bluuebunny/crossref_metadata_2025 huggingface dataset:
Longitudinal beam dynamics and collective effects at the STCF collider rings
Authors: Zhang Linhao , Liu Tao , Li Sangya , Zou Ye , Luo Qing , Tang Jingyu
Published: November 2024

The Super Tau-Charm Facility (STCF) proposed in China is a new-generation high-luminosity [Formula: see text] collider in the low-energy region, with the beam energy of 1–3.5[Formula: see text]GeV and a target luminosity of larger than [Formula: see text] at the optimized beam energy of 2[Formula: see text]GeV. Due to the limitations posed by the coherent X-Z instability and significant beam collective effects, the longitudinal beam dynamics are crucial for the STCF. This paper aims to introduce an iterative optimization model for the design of longitudinal beam dynamics in STCF. The model takes into account factors such as lattice design, coherent X-Z instability, and single-bunch collective effects. The analysis includes an estimation of the main collective instabilities and proposes corresponding mitigation strategies. This study will contribute to the further design optimization of the STCF collider rings.
Reflecting attack and improvement of a semi-quantum private comparison protocol with three-particle GHZ-like states
Authors: Yang Chun-Wei , Huang Yu-Yun , Tsai Chia-Wei , Lin Jason
Published: November 2024

This study focuses on semi-quantum private comparison (SQPC) protocols, where participants with limited quantum capabilities compare private information with the help of a quantum third party (TP). Yan et al. introduced an SQPC protocol in 2021, but Li et al. later found it vulnerable to double controlled NOT (CNOT) operation attacks and proposed improvements. However, this study identifies a different vulnerability in Yan et al.’s protocol — a reflecting attack that allows information leakage. Bob can intercept and reflect quantum states, avoiding detection and then use Alice’s measurement outcomes and pre-shared key to access her confidential information. The study also proposes an enhanced method to secure the protocol.
Ramond superstring in static gauge
Authors: Goumidi A. , Belaloui N.
Published: November 2024

A Ramond open superstring quantization is studied in a flat D-dimensional Minkowski spacetime in a static gauge. This gauge degenerates the boost generators. A deformation in the structure of the boosts is proposed at the classical level with some energy-dependent coefficients. We quantize the theory and propose the quantum version of the deformation of the boost operators. The energy-dependent coefficients are determined in the first and second excited levels in order to keep the physical Hilbert space Lorentz invariant. The critical space–time dimension [Formula: see text] and ordering ambiguity constant [Formula: see text] are recovered. We give the connection between the covariant and static gauge quantizations.
The physical meaning of Sharma–Mittal entropy and its relevance to Giddings’ hypothesis on black hole evaporation
Authors: Dashtianeh Hasan , Sadeghi Jafar
Published: November 2024

Recent research has shown that generalized entropies are suitable for describing the thermodynamic properties of gravitational systems. In 2016, Giddings proposed that the spectrum of Hawking radiation, which characterizes evaporating semiclassical black holes, originates from a quantum “atmosphere” that lies beyond a black hole’s horizon. Subsequent studies confirmed that this proposal is possible if the Bekenstein–Hawking entropy of the Schwarzschild black hole is taken to be the Tsallis entropy, and that this result is also compatible with the generalization of the Tsallis entropy to the Rényi entropy. In our paper, we show that the Sharma–Mittal entropy, which is another generalization of the Tsallis entropy, rejects the possibility of Hawking’s proposal but can be compatible with Giddings’ suggestion. So, in this paper, we consider the Sharma–Mittal entropy and study its behavior related to Giddings’ suggestion. So we specify a range for the upper limit of the [Formula: see text] parameter, which enables Giddings’ suggestion in the presence of the Sharma–Mittal entropy. We also understood that the Sharma–Mittal entropy, similar to the Tsallis and Rényi entropies, exhibits the same behavior under some approximation of its parameters, in accordance with Giddings’ suggestion.
Hierarchical Feature Fusion for Cross-Modality Person Re-identification
Authors: Fu Wen , Lim Monghao
Published: November 2024

To address the limitations of visible light cameras that cannot function effectively at night, infrared cameras have become the optimal supplement. However, current methods for visible–infrared cross-modality person re-identification focus solely on feature combination and fusion, neglecting the importance of feature alignment. To address this issue, we introduce a novel Hierarchical Feature Fusion (HFF) network, which comprehensively integrates features across various levels through sequential feature extraction. Specifically, we design a pixel-level contrastive loss function that makes pixels in the same region of cross-modality images more similar and distinguishes pixel features at different locations, thereby extracting similar low-frequency information in the shallow network. Furthermore, in the deep network, we extract high-frequency information of different modalities through the Bi-Transformer Layer and propose Node-level Coupling Attention and Modality-level Decoupling Attention. Coupling attention is used for high-frequency information coupling within the same modality while decoupling attention is used for high-frequency information decoupling between different modalities to obtain more texture and detail information. Through a series of experimental results, we validate the superiority of the proposed HFF network in cross-modality person re-identification. Our proposed method achieved 87.16% and 95.23% Rank-1 on the SYSU-MM01 and RegDB datasets, respectively, and extensive experiments have validated its effectiveness in feature alignment.
Bayesian Point Estimation of Linear/Circular Consecutive k-out-of-n : F System Reliability Under Vague Environment
Authors: Madhumitha J. , Vijayalakshmi G.
Published: November 2024

The paper proposes a Bayesian approach to estimate the reliability and mean time to failure (MTTF) of linear and circular consecutive [Formula: see text]-out-of-[Formula: see text]:[Formula: see text] systems under vague environments, where uncertainties are represented using vague sets. By assuming model parameters as vague random variables with vague prior distributions, the study employs the Resolution Identity theorem for vague sets to resolve and structure this vagueness within the Bayesian framework. The proposed method uses the squared error loss function to derive vague Bayesian estimates, providing a more realistic and comprehensive analysis of system reliability in the presence of uncertainty. Numerical illustrations are included to demonstrate the applicability and effectiveness of the approach, highlighting its potential for handling vague information in complex system reliability analysis.
Early Phase Software Dependability Analysis: A Neutrosophic Inference System-Based Approach
Authors: Chatterjee Subhashis , Saha Deepjyoti , Sharma Akhilesh , Verma Yogesh
Published: November 2024

Due to the presence of reliability, security, or performance-related issues, software systems will become nondependable during the early development phase. Currently, there is a lack of research addressing these dependability issues in software quality analysis. To bridge this gap, this study proposes a neutrosophic inference system (NIS)-based model to predict reliability, security and performance attributes during the early phase. The NIS model accommodates uncertainties, imprecisions, indeterminacies and incompleteness of metric values utilizing its truth, indeterminate and false components. To enhance the prediction accuracy of the NIS model, a rule-base formation algorithm is proposed for NIS considering domain expert knowledge. Finally, an artificial neural network (ANN) model is designed based on estimated values of reliability, security and performance attributes to predict the total number of faults in software projects. Comparative analysis demonstrates that the proposed model outperforms other existing models. This proposed methodology helps software developers in assessing software dependability from the beginning stage of software development.
Reliability Inference for Power Rayleigh Distribution Under Block Progressive Censoring: A Pivotal Quantity-Based Approach
Authors: Mondal Rajendranath , Gangopadhyay Aditi Kar , Maiti Kousik , Lodhi Chandrakant
Published: November 2024

In this paper, we study the statistical inference of the unknown parameters and the reliability characteristics (RCs) such as reliability function, hazard function, median time to failure (MdTF) and differences in different test facilities (DDTF) of the power Rayleigh distribution under a block progressive censored scheme. The maximum likelihood and the pivotal inference methods are implemented to estimate the unknown parameters and the RCs of the power Rayleigh distribution. Asymptotic confidence intervals of the unknown parameters and the RCs are derived by applying the asymptotic normality property of maximum likelihood estimator (MLE) and the delta method. In the pivotal inference, generalized confidence intervals are obtained. The performances of these estimation methods are tested and compared with each other with the help of a simulation study. Finally, two real data sets are taken to illustrate the proposed methods.
Lq estimates for nonlocal p-Laplacian-type equations with BMO kernel coefficients in divergence form
Authors: Byun Sun-Sig , Kim Kyeongbae
Published: November 2024

We study [Formula: see text]-fractional [Formula: see text]-Laplacian-type equations with discontinuous kernel coefficients in divergence form to establish [Formula: see text] estimates for any choice of pairs [Formula: see text] with [Formula: see text] and [Formula: see text] under the assumption that the associated kernel coefficients have small BMO seminorms near the diagonal. As a consequence, we find in the literature an optimal fractional Sobolev regularity of such a nonhomogeneous nonlocal equation when the right-hand side is presented by a suitable fractional operator. Our results are new even in the linear case.
The invariants of the Weil representation of SL2(ℤ)
Authors: Müller Manuel K.-H. , Scheithauer Nils R.
Published: November 2024

The transformation behavior of the vector-valued theta function of a positive-definite even lattice under the metaplectic group [Formula: see text] is described by the Weil representation. We show that the invariants of this representation are induced from five fundamental invariants. As an application we give simple generating sets for Jacobi forms of singular weight.
Vibration Control of Wind Turbine Towers with Inerter-Based Outrigger-Cable-Lever-Damping (IOCLD) Systems
Authors: Su Ning , Bian Jing , Chen Zhaoqing , Zeng Cong , Xia Yi
Published: November 2024

Wind Turbine Towers (WTTs) are slender infrastructures for renewable energies, which are subjected to significant vibrations induced by wind and seismic hazards during their lifetime. In order to suppress these harmful vibrations, an Inerter-based Outrigger-Cable-Lever-Damping (IOCLD) system is proposed. It is composed of an outrigger, a lever, and a pair of cables and inerter-dashpot dampers. The outrigger is to convert bending rotation into vertical vibrations, which is transferred to the lever by the cables. The lever amplifies the inertial-damping force provided by the dampers. The inerter is beneficial to enhance energy dissipation. With these mechanisms, the vibration of WTTs can be effectively suppressed. In order to achieve optimal control performances, the tuning parameters of the IOCLD are analytically derived. Additionally, an equivalent inertance ratio is proposed to obtain the optimal parameters and evaluate the control performance. Finally, through practical numerical cases for wind- and seismic-induced vibration control, the effectiveness of the IOCLD is proved. Compared with existed Amplifying Damping Transfer System (ADTS) without inerters, IOCLD exhibits an excellent energy dissipation rate, which exceeds twice of ADTS for the investigated cases. Compared with conventional Tuned Mass Damper (TMD), IOCLD shows its advantages for lightweight, stability and in-situ adjustable feasibility.
Experimental and Finite Element Analysis on an Elastic–Plastic Hemispherical Asperity Contact Against a Rigid Flat in Plane Strain with Bilinear Hardening
Authors: Huang Jiaxin , Sun Yining , Sun Chen , Chen Jubing
Published: November 2024

Real surface contact occurs primarily at the asperities, whose morphologies vary based on different processing methods. To simplify this complexity, asperities are often idealized as regular geometric shapes such as spheres or hemispheres. This paper introduces a spherical asperity model under plane strain conditions, derived from finite element analysis. The model establishes relationships between interference and contact area, as well as interference and average contact pressure, which are dependent on the material properties of the asperities. Unlike many previous models that segmented asperity deformation into different stages based on the deformation state of the contact area, this model presents a unified expression that encompasses the elastic, elastic–plastic, and plastic deformation of spherical asperities. This unified approach eliminates potential discontinuities at critical points inherent in piecewise models. Additionally, due to the small contact area of asperities, accurately measuring the contact area during the deformation of a single asperity presents significant challenges. This study employs the digital image correlation (DIC) method to measure the contact area between the spherical asperity and the indenter, with model results validated against experimental data.
Acoustic Waves in Axial Crystals and Quasicrystals with Preliminary Finite Strains
Authors: Sokolova Marina , Khristich Dmitrii
Published: November 2024

The dynamic problem of acoustic wave propagation in elastic bodies with preliminary finite deformations is formulated. Several types of anisotropic elastic materials are considered: hexagonal crystals of class [Formula: see text], transversally isotropic materials and axial quasicrystals with an arbitrary order of the rotary axis. A variant of nonlinear hypoelasticity relations is constructed for these materials. In the constitutive relations, the tensor connecting the rate of change of the stress tensor and the strain rate tensor is a function of deformations. The propagation of acoustic waves in a hypoelastic material with preliminary finite deformations and stresses is described as a process of weak perturbations superimposed on finite strains.

The characteristic features of elastic wave propagation in hexagonal crystals and axial quasicrystals are revealed. Within the framework of the constructed models, the most significant differences are found in the phase velocities of a transverse wave with a polarization vector located in the crystallographic plane (110). Unlike hexagonal crystals, in axial quasicrystals, there are such directions of acoustic wave propagation for which the phase velocities of transverse waves are insensitive to the degree of preliminary deformations. Based on the solution of the problem of elastic wave propagation, a program of dynamic experiments with macrosamples, which allows to distinguish axial quasicrystals from hexagonal crystals by the peculiarities of acoustic wave propagation, is proposed.
Existence of renormalized solutions to the parabolic nitial-boundary value problems involving variable exponents and measure data
Authors: Yaremenko Mykola Ivanovich
Published: November 2024

In this paper, we establish the existence of a renormalized solution to the initial-boundary problem to the parabolic differential problem involving variable exponent under the Leray–Lions type of conditions. We show the independence of the definition of the renormalized solution of the decomposition of the given measure, and applying the approximation approach we establish the existence of a renormalized solution to the parabolic problem with measure data, which does not charge the sets of zero capacity.
A gram-scalable and air-stable 2,2-diphenyl-1,3-dithiolane-bridged bis-1, 8-naphthalimide fluorescent probe for efficient Hg2+ detection
Authors: Cao Wenyu , Wang Weifang , Deng Ping , Yu Yan
Published: November 2024

A simple, novel, and gram-scalable fluorescent probe material (NIT) containing a 2,2-diphenyl-1,3-dithiolane-bridged bis-1,8-naphthalimide unit with excellent air environment stability has been reported. NIT can effectively detect Hg[Formula: see text] according to the variation in the fluorescence characteristics of NIT with and without Hg[Formula: see text]. The selectivity, concentration titration, pH applicable range, and detection limit of NIT in 2-methyl tetrahydrofuran/water have been investigated. The results show NIT possesses high selectivity, a wide pH applicable range of 3-13, and sensitivity to detect Hg[Formula: see text]. NIT also indicates the potential application in real environmental water samples for detecting Hg[Formula: see text].
Design and structural features of magnetic cobalt ferrite nanoparticles in a biopolymer matrix
Authors: Aleksandrova Galina , Tikhonov Nikolay , Sapozhnikov Anatoly
Published: November 2024

Nanostructured cobalt ferrites were obtained by chemical condensation in a one-pot synthesis under environmentally acceptable conditions. Narrowly dispersed cobalt ferrite nanoparticles were formed in the presence of a dielectric matrix of the natural polysaccharide arabinogalactan. It is shown that the size-controlled stabilization and guided self-organization of nanocomposites is due to the unique nature of the chosen polymer matrix. Modification of the nanoparticles surface with a hydrophilic polysaccharide promotes a uniform spatial distribution of nanoparticles in the bulk of the nanocomposite. The structural characteristics of NCs were studied using XRDMA, IR spectroscopy, TEM and X-ray diffractometer. The inorganic phase of the obtained samples with varying cobalt content has a cubic spinel structure with an average crystallite size of 6.5–12.5 nm. The electron paramagnetic resonance method was used to study the magnetic properties of nanocomposites and their changes with increasing temperature in the range of 25–125[Formula: see text]C. It was shown for the first time that heating the nanocomposites directly in the spectrometer resonator significantly enhances the integral intensity of the EPR spectrum signal with a significant variation in the line width and [Formula: see text]-factor. It was established that the degree of substitution of iron by cobalt in obtained nanocomposites played a key role in changing the interaction of samples with a magnetic field. Presumably, the shape of the spectrum changes when the temperature rises to 125[Formula: see text]C due to the transformation of multi-domain particles into single-domain particles due to the displacement of domain boundaries. The resulting water-soluble nanocomposites, combined with a biocompatible polymer matrix, have a unique set of properties and, as a result, are potentially interesting for classical and new applications in technological fields, from electronics to biomedicine.
Thermal and electrical characteristics of praseodymium-based perovskites as a function of iron and cobalt substitution
Authors: Srinivas Reddy Padigela , Sripada Suresh , Rajesh S. , Vaidya Prashanth Kumar , Mallikarjun A. , Ravindar Reddy M. , Mettu Maheshwar Reddy , Mahendrakar Sangeetha
Published: November 2024

Praseodymium-based perovskite samples (PSFCO) were made using the sol–gel process, consisting of Pr[Formula: see text]Sr[Formula: see text]Fe[Formula: see text]Co[Formula: see text][Formula: see text]O3 (where [Formula: see text] = 0.2, 0.4, 0.6, and 0.8). Images obtained through TEM confirmed the magnitude and clustering of particles according to their shape. In order to build solid-oxide fuel cells, it is essential to assess electrical characteristics and thermal behavior of produced samples using a dilatometer and an LCR impedance meter. Researchers looked examined how each sample’s dielectric constant and dielectric loss changed with respect to frequency, temperature, and thermal expansion. A significant change in the dielectric performance and also thermal expansion coefficient is observed when iron and cobalt contents are substituted. This change explains the compound compatibility of the cathode materials when used with electrolytes which leads to greater ionic conductivity and less thermal expansion values, together of which are important in SOFC applications.
Structural Insights and Drug Repurposing of FDA-Approved Molecules against Human Agmatinase in Cancer Therapy
Authors: Khan Zeeshan , Ikram Saima , Ahmad Jamshaid , Rehman Irshad Ur , Ahsan Hina , Ullah Amin , Alshaya Dalal Sulaiman , Fayad Eman , Hassan Hesham M. , Eldeen Muhammad Alaa
Published: November 2024

Background: Cancer remains a significant global health challenge, with ongoing research focused on identifying effective therapeutic targets. Human agmatinase (AGMAT), a binuclear manganese enzyme, has been associated with cancer progression through its role in polyamine production and its involvement in the NO/MAPK/PI3K signaling pathway in lung tissue. Objective: This study aimed to identify potential inhibitors of AGMAT from a library of FDA-approved drugs using computational methods, intending to find novel therapeutic agents for cancer treatment. Methods: The three-dimensional structure of AGMAT was determined using homology modeling, with Pseudomonas guanidinobutyrase (GbuA) serving as the template due to its 74% sequence similarity to AGMAT. The model was validated using PROCHECK, Verify3D, ProSA and ERRAT software. High-throughput virtual screening was conducted on a chemical library of approximately 7922 FDA-approved drugs to identify potential AGMAT inhibitors. Molecular docking simulations assessed the binding affinities of these drugs. Results: The virtual screening identified ten lead FDA-approved molecules: Nemifitidum, Examorelin, Pralmorelin hydrochloride, Nonathymulin, Ebiratide, Lypressin, Histrelin, Agripressin, Cetrorelix and Ornipressin that exhibited significant binding affinities to AGMAT. Conclusion: The identified lead compounds represent promising candidates for further investigation as potential cancer therapeutics targeting AGMAT. These findings provide a basis for future experimental validation and the development of new drugs toward cancer treatments.
Coumarin Prevents the Oligomerization and Aggregation of Amylid β: Deciphering the Mode of Action using Molecular Simulations
Authors: Furkan Mohammad , Qais Faizan Abul , Khan Mohd Shahnawaz , Khan Mohammad Rashid , Ahmad Iqbal , Khan Rizwan Hasan
Published: November 2024

Neurological disorders (NDs) affect 15% of the human population globally, causing cognitive and physical disabilities. There is an increase in cases of NDs with the aging populations that challenges accessible healthcare. NDs, like Parkinson’s, and Alzheimer’s, cause neuronal loss and impairments. Misfolded protein accumulation characterizes disorders like Alzheimer’s and Parkinson’s. Amyloid beta (A[Formula: see text]) has two main variants, A[Formula: see text][Formula: see text] and A[Formula: see text][Formula: see text]. A[Formula: see text] accumulation triggers microglia activation, and synaptic loss in Alzheimer’s disease (AD). A[Formula: see text] induces neuronal dam-age, forming amyloid plaques. Soluble A[Formula: see text] oligomers are neurotoxic, disrupting neuronal func-tions. Therefore, A[Formula: see text] aggregation inhibition is a potential therapeutic strategy for AD. Molecu-lar dynamics (MD) simulations offer unique insights, especially for investigating structural changes in peptides like A[Formula: see text] interacting with inhibitors. Computational methods provide in-sights into the driving forces behind the aggregation of monomeric proteins at early stages. Using computational methods, this study explores how coumarin inhibits A[Formula: see text] oligomerization and aggregation, revealing reduced [Formula: see text]-sheet formation and potential drug development in-sights. Coumarin interacted at the high aggregation propensity and hydrophobic region of A[Formula: see text] and stabilized it. When 10 molecules A[Formula: see text][Formula: see text] were simulated, [Formula: see text]-sheet content stood at 2.27% within the initial 5 ns, progressively reaching 11.35% until 50 ns. This upward trend continued, reaching an average [Formula: see text]-sheet content as 22.83% for entire simulation. However, the introduc-tion of 250 mM coumarin during the simulation diminished the formation of [Formula: see text]-sheets to 10.59%. Overall, our studies suggest that coumarin could serve as a potential preventive and therapeutic agent for inhibiting A[Formula: see text] oligomerization and aggregation.
New Approach of Hybrid Momentum Exchange Devices for Spacecraft Attitude Control System
Authors: Gamal Haytham M. , Desouky Mohammed A. A. , Ashry Mahmoud , Hussien Ahmed Esmat
Published: November 2024

Control moment gyroscopes (CMGs) are a favorable choice for spacecraft attitude control systems thanks to their torque amplification capability. However, their performance is hindered by geometric singularities, which can severely limit control capabilities during attitude maneuvers. This paper proposes a hybrid attitude control system incorporating a single reaction wheel into the standard minimum redundant four-CMG pyramid configuration, providing an additional degree-of-freedom to avoid and escape singularities effectively. A comprehensive mathematical analysis of the system’s Jacobian matrix, using row echelon form, is performed alongside a geometrical analysis of the hybrid configuration’s momentum envelope. These analyses demonstrate the reflection of a reaction wheel inclusion into the system of four CMGs in the improvement of the system’s capacity to avoid/escape singularity. Additionally, an asymptotic control law and an adapted steering law are developed to optimize control performance. The effectiveness of the proposed hybrid system is validated through simulation, which includes a comparative analysis with traditional CMG-only system. The results highlight the superiority of the hybrid system in handling singularities.
Multi-Targets Visiting Orbit Design Based on Numerical Method
Authors: Zhong Zenan , Sun Zhengxiang , Wang Songyan , Chao Tao , Yang Ming
Published: November 2024

In this paper, for the two/three targets in the circle orbit with the same altitude, a numerical method is presented to design an orbit for a spacecraft to visit multiple targets without maneuvering. First, for the two targets’ case, an equation is established by the relationship of the two angles that both are the function of the time, one of the angles is the angle between two targets’ geocentric position vectors at two times, and another one is the spacecraft flight angle during the two times. The visit time can be solved by the assumption that one of the visit times is known in the equation, and the orbit element can be transferred from the position and velocity vector determined by the solved visit time. Then, for the three targets’ case, the problem is decoupled into two cases of two targets, and there is a public target in each case. Based on the method for two targets, two different orbits can be obtained by determining the visit time of the public target. The difference between two orbits can be expressed by the difference in velocity vectors of the public target at different times. A sampling method is utilized to select two velocity vectors with relatively small differences as initial values, the Newton iteration method is used to obtain visit times with higher accuracy. Simulation results illustrate the effectiveness of the orbit design methods.
The State of Digital Accessibility
Authors: Branham Stacy M. , Wahid Shahtab , Byrne-Haber Sheri , Mazrui Jamal , Muncharaz Carlos , Myhill Carl
Published: November 2024

If you are new to digital accessibility, and even if you are not, it can be difficult to stay abreast of the big picture, and the tech industry moves fast. So, we asked a team of experts to bring us up to speed. Not only do they have day jobs that involve digital accessibility, but they also have lived experience of disability. We posed the following questions to them: What's the state of accessibility? Key challenges? Why do we need accessible software? How can we make the case for accessibility? Who's leading the way? Where do we go from here?
Subword Dictionary Learning and Segmentation for Expanding the Vocabulary of Automatic Speech Recognition in Tamil and Kannada
Authors: A Madhavaraj , Pilar Bharathi , Angarai Ganesan Ramakrishnan
Published: November 2024

We present automatic speech recognition (ASR) systems for Tamil and Kannada based on subword modeling to effectively handle unlimited vocabulary arising due to the highly agglutinative nature of the languages. We propose a variant of the byte pair encoding (BPE) algorithm named extended-BPE, and
Morfessor
tool to segment each word into its subwords. We have effectively incorporated maximum likelihood and Viterbi estimation techniques with weighted finite state transducers framework in these algorithms to learn the subword dictionary from a large text corpus. Using the learned subword dictionary, the words in the transcriptions of the training data are segmented into subwords. We train deep neural network ASR systems that recognize the subword sequence for any given test speech utterance. The output subword sequence is then post-processed using deterministic rules to get the final word sequence. Because of this subword design, the number of words that can be recognized is much larger than the number of words in the training corpus. For Tamil ASR, we use 152 hours of data for training and 65 hours for testing, whereas for Kannada ASR, we use 275 hours for training and 72 hours for testing. Upon experimenting with different combinations of segmentation and estimation techniques, we find that the word error rate (WER) reduces drastically when compared to the baseline word-level ASR, achieving a maximum absolute WER reduction of 6.24% and 6.63% for Tamil and Kannada, respectively. Further, comparing our results with that of an end-to-end ASR model available on GitHub, we have seen that our subword language models can perform comparable to or exceed that of recent end-to-end ASR models for Kannada and Tamil languages.
GCNTrain+: A Versatile and Efficient Accelerator for Graph Convolutional Neural Network Training
Authors: Song Zhuoran , Long Jiabei , Jiang Li , Jing Naifeng , Liang Xiaoyao
Published: November 2024

Recently, graph convolutional networks (GCNs) have gained wide attention due to their ability to capture node relationships in graphs. One problem appears when full-batch GCN is trained on large graph datasets, where the computational and memory requirements are unacceptable. To address this issue, mini-batch GCN training is introduced to improve the scalability of GCN training for large datasets by sampling and training only a subset of the graph in each batch. Although several acceleration techniques have been designed for boosting the efficiency of full-batch GCN, they lack attention to mini-batch GCN, which differs from full-batch GCN in terms of the sampled dynamic graph structures. Based on our previous work GCNTrain [28], which was originally excogitated for accelerating full-batch GCN training, we devise GCNTrain+—a universal accelerator to tackle the performance bottlenecks associated with both full-batch and mini-batch GCN training.

GCNTrain+ is equipped with two engines to optimize computation and memory access in GCN training, respectively. To reduce the computation overhead, we propose to dynamically reconfigure the computation order based on the varying data dimensions involved in each training batch. Moreover, we build a unified computation engine to perform the sparse-dense matrix multiplications (SpDM) and sparse-sparse matrix multiplications (SpSpM) discovered in GCN training uniformly. To alleviate the memory burden, we devise a two-phased dynamic clustering mechanism to capture data locality as well as customized hardware to reduce the clustering overhead. We evaluate GCNTrain+ on seven datasets, and the result shows that GCNTrain+ achieves 136.0 ×, 52.6 ×, 2.2 ×, and 1.5 × speedup over CPU, GPU, GCNAX, and GCNTrain in full-batch GCN training. Additionally, GCNTrain+ outperforms them with speedups of 131.6 ×, 67.1 ×, 4.4 ×, and 1.5 × in mini-batch GCN training.
Optimal Intervention Strategies on TB Epidemiology in a Prison Population
Authors: Maku Vyambwera Sibaliwe , Witbooi Peter
Published: November 2024

This paper presents a compartmental model in ordinary differential equations of tuberculosis (TB) disease dynamics in a prison population, which is calibrated to reflect the unique conditions of the Democratic Republic of Congo. Data are sourced from various sources of statistics that are publicly available and also from other modeling publications. The model is utilized to determine the optimal roll‐out strategy for a combination of intervention strategies in TB control in a prison population. The two control functions both address treatment but are linked to different infection classes, making them distinct functions of time. Numerical simulations reveal that without well‐planned control measures, TB remains endemic. However, optimal control strategies can potentially eliminate the disease, provided the influx of TB‐infected prisoners is controlled. Implementing these strategies can significantly reduce the number of infectious TB cases while minimizing treatment costs.

MSC2020 Classification: 92D30, 34K20
A Comparative Analysis of Hydroxyurea Treatment on Coagulation Profile Among Sickle Cell Anaemia Children in Lagos, Nigeria
Authors: Kene-Udemezue Blessing E. , Salako Abideen O. , Akinsete Adeseye M. , Odubela Oluwatosin O. , Adeyemo Titilope A.
Published: November 2024

Background: Hydroxyurea (HU) is a disease‐modifying therapy with significant clinical and laboratory efficacy among individuals living with sickle cell anaemia (SCA). This is evident through increased fetal haemoglobin, higher packed cell volume, improved red cell hydration, reduced leukocytes, and platelet function. The effect on the coagulation pathway and pathophysiologic mechanism remains unclear, especially in children living with SCA. This study evaluated the coagulation profile using D‐dimer and thrombin antithrombin complex (TAT) in children with SCA.

Methods: The cross‐sectional study was conducted over three months at LUTH among 80 children living with SCA in steady state aged 2–18 years (40 HU exposed and 40 HU naïve, respectively). Blood samples were assayed for D‐dimer, TAT, and complete blood count. Descriptive analysis such as mean and standard deviation for normally distributed variables or median and interquartile range for skewed data were used to summarize continuous variables, while proportion or percentages for categorical variables. Univariate analysis and bivariate analysis were done and statistical significance was set at p < 0.05.

Results: The mean age (±SD) of study participants in both groups was 11.35 (±4.6 years). D‐dimer levels (23.27 ng/mL) and TAT (29.79 pg/mL) were significantly lower among HU exposed compared to HU naïve children (62.73 ng/mL and 109.34 pg/mL, respectively) p < 0.001. There was a negative correlation between D‐dimer and TAT with the duration of HU use (r = −0.499, p = 0.001, and r = −0.401, p = 0.010), respectively. There was a positive correlation between D‐dimer and TAT with total WBC (r = 0.368, p = 0.019, and r = 0.385, p = 0.014, respectively) among the HU naïve participants and a negative correlation between D‐dimer and TAT with haemoglobin level (r = −0.303, p = 0.047, and r = −0.311, p = 0.041, respectively) among HU exposed children.

Conclusion: HU modulates the D‐dimer and TAT levels of children living with SCA toward the normal reference range, thus reducing the risk of hypercoagulability and associated sequelae. Therefore, continuous advocacy for HU use should entail close monitoring of adverse effects.
Optimization Design of W‐Beam‐Modified Guardrail Structure Based on the RBF Model and Anticrossing Consideration
Authors: Liu Tangzhi , Zuo Linming , Wu Pan , Tian Yingyuan , Ge Yu , Zhang Lu , Chen Xiang
Published: November 2024

The frequent occurrence of secondary traffic accidents, characterized by vehicles losing control and straying into opposing lanes on highways, has emerged as a pressing concern. To address this issue, attention has been focused on the pivotal role of median guardrails as safety barriers. While conventional guardrails have effectively hindered vehicles from veering off course, mitigating accident severity, they are now inadequate in meeting the heightened protective standards necessitated by the surge in truck traffic and advancements in vehicle capabilities. To evaluate and enhance the protective capabilities of guardrails, this research employs a vehicle finite element (FE) model in conjunction with a W‐beam guardrail system. Collision trajectories, acceleration, and displacement metrics were analyzed to compare the effectiveness of three improved guardrail designs in preventing crossing in the event of a runaway truck. Furthermore, based on the design of the retrofitted guardrail, the optimization of the structural parameters was carried out by a multiobjective optimization method using radial basis function (RBF) and NSGA‐II algorithms with the size of the guardrail as the design variable. The collision simulation comparisons reveal that the double W‐beam arch‐reinforced guardrail surpasses both the double W‐beam and the arch‐reinforced guardrail regarding protective performance. Notably, the double W‐beam design offers a viable option for disposing of obsolete guardrails postdemolition. The optimized design underscores that optimal structural protection is achieved when meticulously adjusting the thickness of the upper girder plate and the arch to precise dimensions. This refined guardrail system enhances safety and achieves material efficiency, utilizing less steel in its construction. By elucidating effective design modifications and the determination of optimal structural dimensions, this study provides its ideas for safer roads and more efficient infrastructure development.
Anti‐Inflammatory and Bacteriostatic Effects of Hydrogen‐Rich Water on Rats With Periodontitis
Authors: Bai Yang , Zhao Lisheng , Wang Lin , Shan Yanbo , Zhang Wei , Wen Ning
Published: November 2024

Objective: To investigate the anti‐inflammatory and bacteriostatic effects of hydrogen‐rich water (HRW) intake on Wistar rats with periodontitis.

Methods: The periodontitis model of rats was established by silk ligature and Porphyromonas gingivalis (Pg) solution smearing. The rats were divided into normal control group, model group, and HRW group. The rats in normal control group were given normal feeding without any intervention, while periodontitis was induced in the rats of model group and HRW group, and the rats were given HRW intake and normal saline, respectively, during the whole procedure of the experiments. The antibacterial effect and clinical symptoms (plaque index and gingival sulcus bleeding index (SBI)) were then observed, and peripheral blood (PB), gingival sulcus fluid, and jaw samples were collected to evaluate the changes of inflammatory factors and the curative effect.

Results: In the rats of model group, alveolar bone resorption was obvious, which indicated that the rats with periodontitis were successfully constructed, and HRW intake mitigated it. Pg colony number of the rats fed with HRW was significantly lower than that of the model rats. The contents of proinflammatory factors tumor necrosis factor alpha (TNF‐α), interleukin‐1 beta (IL‐1β), and interleukin‐6 (IL‐6) in PB serum and gingival crevicular fluid (GCF) of rats in model group were significantly increased, and HRW intake reversed these and promoted the level of anti‐inflammatory factor interleukin‐10 (IL‐10).

Conclusion: HRW can effectively inhibit the growth of periodontal pathogens and reduce inflammation and may be used to prevent or ameliorate periodontitis.
Predictive Value of IL‐6 and Lymphocyte Subsets for Death in Children With Influenza‐Associated Encephalopathy A Retrospective Study
Authors: Sun Ruiyang , Zhang Xue , Hou Jiapu , Jia Wanyu , Li Peng , Wang Daobin , Fu Shuqin , Song Chunlan
Published: November 2024

Objective: This study aims to investigate the predictive value of interleukin‐6 (IL‐6) and lymphocyte subsets for death in children with influenza‐associated encephalopathy (IAE).

Patients: This study included 76 children with IAE who were divided into a death group and a survival group. The differences in the levels of IL‐6 and lymphocyte subsets between the two groups were analyzed, and the predictive value of these two parameters was compared by receiver operating characteristic (ROC) curve analysis.

Results: The level of IL‐6 and the percentage of natural killer (NK) cells in the death group were higher than those in the survival group (p  < 0.05). The percentage of CD4+ T cells and CD4+/CD8+ levels in the death group were lower than those in the survival group. ROC curves were used for analysis, and the area under the curves (AUCs) of IL‐6, the percentage of CD4+ T cells, the percentage of CD4+/CD8+, and the percentage of NK cells were 0.812, 0.810, 0.740, and 0.706, respectively. The AUC of the combination of these four metrics was 0.870. There was a little difference in the efficacy of the four clinical indicators, and the predictive efficacy of the combined test was higher than that of the single test.

Conclusion: The IL‐6 concentration, percentage of CD4+ T cells, percentage of NK cells, and CD4+/CD8+ have predictive value for death in children with IAE, and the combination of these four metrics has improved the predictive value.
Predictors of Jordanian Registered Nurses’ Clinical Decision‐Making: The Role of Self‐Directed Learning and Personal Characteristics
Authors: Rababah Jehad A. , Al-Hammouri Mohammed Munther
Published: November 2024

Background: Making clinical decisions is a complex process that encompasses assessing patient needs, identifying potential health problems, and developing and implementing appropriate interventions. The predictors of clinical decision‐making among registered nurses are not thoroughly understood.

Aim: To investigate the potential predictors of clinical decision‐making in Jordanian registered nurses. Those predictors included age, gender, percent grade, experience, work hours per week, self‐initiated reading hours per week, and the four dimensions of self‐directed learning: learning motivation, planning and execution, self‐monitoring, and interpersonal relationships.

Methods: The authors employed a cross‐sectional design. Registered nurses (N = 139) were recruited from a referral hospital in Jordan. A demographics questionnaire was used in this study. In addition, the nurse decision‐making instrument‐revised and the self‐directed learning instrument were used. Data were collected in August and September 2022. Data analysis was performed using Pearson’s r and multiple linear regression.

Results: The results showed that registered nurses’ scores on nurse decision‐making instrument‐revised had positive correlations with age, experience, and self‐directed learning instrument scores. Multiple linear regression results revealed that the model was significant, and the explained variance of registered nurses’ clinical decision‐making was 53%. The following predictors significantly contributed to the regression model: registered nurses’ age, gender, percent grade, experience, and the four domains of self‐directed learning.

Conclusion: There is a positive, moderate correlation between registered nurses’ self‐directed learning and clinical decision‐making. This study also showed that registered nurses’ clinical decision‐making is predicted by self‐directed learning and other factors including age, experience, and percent grades.
Identification and Genetic Analysis of Species D Rotaviruses in Pangolin Samples
Authors: Wang Kai , Liu Shasha , Liang Xiaotong , Hu Wanke , Wen Zhenyu , Wang Jiayi , Wang Xianghe , An Fuyu , Chen Ziqiao , Yan Haikuo , Yan Hongmei , Wang Lei , Zhang Xiaoai , Yu Jieshi , Wei Wen-Kang , Hua Yan
Published: November 2024

Pangolins have been found to carry severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2)‐related coronaviruses. In light of this discovery, interest has been piqued in viromes of these heavily trafficked wild animals. In this study, we performed viral metagenomic sequencing to explore viromes of both confiscated dead pangolins and captive healthy pangolins. Sequence reads of vertebrate‐associated viruses in Herpesviridae, Retroviridae, Iridoviridae, Reoviridae, Arenaviridae, and Flaviviridae were detected in confiscated dead pangolins. A novel rotavirus (RV) (Reoviridae), showing a high degree of genetic similarity to the RV species D (RVD) that was previously unreported in mammals, was further confirmed by using reverse transcription‐polymerase chain reaction (RT‐PCR) and Sanger sequencing. Three out of 18 samples from the confiscated dead pangolins were positive for genomic sequences of the novel RV. Importantly, sequence alignments and phylogenetic analyses demonstrated that these RV strains genetically belonged to the RVD. Nevertheless, these novel RVD strains were divergent from known RVD strains that have been found only in Avian. They formed a separate genetic cluster. Five serial passages were attempted to isolate the RV, but no live virus was obtained. In addition, fecal samples were collected from healthy pangolins (n = 41) in our institution and screened for RVs by viral metagenomic sequencing and RT‐PCR. In these fecal samples, neither species D nor previously identified species A RVs were detected. This study reported RVDs in pangolin samples for the first time to our knowledge. Identifiability disagreements between wild and captive pangolins highlight the need for further exploration into pangolin viruses to better understand their emergence and transmission potential.