection dataset. The performance of the proposed model proved that in terms of accuracy and loss the hybrid AlexNet-RF model secured reliable higher detection rate of approximately 97.1% to 97.5%. This showed that embedding RF in the Softmax layer of AlexNet significantly improves the prediction rate of kidney stone.
Formalizing the Semantics of a Classical-Quantum Imperative Language in Coq
Authors: Shi Wenjun , Cao Qinxiang , Deng Yuxin
Published: September 2023

In order to verify the functional correctness of quantum circuits or algorithms, a prominent approach is to specify them as quantum programs and semi-automatically deduce them in a theorem prover. It is indispensable to first formalize the semantics of the basic quantum language. We formalize in Coq an imperative language which allows for classical and quantum information interactions. We define small-step operational semantics and state-based denotational semantics. Then we prove a consistency theorem between these two semantics. A distribution-based denotational semantics is also defined and related to the state-based one. Finally, we describe a few typical quantum algorithms and utilize the distribution-based denotational semantics to verify their correctness.
Shape evolution of nuclei in the region of (A≈30) using covariant density functional theory
Authors: Bashir Hanaa , Abusara H. , Ahmad Shakeb
Published: September 2023

Shape evolution of even–even isotopes of Ne, Mg, Si, S, Ar and Ca in the vicinity of [Formula: see text] mass region of the nuclear chart is studied using covariant density functional theory. It will be studied based on finite range NN-interaction force represented by NL3∗ and DD-ME2 and zero finite range NN-interaction force represented by DD-PC1. Both [Formula: see text]Mg and [Formula: see text]Si exhibit shape coexistence and the ground state shape which is found to be both oblate and prolate. The spherical shape is obtained for the Ca isotopes, and for nuclei that have magic neutron numbers [Formula: see text] and 20. The rest of the isotopic chain has only one minimum and alternates between prolate and oblate shapes. Physical properties are calculated at the location of ground state deformation with neutron number ([Formula: see text]) and proton number ([Formula: see text]), such as the binding energy, two-neutron separation energies, proton, neutron and charge radii. In general, a smooth change in these properties is found, except near [Formula: see text] and 20 one can see a sharp change, which reflects the sudden change in the ground state deformation in the neighboring nuclei. A very good agreement is found with the available experimental data, HF and FRDM models
Vibration Characteristics of Metamaterial Periodic Multi-Span Beams with Elastic Supports
Authors: Wang Xuehang , Xu Andi , Li Fengming
Published: September 2023

A novel metamaterial periodic multi-span beam with elastic supports and local resonators is designed and studied. The vibration characteristics of the designed metamaterial multi-span beam structure are investigated by the spectral element method (SEM) combined with the transfer matrix method (TMM). The accuracy and feasibility of the theoretical methods are validated by the finite element method (FEM) and vibration experiment. It is demonstrated that the metamaterial periodic multi-span beam with elastic supports can produce local resonance bandgaps in the low-frequency regions and Bragg bandgaps in the middle- and high-frequency regions. For some support stiffnesses, the amplitudes and widths of the bandgaps for the proposed structure are larger than those of the metamaterial multi-span beam with simply supported boundaries. Thus, the positions and ranges of the Bragg bandgaps can be adjusted by changing the stiffness of the elastic supports so as to improve the vibration reduction performance of the structure.
Dynamics of Spinning Viscoelastic Tapered Shafts with Axial Motion
Authors: Bao Rui , Wang Guangding , Chen Liqing , Yuan Huiqun
Published: September 2023

In this paper, the vibration and stability of spinning viscoelastic tapered shafts with axial motion are investigated. The model of the shaft system is developed by incorporating the spinning motion, axial motion, axial load, viscoelasticity, and geometric properties. The coupled governing equations of motion of the spinning shaft system are obtained by applying Hamilton’s principle. By employing the Laplace transform and Galerkin discretization method, the natural frequency and modal damping are computed. Also, the critical divergence axial and spinning velocities, as well as the flutter axial velocity, are determined. As a result, the divergence and flutter instability conditions of the system are examined. The effects of the main parameters, such as taper ratio, axial load, and viscoelasticity of material, on the vibration behavior of the shaft system are evaluated. The results show that compared to the homogeneous spinning shaft system with uniform cross-section, the vibration and stability of the viscoelastic tapered shaft system undergo an essential evolution. It is further demonstrated that the axial load and viscoelasticity are also the key parameters governing the stability of the system.
Zeta functions for tensor codes
Authors: Cotardo Giuseppe
Published: September 2023

In this work, we introduce a new class of optimal tensor codes related to the Ravagnani-type anticodes defined in 2023. We show that it extends the family of [Formula: see text]-maximum rank distance codes and contains the [Formula: see text]-binomial moment determined codes (with respect to the Ravagnani-type anticodes) as a proper subclass. We define and study the zeta function for tensor codes. We establish connections between this object and the weight enumerator of a tensor code with respect to the Ravagnani-type anticodes. We introduce a new refinement of the invariants of tensor codes exploiting the structure of product lattices of some classes of anticodes classified in 2023 and we derive the corresponding MacWilliams identities. In this framework, we also define a multivariate version of the tensor weight enumerator and we establish relations with the corresponding zeta function. As an application, we derive connections on the tensor weights.
On a class of permutation quadrinomials
Authors: Ding Zhiguo , Zieve Michael E.
Published: September 2023

For each prime power [Formula: see text], we determine all [Formula: see text] for which [Formula: see text] permutes [Formula: see text].
Observational constraints on modified CPL models for dark energy
Authors: Sardar Gopal , Chakraborty Subenoy
Published: September 2023

In this paper, we consider two modified Chevallier–Polarski–Linder (CPL) models in the background of homogeneous and isotropic FLRW space-time model. From the observational dataset (Pantheon + BAO + HST) we find that the logarithmic form of the equation of state for the dark energy (model II) is more preferred with the use of AIC and BIC and tightly constrained than the other form of the equation of state parameter (model I). However, model I is more favored compared to the model II in the context of Bayesian evidence. Finally, for [Formula: see text] tension it is found that model I is more preferable than model II.
Cosmography for various parametrizations of dark energy equation of state
Authors: Sardar Alok , Roy Tanusree , Debnath Ujjal
Published: September 2023

The concept of dark energy (DE) emerged as a result of confirming the accelerated expansion of the universe. Since then, numerous models have been developed to explore the origin and nature of DE. In this study, we investigate several recent cosmological models (Models 1–9) based on the parametrization of the DE equation of state. Our analysis focuses on a homogeneous, isotropic flat universe comprising DE, dark matter (DM), and radiation. We assume the separate conservation of the dark components (DE and DM) and radiation. By employing various parametrizations of [Formula: see text], we derive the corresponding Hubble function [Formula: see text]. To understand the cosmic expansion history of the universe in a model-independent manner, we employ cosmography as an approach. We express important cosmographic parameters such as deceleration, jerk, snap, and lerk parameters in terms of the Hubble rate [Formula: see text] and its derivative up to the fourth order. Additionally, we examine the statefinder parameter and [Formula: see text] diagnostics to distinguish between different types of DE models. Finally, we compare the physical interpretations of these diagnostic parameters with the standard [Formula: see text]CDM model to assess the viability of each model.
Supersymmetric quantum potentials analogs of classical electrostatic fields
Authors: García-Muñoz Juan D. , Raya A.
Published: September 2023

A relation between classical electrostatic fields and Shrödinger-like Hamiltonians is evidenced. Hence, supersymmetric quantum potentials analogous to classical electrostatic fields can be constructed. Proposing an ansatz for the electrostatic potential as the natural logarithm of a nodeless function, it is demonstrated that the electrostatic fields fulfil the Bernoulli equation associated to a second-order confluent supersymmetric transformation. By using the so-called confluent algorithm, it is possible, given a charge density, to find the corresponding electrostatic field as well as the supersymmetric potentials. Furthermore, the associated charge density and the electrostatic field profile of Schrödinger-like solvable potentials can be determined.
Current Understanding and Prospects of Silver Nanoparticles-Based Biosensor
Authors: Sharma Rama
Published: September 2023

Due to their distinctive optical potential, controlled plasmonic features, control over size and shape, and ability to manipulate their localized surface plasmon resonance (LSPR) and their response to their surroundings, silver nanoparticle attracts special attention in the fields of the biosensor. Silver (Ag) is an appealing tool in many domains, including diagnosis, medicine delivery, environment, electronics, and as an antibacterial agent. Ag nanoparticle applications are ubiquitous today in the fields of biosensors. Numerous studies have demonstrated the effectiveness of using Ag nanoparticles to improve the specific detection of clinical indicators. The development of nanotechnology has greatly benefited the field of biosensors since nanomaterials have a high surface-to-volume ratio that enables them to operate with greater sensitivity and effectiveness. Utilizing interdisciplinary study in biology, chemistry, and material science, recent advancements in nanotechnology encouraged the manufacture of nanomaterials in a variety of shapes and sizes. In the context of disease diagnosis, this review highlighted the use of Ag nanoparticles in biosensors to detect small molecules to bigger entire cells. This paper also discusses how to make a glucose biosensor more sensitive. It describes how the detection performance of biomolecules including DNA, protein, tiny molecules, and complete cells can be improved. For future applications in the field of diagnosis, this review helps in developing an overall understanding of the clinical importance of Ag nanoparticles. These biosensors can be implemented in the field of diagnosis to speed up the response time.
Structural, Optical, Relaxor and Transport Properties of a Nanocrystalline Double Perovskite: Ba2(FeMo)O6
Authors: Mishra S. , Choudhary R. N. P. , Parida S. K.
Published: September 2023

The paper presents a synthesis (solid-state. reaction) and characterization of a lead-free double perovskite oxide Ba2(FeMo)O6 ceramic. The initial analysis using X-ray diffraction revealed that the material has a cubic crystal symmetry with a micro-lattice strain of 0.000824 and an average crystallite size of 62[Formula: see text]nm. The microstructural features and elemental composition of the prepared polycrystalline sample were examined using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). The SEM micrograph, EDX spectrum and elemental mapping show distinctly grown grains with well-defined grain boundaries, purity and distribution pattern of the grains, respectively. Raman scattering spectroscopy is a valuable tool for studying the vibrational modes to get information about structural and chemical properties of materials. The optical properties of the material were investigated using UV–Vis spectroscopy, which provides various parameters including energy bandgap for different technological applications. The electrical behavior of the synthesized double perovskite was examined through frequency- and temperature-dependent dielectric measurements as well as impedance spectroscopy. The electrical conduction in the material followed Jonscher’s power law and is supported by a thermally activated conduction mechanism. The analysis of electrical resistance versus temperature confirms negative temperature coefficient of resistance nature and can be used as NTC thermistors. The study of polarization-electric field loop opens up the possibility of the ferroelectric nature of the studied sample and also measures energy storage density, energy loss density and efficiency for searching different potential applications related to sensors. Overall, the results suggest its potential for various technological applications, such as in sensors and devices requiring specific electrical behavior or ferroelectric properties.
Computational Design, Combinatorial Screening and Experimental Analysis of Lung Cancer EGFRVIII-Binding Peptides
Authors: Gao Dongyun , Yao Jun , Zhou Xuefeng , Zhang Xia , Zhou Linlin , Wang Qiangrong , Li Shan , Ding Xi
Published: September 2023

Human epidermal growth factor receptor mutation variant III ([Formula: see text] is a cancer-specific cell surface oncogenic marker and has been observed to be widely involved in the formation, progression and metastasis of lung cancer and some other tumors. Previously, a massive quantity of [Formula: see text]-binding peptides were enriched via random phage display (RPD) targeted against the protein. In this study, we reported rational discovery of 12-mer peptides with high affinity to [Formula: see text] and strong selectivity for [Formula: see text] over wild-type EGFR ([Formula: see text]. A combinatorial peptide library was designed to target [Formula: see text] based on over ten thousands of known [Formula: see text] binders enriched from RPD analysis, and a virtual high-throughput screening protocol was then systematically performed against the library to derive those potential candidates, which were further examined rigorously at structural and energetic levels to identify few promising hits. Anisotropy binding assays were carried out to substantiate the computational findings. Consequently, eight 12-mer peptides were designed as effective binders that can target the [Formula: see text] extracellular subdomain 3 (SD3). In particular, two potent peptides (T1: FLHRYEIVTSYF and T3: FLQKYEWNTSYW) were found to have a high affinity to [Formula: see text] and a good selectivity for [Formula: see text] over [Formula: see text]. Structural analysis revealed that the peptide-binding site can be divided into hydrophobic, polar and mixed regions, which correspond to the nonpolar [Formula: see text]-terminal section, polar/charged middle section and hybrid C-terminal section of the peptide. The peptide selectivity originated from the middle section, which can form a different hydrogen bond network between the two proteins upon the mutating perturbation, whereas the N- and C-terminal sections are primarily responsible for the peptide stability but not specificity.
Wind and Actuator Fault Estimation for a Quadrotor UAV Based on Two-Stage Particle Filter
Authors: Xing Zhewen , Zhang Youmin , Su Chun-Yi
Published: September 2023

This paper investigates the problems of wind and actuator fault estimation for a quadrotor unmanned aerial vehicle (UAV). To effectively assess the safety and reliability of a quadrotor UAV in the presence of unknown wind disturbances, a two-stage particle filter (TSPF) scheme is proposed to obtain the simultaneous estimation of winds and actuator faults that may degrade the performance of the vehicle. In this scheme, the first-stage particle filter is used to estimate the states of the quadrotor UAV, and the second-stage particle filter is designed to produce estimates of unknown parameters, including the wind disturbances and actuator faults. To mitigate the degeneracy and impoverishment issues, the second-stage particle filter admits a parallel implementation of increased particle samplings for the wind and actuator fault estimation. Finally, simulation results are presented to demonstrate the effectiveness of the proposed scheme.
Exploring Digital Means to Engage Visitors with Roman Culture: Virtual Reality vs. Tangible Interaction
Authors: Petrelli Daniela , Roberts Andrew J.
Published: September 2023

To effectively communicate the archaeological remains of the distant past is a challenge: Little may be left to see, and the culture may be very different to comprehend. This article compares two technological approaches to communicating Roman archaeology in museums: virtual reality and tangible interaction. Although very different in rationale, design, and implementation, the two explorative studies have the same aim of engaging visitors with important exhibits. The challenge is to effectively communicate the exhibit's original and cultural context. In “Views of the Past,” virtual reality was used to support an environmental narrative experience where fragments of history are found scattered in the 3D reconstructed forum of Augustus in Rome. In “My Roman Pantheon,” a tangible interactive installation, visitors act as Romans living along Hadrian's Wall making offerings to the deities of the Roman pantheon to secure their protection. In both explorative studies the combination of the features (virtual reality + narratives, tangible + acting) make visitors feel “cultural presence,” where the perception of a place is combined with the awareness of the culture and an understanding of the past. Although they work on very different sensorial reaction (sight for virtual reality, touch for tangible interaction), both are promising mechanisms to design effective visitors’ experiences for challenging cultural heritage settings.
Computation of Turing Bifurcation Normal Form for
n
-Component Reaction-Diffusion Systems
Authors: Villar-Sepúlveda Edgardo , Champneys Alan
Published: September 2023

General expressions are derived for the amplitude equation valid at a Turing bifurcation of a system of reaction-diffusion equations in one spatial dimension, with an arbitrary number of components. The normal form is computed up to fifth order, which enables the detection and analysis of codimension-two points where the criticality of the bifurcation changes. The expressions are implemented within a Python package, in which the user needs to specify only expressions for the reaction kinetics and the values of diffusion constants. The code is augmented with a Mathematica routine to compute curves of Turing bifurcations in a parameter plane and automatically detect codimension-two points. The software is illustrated with examples that show the versatility of the method including a case with cross-diffusion, a higher-order scalar equation and a four-component system.
Maximizing the Diversity of Exposure in Online Social Networks by Identifying Users with Increased Susceptibility to Persuasion
Authors: Zareie Ahmad , Sakellariou Rizos
Published: September 2023

Individuals may have a range of opinions on controversial topics. However, the ease of making friendships in online social networks tends to create groups of like-minded individuals, who propagate messages that reinforce existing opinions and ignore messages expressing opposite opinions. This creates a situation where there is a decrease in the diversity of messages to which users are exposed (
diversity of exposure
). This means that users do not easily get the chance to be exposed to messages containing alternative viewpoints; it is even more unlikely that they forward such messages to their friends. Increasing the chance that such messages are propagated implies that an individuals’
susceptibility to persuasion
is increased, something that may ultimately increase the diversity of messages to which users are exposed. This article formulates a novel problem which aims to identify a small set of users for whom increasing susceptibility to persuasion maximizes the diversity of exposure of all users in the network. We study the properties of this problem and develop a method to find a solution with an approximation guarantee. For this, we first prove that the problem is neither submodular nor supermodular and then we develop submodular bounds for it. These bounds are used in the Sandwich framework to propose a method which approximates the solution using reverse sampling. The proposed method is validated using four real-world datasets. The obtained results demonstrate the superiority of the proposed method compared to baseline approaches.
An Intent Taxonomy of Legal Case Retrieval
Authors: Shao Yunqiu , Li Haitao , Wu Yueyue , Liu Yiqun , Ai Qingyao , Mao Jiaxin , Ma Yixiao , Ma Shaoping
Published: September 2023

Legal case retrieval is a special Information Retrieval (IR) task focusing on legal case documents. Depending on the downstream tasks of the retrieved case documents, users’ information needs in legal case retrieval could be significantly different from those in Web search and traditional ad hoc retrieval tasks. While there are several studies that retrieve legal cases based on text similarity, the underlying search intents of legal retrieval users, as shown in this article, are more complicated than that yet mostly unexplored. To this end, we present a novel hierarchical intent taxonomy of legal case retrieval. It consists of five intent types categorized by three criteria, i.e., search for
Particular Case(s)
,
Characterization
,
Penalty
,
Procedure
, and
Interest
. The taxonomy was constructed transparently and evaluated extensively through interviews, editorial user studies, and query log analysis. Through a laboratory user study, we reveal significant differences in user behavior and satisfaction under different search intents in legal case retrieval. Furthermore, we apply the proposed taxonomy to various downstream legal retrieval tasks, e.g., result ranking and satisfaction prediction, and demonstrate its effectiveness. Our work provides important insights into the understanding of user intents in legal case retrieval and potentially leads to better retrieval techniques in the legal domain, such as intent-aware ranking strategies and evaluation methodologies.
Automated Buffer Sizing of Dataflow Applications in a High-level Synthesis Workflow
Authors: Honorat Alexandre , Dardaillon Mickaël , Miomandre Hugo , Nezan Jean-François
Published: September 2023

High-Level Synthesis (HLS) tools are mature enough to provide efficient code generation for computation kernels on FPGA hardware. For more complex applications, multiple kernels may be connected by a dataflow graph. Although some tools, such as Xilinx Vitis HLS, support dataflow directives, they lack efficient analysis methods to compute the buffer sizes between kernels in a dataflow graph. This article proposes an original method to safely approximate such buffer sizes. The first contribution computes an initial overestimation of buffer sizes without knowing the memory access patterns of kernels. The second contribution iteratively refines those buffer sizes, thanks to cosimulation. Moreover, the article introduces an open source framework using these methods to facilitate dataflow programming on FPGA using HLS. The proposed methods and framework have been tested on seven dataflow applications and outperform Vitis HLS cosimulation in five benchmarks, either in terms of BRAM and LUT usage, or in terms of exploration time. In the two other benchmarks, our best method gets results similar to Vitis HLS. Last but not least, our method admits directed cycles in the application graphs.
Task-based Meta Focal Loss for Multilingual Low-resource Speech Recognition
Authors: Chen Yaqi , Zhang Wenlin , Zhang Hao , Qu Dan , Yang Xu-Kui
Published: September 2023

Low-resource automatic speech recognition is a challenging task due to a lack of labeled training data. To resolve this issue, multilingual meta-learning learns a better model initialization from many source language tasks for fast adaptation to unseen target languages. However, for diverse source languages, the quantity and difficulty vary greatly because of their different data scales and phonological systems. These differences lead to task-quantity and task-difficulty imbalance issues and thus a failure of multilingual meta-learning ASR. In this work, we propose a task-based meta focal loss (TMFL) approach to address this tough challenge. Specifically, we introduce a hard-task moderator and update the meta-parameters using gradients from both the support set and query set. Our proposed approach focuses more on hard tasks and makes full use of the data from hard tasks. Moreover, we analyze the significance of the hard task moderator and interpret its significance at the sample level. Experiment results show that the proposed method, TMFL, significantly outperforms the state-of-the-art multilingual meta-learning on all target languages for the IARPA BABEL and OpenSLR datasets, especially under very-low-resource conditions. In particular, it can reduce character error rate from 72% to 60% by fine-tuning the pre-trained model with about 22 hours of Vietnamese data.
A Classical Architecture for Digital Quantum Computers
Authors: Zhang Fang , Zhu Xing , Chao Rui , Huang Cupjin , Kong Linghang , Chen Guoyang , Ding Dawei , Feng Haishan , Gao Yihuai , Ni Xiaotong , Qiu Liwei , Wei Zhe , Yang Yueming , Zhao Yang , Shi Yaoyun , Zhang Weifeng , Zhou Peng , Chen Jianxin
Published: September 2023

Scaling bottlenecks the making of digital quantum computers, posing challenges from both the quantum and the classical components. We present a classical architecture to cope with a comprehensive list of the latter challenges
all at once
, and implement it fully in an end-to-end system by integrating a multi-core RISC-V CPU with our in-house control electronics.

Our architecture enables scalable, high-precision control of large quantum processors and accommodates evolving requirements of quantum hardware. A central feature is a microarchitecture executing quantum operations in parallel on arbitrary predefined qubit groups. Another key feature is a reconfigurable quantum instruction set that supports easy qubit re-grouping and instructions extensions.

As a demonstration, we implement the widely-studied surface code quantum computing workflow, which is instructive for being demanding on both the controllers and the integrated classical computation. Our design, for the first time, reduces instruction issuing and transmission costs to constants, which do not scale with the number of qubits, without adding any overheads in decoding or dispatching.

Our system uses a dedicated general-purpose CPU for both qubit control and classical computation, including syndrome decoding. Implementing recent theoretical proposals as decoding firmware that parallelizes general inner decoders, we can achieve unprecedented decoding capabilities of up to distances 47 and 67 with the currently available systems-on-chips for physical error rate
p
= 0.001 and
p
= 0.0001, respectively, all in just 1 μs.
DIWS-LCR-Rot-hop++: A Domain-Independent Word Selector for Cross-Domain Aspect-Based Sentiment Classification
Authors: Lee Junhee , Frasincar Flavius , Truşcă Maria Mihaela
Published: September 2023

The Aspect-Based Sentiment Classification (ABSC) models often suffer from a lack of training data in some domains. To exploit the abundant data from another domain, this work extends the original state-of-the-art LCR-Rot-hop++ model that uses a neural network with a rotatory attention mechanism for a cross-domain setting. More specifically, we propose a Domain-Independent Word Selector (DIWS) model that is used in combination with the LCR-Rot-hop++ model (DIWS-LCR-Rot-hop++). DIWS-LCR-Rot-hop++ uses attention weights from the domain classification task to determine whether a word is domain-specific or domain-independent, and discards domain-specific words when training and testing the LCR-Rot-hop++ model for cross-domain ABSC. Overall, our results confirm that DIWS-LCR-Rot-hop++ outperforms the original LCR-Rot-hop++ model under a cross-domain setting in case we impose an optimal domain-dependent attention threshold value for deciding whether a word is domain-specific or domain-independent. For a target domain that is highly similar to the source domain, we find that imposing moderate restrictions on classifying domain-independent words yields the best performance. Differently, a dissimilar target domain requires a strict restriction that classifies a small proportion of words as domain-independent. Also, we observe information loss which deteriorates the performance of DIWS-LCR-Rot-hop++ when we categorize an excessive amount of words as domain-specific and discard them.
Block-RACS: Towards Reputation-Aware Client Selection and Monetization Mechanism for Federated Learning
Authors: Batool Zahra , Zhang Kaiwen , Toews Matthew
Published: September 2023

Federated Learning (FL) is a promising solution for training using data collected from heterogeneous sources (e.g., mobile devices) while avoiding the transmission of large amounts of raw data and preserving privacy. Current FL approaches operate in an iterative manner by selecting a subset of participants each round, asking them to training using their latest local data over the most recent version of the global model, before collecting these local model updates and aggregating them to form the next iteration of the global model, and so forth until convergence is reached. Unfortunately, existing FL approaches typically select randomly the set of clients to use each round, which can negatively impact the quality of the model trained, as well the training round time due to the straggler problem. Moreover, clients, especially mobile devices with limited resources, should be incentivized to participate as federated learning is essentially a form of crowdsourcing for AI which requires monetization. We argue that integrating blockchain and smart contract technologies into FL can solve the two aforementioned issues. In this paper, we present Block-RACS (Blockchain-based Reputation Aware Client Selection), a mechanism for FL operating in a smart contract which rewards clients for their participation using cryptocurrencies. Block-RACS employs a multidimensional auction mechanism for selecting users based on the compute and network resources offered by each client, as well as the quality of their local data. This auction is realized in a reliable and auditable manner through a smart contract. This allows Block-RACS to measure the relative contribution of each client by calculating a Shapley value and allocating rewards accordingly. Moreover, a blockchain-based reputation mechanism enables audibility and non-repudiation. The security analysis of the system is also presented to check the security vulnerabilities. We have implemented Block-RACS using Solidity and tested on the Ethereum blockchain with various popular datasets. Our results show that Block-RACS outperforms existing baseline schemes by improving accuracy and reducing the number of FL rounds.
(Invited, Digital Presentation) Langmuir-Type Formulation for Atomic-Order Surface Reactions of Reactant Gases on Si (100) and Ge (100) Surfaces
Authors: Murota Junichi
Published: September 2023

Atomic-order surface reaction processes of reactant gases on the Si (100) and Ge (100) surfaces are reviewed. The site density on the (100) surface where the reactant molecules are adsorbed and react is estimated from the maximum self-limited adsorption/reaction amount of reactant gas on the (100) surface. The atomic-order amounts of reactant gases under self-limiting adsorption/reaction conditions are described using a modified Langmuir-type mechanism as a function of reactant gas partial pressure and exposure time at a specified temperature. For the hydrogen-terminated surface, it is proposed that the reactant molecules are physically adsorbed on the hydrogen-terminated sites and react with the hydrogen terminated on the surface. Fairly good agreement is obtained between all experimental data and the modified Langmuir-type mechanism for the self-limited adsorption/ reaction.
(Invited) Characteristics of GaN/High-k Capacitors Under Positive Bias Stress
Authors: Nabatame Toshihide , Sawada Tomomi , Irokawa Yoshihiro , Koide Yasuo , Tsukagoshi Kazuhito
Published: September 2023

We investigated characteristics of the Hf0.55Al0.45Ox MOS capacitor (HfAlO) under a high sweep voltage and positive bias stress (PBS). The role of a 0.5nm-thick HfO2 (HfO/HfAlO) or a 0.5nm-thick Al2O3 (AlO/HfAlO) interfacial layer (IL) between n-GaN and Hf0.55Al0.45Ox film on electrical properties was also discussed. The HfAlO, HfO/HfAlO and AlO/HfAlO capacitors showed a similar leakage current property. Each flatband voltage (Vfb) exhibited the same value against electric field (E) from Vfb. No Vfb hysteresis of all capacitors was observed at high Es from Vfb up to 3.5MVcm-1. Under PBS, the positive Vfb shift appeared in all capacitors and increased with increasing the E from Vfb. Note that the positive Vfb shift suppressed 0.3V regardless of IL even in high effective electric field from Vfb regions of 10~15MVcm-1 while the positive Vfb shift of the Al2O3 capacitor significantly increased above 0.5V at a low 6.5MVcm-1.
Degradation and Failure Mechanism of p-GaN Gate E-Mode GaN HEMTs
Authors: Mehta Abhas , Shichijo Hisashi , Joh Jungwoo , Suh Chang , Kim Moon
Published: September 2023

This work describes the cause-effect-based degradation process of the p-GaN gate in Enhancement-mode (E-mode) GaN High Electron Mobility Transistors (HEMTs) using gate stressing and failure analysis (FA). We found no correlation between time-to-fail and initial gate current (IG0). Instead, a higher impact of temperature was found on the gate current of the device (IG) and time-to-fail at 100 °C. Gate failure at constant voltage stress was a single-stage failure. Under constant current stress, the gate shows a multi-stage failure. The breakdown starts with increased gate current leading to Schottky barrier leakage and finally to catastrophic contact failure. The metal/p-GaN interface at the gate finger becomes the weakest part of the gate stack. Metal/p-GaN interface and surface defects develop as percolation paths acting as leakage sources, and nano-cracks have been observed in the gate cap. FA also shows physical degradation at the metal/p-GaN cap due to electrical stress.
(Invited) Switching Characteristics of GaN Power Transistors
Authors: Shur Michael , Liu Xueqing , Ytterdal Trond
Published: September 2023

A shorter switching time and smaller conduction and switching losses are the key advantages of GaN power devices over Si technology. Further improvements of GaN HEMT technology will require new design approaches including SiC and even, possibly, diamond substrates, gate and drain edge engineering (beyond just using field plates) for optimizing the voltage distribution in the drain-to-gate spacing to using perforated channel design and a low conducting passivation for smoothing or even eliminating the sharp maximum of the electric field in the vicinity of the gate and field plate edges on switching time.
(Invited) Selective Area Growth, Etching, and Doping of GaN By MOCVD for Power Electronics
Authors: Li Bingjun , Han Jung
Published: September 2023

The lack of selective-area doping technique in GaN greatly hinders the demonstration of sophisticated device structures for high power application. We explored the possibility of using selective-area etching followed by selective area growth to achieve SAD. For the etching step, we explored the in-situ TBCl etching, where we achieved controlled etch rate and smooth trenches. The TBCl etching was proven to be a low-damage etching process compared to the conventional dry etching. Moreover, selective area growth of p-GaN in a patterned trench was analyzed by atom probe tomography (APT). We found Mg atoms cannot diffuse on the GaN surface, which led to an observed inverse proportionality between Mg concentration and local growth rate. However, it was discovered that Mg precursors, like Ga, exhibit inter-trench diffusion through the gas phase.
Numerical Reconstruction of Proton Exchange Membrane Fuel Cell Gas Diffusion Layers
Authors: Yang Danan , Garg Himani , Beale Steven B. , Andersson Martin
Published: September 2023

Stochastic reconstruction is widely employed for effective and flexible imitation of Gas Diffusion Layers (GDLs), e.g., to facilitate the study of their properties. However, the reconstruction often overlooks crucial factors such as fiber curvature, fiber stack arrangement, and fiber anisotropy. Consequently, the impact of these structural characteristics remains poorly understood. In this study, an in-house reconstruction procedure is developed based on the periodic surface model. This procedure enables the generation of GDLs with either straight or curved fibers, layer-by-layer or random arrangement, and different probabilities of through-plane fiber orientation angles. The porosity, domain size, and fiber diameter are extracted from an experimental image-based GDL and utilized as input data for the reconstruction. Furthermore, the different GDLs are compared in terms of pore size distribution and through-plane porosity distribution. It is concluded that introducing proper selections of these fiber features gives the reconstruction more realistic properties.
Probing the Catalyst-Ionomer Interface in Catalyst Layers with Sulfo-Phenylated Polyphenylene Ionomers Using CO-Displacement and Stripping Techniques
Authors: Anton Robert James , Sun Shikai , Swider-Lyons Karen , Mittelsteadt Cortney , Adamski Michael , Britton Benjamin , Morimoto Yu , Zenyuk Iryna
Published: September 2023

An investigation of ionomer-catalyst interfaces for electrodes containing sulfo-phenylated polyphenylene (sPPP) ionomers is conducted with CO displacement and stripping experiments. We find that at fully humidified conditions, catalyst layers containing sPPP ionomers show a CO displacement peak that is almost entirely suppressed. This suppression corresponds to adsorption of sulfonic acid group adsorption on only 2% of the available Pt surface. We also observe that at 100% RH, the double-layer capacitance of the catalyst layer is higher when poisoned by CO. This is inverse of the behavior observed with PFSA electrodes, indicating that there might be different ionomer-catalyst interactions present with an sPPP ionomer. We hypothesize that differences between sPPP and perfluorinated sulfonic acid (PFSA) ionomer backbones may account for this difference due to the presence of phenyl rings, which could adsorb to Pt surfaces preferentially at high humidification.
Self-Supporting Microporous Layer for Polymer Electrolyte Fuel Cells
Authors: Yoshikawa Makoto , Yamamoto Kotaro , Noda Zhiyun , Yasutake Masahiro , Kitahara Tatsumi , Tachikawa Yuya , Lyth Stephen Matthew , Hayashi Akari , Matsuda Junko , Sasaki Kazunari
Published: September 2023

The gas diffusion layer (GDL) used in a PEFC is thicker than the electrode catalyst layer and electrolyte membrane. Thinning down the GDL can reduce gas diffusion resistance and volumetric power density of PEFC stacks. In this study, MPL/GDL is prepared by printing microporous layers (MPLs) on carbon meshes of several tens of micrometers thick as substrates for thin-layer GDLs. Through various current-voltage and overvoltage measurements and microstructural analysis of the cells using these thin-layer MPL/GDLs, cell performance has been improved, equivalent to that of the state of the MPL/GDL.
Mass Transport Impedance in a PEMFC with Superhydrophobic Catalyst Layers
Authors: Duque Luis , Molinero Antonio , Oller Juan Carlos , Barcala José Miguel , Díaz-Álvarez Ester , Folgado M. Antonia , Chaparro Antonio M
Published: September 2023

Hydrogen transport in the anode of a proton-exchange membrane fuel cell (PEMFC) with superhydrophobic catalyst layer has been studied with Current-modulated Hydrogen-flowrate Spectroscopy (CH2S). The catalyst layers of Pt/C catalyst and ionomer (Nafion) are prepared by the electrospray deposition technique, with macroporous morphology and superhydrophobic pores walls. Transport properties are studied under different operating conditions in a PEMFC, including humidification, temperature, and cell current. Features of the CH2S spectra are compared for electrosprayed and commercial –hydrophilic- catalyst layers, reflecting different transport properties. The electrosprayed layers show enhanced hydrogen transport properties.
Two-Phase Flow Through the PTL of PEM Water Electrolyzer: MRI Experiments and Numerical Modeling Using Phase-Field Theory
Authors: Amoury Bilal , Le Tien Dung , Dillet Jérôme , Leclerc Sébastien , Maranzana Gael , Didierjean Sophie
Published: September 2023

Proton Exchange Membrane (PEM) electrolysis is a promising technology for large industrial-scale hydrogen production, but it faces limitations due to mass transport and electrical transfer issues in the anode Porous Transport Layer (PTL). The optimal porosity and pore size of the PTL contributes to efficient water, gas, and electron transport. In this work, the water/gas counter-current flow through the PTL was studied by both experiment and modeling. Magnetic Resonance Imaging (MRI) is utilized to quantify water content within the porous layer during the two-phase flow for different gas and water inlet flow rates. The dependence of the saturation profile and bubble formation on the gas/water flow rates, water channel's orientation, flow direction is studied. To better understand the two-phase flow characteristics in the PTL, the phase-field model based on the Cahn-Hilliard theory for describing a diffuse interface is used to model the water and gas transport over 2D porous layer.
Investigation of Ageing Methods on Gas Diffusion Layers for HT-PEMFC Application
Authors: Pilinski Nadine , Uhlig Lisa Maria , Schmies Henrike , Schweiss Ruediger , Wagner Peter
Published: September 2023

Gas diffusion layers (GDLs) are commonly used materials for polymer electrolyte membrane fuel cell (PEMFC) applications. Key role of the GDL is the distribution of reaction gases evenly from the bipolar plate to the catalyst layer and enabling the removal of product water. Especially challenging are elevated temperatures and acidic conditions for materials applied in high temperature (HT) PEMFCs. In this work, ex-situ ageing tests on GDLs were performed. First, the GDLs were aged in an electrochemical set-up in concentrated phosphoric acid (PA) at temperatures up to 160 °C. After ageing, the GDLs were analysed regarding their morphology and changes in elemental composition. The results show lower impact after ageing at constant potentials of 0.1 V, 0.8 V and OCV but a significant effect of increasing temperature and higher potential of 1.2 V as well as potential cycling. This is confirmed by morphological analysis.
Water Transport Modeling in a Microporous Layer for a Polymer Electrolyte Membrane Water Electrolyzer Having a Gas-Liquid Separating Interdigitated Flow Field
Authors: Nakajima Hironori , Ekström Henrik , Shima Asuka , Sone Yoshitsugu , Lindbergh Göran
Published: September 2023

A new interdigitated flow field design for polymer electrolyte membrane electrolyzers has been developed for ground and space applications. It internally separates oxygen and liquid water, eliminating the water circulators to remove the bubbles and external gas-liquid separators with buoyancy. The capillary pressure in the hydrophobic microporous layer(MPL) of the anode porous transport layer enables the internal separation of oxygen gas and pressurized liquid water. A finite element model (COM-SOL Multiphysics) simulates water transport in the MPL. Electrochemical impedance spectra determine the electrochemical kinetic parameters for the model. The model accounts for the oxygen bubble coverage of the CL, liquid water saturation in the MPL, and the current ratio between liquid water and water vapor at the MPL-CL interface. The vapor from liquid water in the MPL mixes with oxygen for diffusion. The water evaporation rate based on liquid water saturation in the MPL is introduced.