bluuebunny/crossref_metadata_2025 huggingface dataset:
Ensuring a sustained workforce to combat antibiotic resistance in the 21st century: the critical need for training the next-gen of scientists at the pre-doctoral level
Authors: Shafer William M. , Conn Graeme L.
Published: April 2024

Antibiotics revolutionized the treatment of bacterial infection and enhanced modern healthcare. While the current global antibiotic resistance crisis is widely acknowledged, the need for a highly trained cohort of scientists to continue and expand efforts to combat this threat has received less attention. We posit that training of pre-doctoral students in the antibiotic resistance field is critical for future efforts in combating this crisis and urge development of training programs that focus on this need.
Expanding the adenovirus toolbox: reporter viruses for studying the dynamics of human adenovirus replication
Authors: King Cason R. , Dodge Mackenzie J. , MacNeil Katelyn M. , Tessier Tanner M. , Mymryk Joe S. , Mehle Andrew
Published: April 2024

To streamline standard virological assays, we developed a suite of nine fluorescent or bioluminescent replication competent human species C5 adenovirus reporter viruses that mimic their parental wild-type counterpart. These reporter viruses provide a rapid and quantitative readout of various aspects of viral infection and replication based on EGFP, mCherry, or NanoLuc measurement. Moreover, they permit real-time non-invasive measures of viral load, replication dynamics, and infection kinetics over the entire course of infection, allowing measurements that were not previously possible. This suite of replication competent reporter viruses increases the ease, speed, and adaptability of standard assays and has the potential to accelerate multiple areas of human adenovirus research.

IMPORTANCE

In this work, we developed a versatile toolbox of nine HAdV-C5 reporter viruses and validated their functions in cell culture. These reporter viruses provide a rapid and quantitative readout of various aspects of viral infection and replication based on EGFP, mCherry, or NanoLuc measurement. The utility of these reporter viruses could also be extended for use in 3D cell culture, organoids, live cell imaging, or animal models, and provides a conceptual framework for the development of new reporter viruses representing other clinically relevant HAdV species.
Multisite prospective study of perioperative pain management practices for anterior cruciate ligament reconstruction in adolescents: Society for Pediatric Anesthesia Improvement Network (SPAIN) Project Report
Authors: Sadacharam Kesavan , Furstein James S , Staffa Steven J , Li Galaxy , Karroum Rami , Booth Jocelyn M , Kim Eugene , McCahan Suzanne M , Muhly Wallis T , Chidambaran Vidya
Published: April 2024

Introduction

Although 200 000 adolescents undergo anterior cruciate ligament reconstruction (ACLR) surgery annually, no benchmarks for pediatric post-ACLR pain management exist. We created a multicenter, prospective, observational registry to describe pain practices, pain, and functional recovery after pediatric ACLR.

Methods

Participants (n=519; 12–17.5 years) were enrolled from 15 sites over 2 years. Data on perioperative management and surgical factors were collected. Pain/opioid use and Lysholm scores were assessed preoperatively, on postoperative day 1 (POD1), POD3, week 6, and month 6. Descriptive statistics and trends for opioid use, pain, and function are presented.

Results

Regional analgesia was performed in 447/519 (86%) subjects; of these, adductor canal single shot was most frequent (54%), nerve catheters placed in 24%, and perineural adjuvants used in 43%. On POD1, POD3, week 6, and month 6, survey response rates were 73%, 71%, 61%, and 45%, respectively. Over these respective time points, pain score >3/10 was reported by 64% (95% CI: 59% to 69%), 46% (95% CI: 41% to 52%), 5% (95% CI: 3% to 8%), and 3% (95% CI: 1% to 6%); the number of daily oxycodone doses used was 2.8 (SD 0.19), 1.8 (SD 0.13), 0, and 0. There was considerable variability in timing and tests for postdischarge functional assessments. Numbness and weakness were reported by 11% and 4% at week 6 (n=315) and 16% and 2% at month 6 (n=233), respectively.

Conclusion

We found substantial variability in the use of blocks to manage post-ACLR pain in children, with a small percentage experiencing long-term pain and neurological symptoms. Studies are needed to determine best practices for regional anesthesia and functional assessments in this patient population.
Combining EEG Features and Convolutional Autoencoder for Neonatal Seizure Detection
Authors: Wang Yuxia , Yuan Shasha , Liu Jin-Xing , Hu Wenrong , Jia Qingwei , Xu Fangzhou
Published: April 2024

Neonatal epilepsy is a common emergency phenomenon in neonatal intensive care units (NICUs), which requires timely attention, early identification, and treatment. Traditional detection methods mostly use supervised learning with enormous labeled data. Hence, this study offers a semi-supervised hybrid architecture for detecting seizures, which combines the extracted electroencephalogram (EEG) feature dataset and convolutional autoencoder, called Fd-CAE. First, various features in the time domain and entropy domain are extracted to characterize the EEG signal, which helps distinguish epileptic seizures subsequently. Then, the unlabeled EEG features are fed into the convolutional autoencoder (CAE) for training, which effectively represents EEG features by optimizing the loss between the input and output features. This unsupervised feature learning process can better combine and optimize EEG features from unlabeled data. After that, the pre-trained encoder part of the model is used for further feature learning of labeled data to obtain its low-dimensional feature representation and achieve classification. This model is performed on the neonatal EEG dataset collected at the University of Helsinki Hospital, which has a high discriminative ability to detect seizures, with an accuracy of 92.34%, precision of 93.61%, recall rate of 98.74%, and F1-score of 95.77%, respectively. The results show that unsupervised learning by CAE is beneficial to the characterization of EEG signals, and the proposed Fd-CAE method significantly improves classification performance.
Synchronization of complex networks with PID pinning controller
Authors: Lu Xinbiao , Chen Yudan , Chen Yisen , Gao Xing , Chen Guiyun , Yang Tieliu , Wu Wen
Published: April 2024

Recently, synchronization of complex networks has been studied deeply; however, most existing works take the standard proportional control strategy approach to pinning controllers, which produces a steady-state error and has a significant time of fluctuation. In order to solve this problem, we propose a new method using the Proportional-Integral-Differential (PID) control to design a pinning control method for synchronization of complex networks. Based on Lyapunov theory, the stability of the network is proved, and sufficient synchronization conditions are obtained. Finally, examples are given to evaluate the effectiveness of the proposed PID pinning method and compare it to the traditional proportional pinning controller and adaptive pinning controller.
A machine learning methodology for investigating the liquid–liquid transition of hydrogen under high-pressure
Authors: Li Shao , Zhang Chuanguo , Wang Xianlong , Zeng Zhi
Published: April 2024

Due to its unique properties such as superconductivity and superfluidity, high-pressure properties of hydrogen attract a lot of attention. However, the Liquid–Liquid Transition (LLT) of hydrogen under high-pressure and high-temperature is of particular significance for understanding its metallization. We propose a data-driven machine learning approach based on the density functional theory data to fit the potential energy surface into a deep neural network form. This method overcomes the simulation scale limitations of first-principles approaches to investigate the dissociation behavior of hydrogen molecules under high pressure. Our findings reveal an LLT curve exhibiting a first-order continuous change along with transition zone corresponding to hydrogen molecule dissociation. This study offers valuable insights into the LLT phenomenon and the metallization of hydrogen under high pressure.
Quantum-inspired vortex search algorithm with deep neural networks for multi-pose facial expression recognition
Authors: Bhatt Abhishek , Kant Rama , Luthra Monica , Jindal Sonika , Gudipalli Thejo Lakshmi , Jain Vishal , Meenu
Published: April 2024

The rapid expansion of artificial intelligence technologies has enabled machines to comprehend emotional intelligence. Among various indicators, facial expressions serve as an effective medium for understanding emotions. The concept of facial expression recognition (FER) relies heavily on the accurate and robust features available. Initially, the method of three-channel convolutional neural networks (TC-CNN) is adapted to extract facial features. However, only extracting the features is insufficient, the optimization of the extracted features is crucial to determining precise and robust features. This research work focuses on the optimization of the features using the quantum-inspired vortex search algorithm (QVSA). The QVSA integrates the attributes of Q-bits into the vortex search algorithm (VSA), optimizing the features by using the Q-bits to determine the vortex center on the Bloch sphere. The Q-bit attributes also improve the diversity of the features and help to avoid the premature convergence of the VSA. The final recognition of the facial expressions is performed using the deep neural network method of ResNet101v2. The experiments for facial expression recognition are performed on the datasets of RaFD and KDEF, which include different facial positions such as front pose, diagonal pose and profile pose. Performance comparisons demonstrate the effectiveness of the proposed system over state-of-the-art facial expression techniques.
Atmospheric Neutrino octant from flavor symmetry
Authors: Frampton Paul H. , Corianò Claudio , Santorelli Pietro
Published: April 2024

The binary tetrahedral group ([Formula: see text]) has provided the most successful flavor symmetry in understanding simultaneously the three mixing angles both for quarks in the CKM matrix and for neutrinos in the PMNS matrix. One prediction, invariant under leptonic CP violation, relates the atmospheric and reactor neutrino mixings [Formula: see text] and [Formula: see text], respectively. We study sedulously this relation using the latest neutrino data. It is natural to focus on the frustrating experimental octant ambiguity of [Formula: see text]. We conclude that the flavor symmetry requires that [Formula: see text] is in the second octant [Formula: see text], not in the first one [Formula: see text], and eagerly await experimental confirmation of this prediction.
Einstein–Podolsky–Rosen steering paradox “2=1” for N qubits
Authors: Liu Zhi-Jie , Zhou Jie , Meng Hui-Xian , Fan Xing-Yan , Xie Mi , Zhang Fu-Lin , Chen Jing-Ling
Published: April 2024

Einstein–Podolsky–Rosen (EPR) paradox highlights the absence of a local realistic explanation for quantum mechanics, and shows the incompatibility of the local-hidden-state models with quantum theory. For N-qubit states, or more importantly, the N-qubit mixed states, we present the EPR steering paradox in the form of the contradictory equality “[Formula: see text]”. We show that the contradiction holds for any N-qubit state as long as both “the pure state requirement” and “the measurement requirement” are satisfied. This also indicates that the EPR steering paradox exists in more general cases. Finally, we give specific examples to demonstrate and analyze our arguments.
Improved RSA with Enhanced Security on STM32 @ 84MHz
Authors: Sarkar Ankita , Jhamb Mansi
Published: April 2024

Enhanced computations resulted in the evolution of cyber-physical systems (CPS). These systems are highly vulnerable to security threats. This work addresses the security concerns for a reliable CPS in the Internet of Things (IoT) through an improvised RSA with enhanced security features. The proposed method renders data throughput encryption at 11.67[Formula: see text]Kbps with an overall average execution time of 0.02[Formula: see text]s. The proposed algorithm exhibits the unique feature of being asymmetric, lightweight & enhanced security owing to randomization (average entropy of 0.98). The performance metrics of the proposed method are compared with other state-of-art techniques. This algorithm is implemented on commercially competent architecture STM32F401RET6 with cortex M4 processor running @ 84[Formula: see text]MHz. The proposed encryption method exhibits great features thus making it a potential real-world solution.
Group-Based Federated Knowledge Distillation Intrusion Detection
Authors: Gao Tiaokang , Jin Xiaoning
Published: April 2024

Intrusion detection based on federated learning allows the sharing of more high-quality attack samples to improve the intrusion detection performance of local models while preserving the privacy of local data. Most research on federated learning intrusion detection requires local models to be homogeneous. However, in practical scenarios, local models often include both homogeneous and heterogeneous models due to differences in hardware capabilities and business requirements among nodes. Additionally, there is still room for improvement in the accuracy of recognizing novel attacks in existing researches. To address the challenges mentioned above, we propose a Group-based Federated Knowledge Distillation Intrusion Detection approach. First, through a step-by-step grouping method, we achieve the grouping effect of intra-group homogeneity and inter-group heterogeneity, laying the foundation for reducing the aggregation difficulty in intra-group homogenous aggregation and inter-group heterogeneous aggregation. Second, in intra-group homogenous aggregation, a dual-objective optimization model is employed to quantify the learning quality of local models. Weight coefficients are assigned based on the learning quality to perform weighted aggregation. Lastly, in inter-group heterogeneous aggregation, the group leader model’s learning quality is used to classify and aggregate local soft labels, generating global soft labels. Group leader models utilize global soft labels for knowledge distillation to acquire knowledge from heterogeneous models. Experimental results on NSL-KDD and UNSW-NB datasets demonstrate the superiority of our proposed method over other algorithms.
Identification of Key Classes in Software Systems Based on Static Analysis and Voting Mechanism
Authors: Mao Caiyun , Li Longjie , Liu Li , Ma Zhixin
Published: April 2024

Identifying key classes of a software system can help developers understand the system quickly, reduce the time for system maintenance, and prevent security risks caused by defects in key classes. So far, many approaches have been proposed to identify key classes from software systems. However, some approaches select too many key class candidates, making it inconvenient and difficult for developers to start understanding the system from these classes. For the other approaches, although the number of key class candidates is not large, their effectiveness needs to be further improved. To this end, in this paper, we propose a new model, named SAVM, to detect key classes by combining static analysis and a voting mechanism. First, we extract structural information from the source codes of a software system and construct a class coupling network (CCN) using this information. Then, we present the VRWD method that iteratively identifies important nodes in CCN based on a voting mechanism. Specifically, in each iteration, a node votes for its outgoing neighbors and in the meantime receives votes from its incoming neighbors. Afterward, the node that attains the highest voting score is elected as the important node in this turn. Finally, the corresponding classes of the selected important nodes are the key class candidates. The effectiveness of the proposed model and eight other baselines is evaluated in eight open-source Java projects. The experimental results show that although no method performs the best in all projects, according to the average ranking of the Friedman test, our method overall performs better compared to the baselines. In addition, this paper also proves through experiments that our approach can be applied to large-scale software projects. These indicate that our approach is a valuable technique for developers.
Adaptive Fuzzy Backstepping and Backstepping Sliding Mode Controllers Based on ICD Observer: A Comparative Study
Authors: Choueikh Safa , Kermani Marwen , M’Sahli Faouzi
Published: April 2024

This paper develops a Fuzzy Adaptive Backstepping Control (FABC) and a Fuzzy Adaptive Backstepping Sliding Mode Control (FABSMC) for Single-Input Single-Output (SISO) nonlinear-systems with unmeasured states. The proposed adaptive schemes are fully compared. Thus, the Fuzzy Type-2 (FT2) concept and the High-Order Integral-Chain Differentiator (HOICD) are used as two universal approximators. Indeed, the first one is employed to approximate the nonlinear system model’s and the second one to estimate the unknown states. Special attention is paid for the used approximators robustness under unmodeled dynamics, parameter variations and process noise.

It should be noted that the asymptotic stability of both the fuzzy adaptive controls and the observer convergence for each scheme have been proved. In addition, the employed schemes have been simulated on a two-tank coupled nonlinear system. Thus, from simulation results, we can prove that the proposed methods guarantee that all signals for closed loop systems are both regular and bounded. Specifically, it can be shown that the performances of the proposed Fuzzy Interval Type-2 (FIT2) schemes are significantly improved compared with Fuzzy Type-1 (FT1) schemes in presence of external disturbances.
Fuzzy Data Association-Towards Better Uncertainty Tracking in Clutter Environments
Authors: Peng Yi Jen , Lin Chun-Ta , Chen Yee Ming
Published: April 2024

The goal of explainable artificial intelligence (XAI) is to solve problems in a way that humans can understand how it does it. For data association there is growing demand for XAI, in which the measurement uncertainty and target (dynamic or/and measurement) model uncertainty are two fundamental problems in maneuvering target tracking in clutter. It commonly suffers of false alarms and missed detections. These situations focus on enhancing explainability, mitigating bias and creating better outcomes for all. Most the probabilistic data association (PDA) methods are weakly able, or even unable, to explain data association. To overcome these situations, the XAI components employed of two modules of Fuzzy-joint probability data association (FJDA) and Fuzzy maneuver compensator (FMC) are first established. Next, these two modules are further employed to construct maneuver tracking scheme, FJDA is then utilized to evaluate the association degree of measurements belonging to different targets and FMC plays compensation role in accordance with maneuver need. The performances of the proposed maneuver tracking scheme were compared with the PDA method and the joint probabilistic data association (JPDA) method using simulated radar surveillance data under a high cluttered environment. The numerical simulation proposed maneuver tracking scheme embedded XAI components FJDA/FCM having a remarkable improvement, due to fully utilize the useful knowledge information in the data association and reduces the impact of measurement uncertainties of the maneuvering target tracking with changing dynamics.
Algebraic groups in non-commutative probability theory revisited
Authors: Chevyrev Ilya , Ebrahimi-Fard Kurusch , Patras Frédéric
Published: April 2024

The role of coalgebras as well as algebraic groups in non-commutative probability has long been advocated by the school of von Waldenfels and Schürmann. Another algebraic approach was introduced more recently, based on shuffle and pre-Lie calculus, and results in another construction of groups of characters encoding the behavior of states. Comparing the two, the first approach, recast recently in a general categorical language by Manzel and Schürmann, can be seen as largely driven by the theory of universal products, whereas the second construction builds on Hopf algebras and a suitable algebraization of the combinatorics of non-crossing set partitions. Although both address the same phenomena, moving between the two viewpoints is not obvious. We present here an attempt to unify the two approaches by making explicit the Hopf algebraic connections between them. Our presentation, although relying largely on classical ideas as well as results closely related to Manzel and Schürmann’s aforementioned work, is nevertheless original on several points and fills a gap in the non-commutative probability literature. In particular, we systematically use the language and techniques of algebraic groups together with shuffle group techniques to prove that two notions of algebraic groups naturally associated with free, respectively, Boolean and monotone, probability theories identify. We also obtain explicit formulas for various Hopf algebraic structures and detail arguments that had been left implicit in the literature.
Vertical Vibration of a Rigid Cylindrical Foundation Embedded in a Half-Space of Unsaturated Poroelastic Soil
Authors: Zou Hongyun , Zhang Weijie , Xiong Feng , Lu Yang
Published: April 2024

This work presents an analytical method for determining vertical dynamic impedance and displacement response factor of a rigid cylindrical foundation embedded in unsaturated poroelastic soils. The foundation is assumed to be perfectly boned to its surrounding soil and its overlying half-space of unsaturated poroelastic soil, subjected to harmonic vertical loadings. The soil surrounding the circumference of the cylinder is modeled as a number of infinitely thin horizontal soil layers. Based on the Biot-type soil constitutive model, the equations governing the interaction of unsaturated soils with the cylindrical foundation are derived. Solutions are obtained by solving ordinary differential equations transformed from partial differential governing equations using the Hankel transform. The proposed solutions are verified against existing solutions of benchmark elastodynamic problems for embedded cylindrical foundations in dry and saturated soils. Using the derived solutions, several influencing parameters defining the stiffness and mass of the foundation system are examined to investigate the dynamics of the foundation interacting with it adjacent soils. It is concluded that the dynamic displacement response factor is sensitive to soil saturation. It is believed that the proposed solution should be beneficial to dynamic design with cylindrical foundations embedded in unsaturated soils.
Non-Invasive Deep-Brain Stimulations by Spatio-Temporal Fourier Synthesis
Authors: Kish Laszlo B. , Antal Andrea
Published: April 2024

A new type of non-invasive deep-brain stimulation is conceived and demonstrated by computer simulations. The process is based on spatio-temporal Fourier synthesis using multiple electrode pairs with sinusoidal current drive to limit skin sensations and concentrate the stimulus power to a small spatial volume and into large rare spikes in the time domain, while the signal power at the skin is steady and small. Exotic time signals are also shown, such as the cases of high-frequency prime harmonics, quasi-random and chirping stimulations. The first one is able to generate sharp spikes with low frequency while its carriers are high-frequency harmonics that easily conduct via the skin and brain tissue. Open questions are, among others, the best shapes and timing of spikes. The answers require experimental tests and explorations in animal models and human subjects.
An Information-Theoretic Approach to Analyze Irregularity of Graph Signals and Network Topological Changes Based on Bubble Entropy
Authors: Dong Keqiang , Li Dan
Published: April 2024

This work generalizes the recently introduced bubble entropy (BE) algorithm for univariate time series to graph and network analysis. In this paper, we introduce a modified method, called bubble entropy for graph signals ([Formula: see text], as an invaluable tool for detecting the irregularity of signals defined on graphs. Our algorithm is based on using the adjacency matrix to combine the signal values with the topology of the graph. Experiments on both synthetic and real data demonstrate the availability of the proposed measures in detecting the irregularity of graph signals and identifying topological changes in graphs.
On a Sobolev-type inequality and its minimizers
Authors: de Oliveira José Francisco , Silva Jeferson
Published: April 2024

Critical Sobolev-type inequality for a class of weighted Sobolev spaces on the entire space is established. We also investigate the existence of extremal function for the associated variational problem. As an application, we prove the existence of a weak solution for a general class of critical semilinear elliptic equations related to the polyharmonic operator.
Complex-valued temporal convolutional network for speech enhancement
Authors: Song Jiaqi , Zou Lian , Zhou Liqing , Liu Ziao , Fan Cien , Wang Bin
Published: April 2024

In this study, we introduce a novel approach to speech enhancement through the design of a complex temporal convolutional network (Complex-TCN). This model leverages the power of complex networks, enabling the simultaneous capture of both magnitude and phase information inherent in speech signals. By employing a temporal convolutional network, the Complex-TCN excels at extracting contextual information within the time domain of speech. Our findings underscore the substantial performance improvements achieved through the synergistic use of the temporal convolutional network and the incorporation of complex representations.
Sparse recovery with coherent frames via ℓ1−2-analysis
Authors: Xie Xizhe , Bi Ning , Chen Wengu
Published: April 2024

This paper introduces a nonconvex [Formula: see text]-analysis model: [Formula: see text] where [Formula: see text] is a measurement matrix and [Formula: see text] is a tight frame. Our main motivation is to generalize the sparse recovery via [Formula: see text] minimization to this new model. As a nonconvex model, it is well known that its global minimizer and local minimizer are usually inconsistent. This paper provides a type of null space property (NSP) characterization which are necessary and sufficient conditions for the measurement matrix [Formula: see text] such that a vector [Formula: see text] can be recovered from [Formula: see text] with a tight frame [Formula: see text] via [Formula: see text]-analysis local minimization, or any vector [Formula: see text] can be uniformly recovered from [Formula: see text] with a tight frame [Formula: see text] via [Formula: see text]-analysis minimization locally and globally.
Utilization of systematic error-assessment software to improve phylogenetic accuracy
Authors: Kim Hayeon , Lee Junghwan , Je Mikyeong , Cho Myeongji , Son Hyeon S.
Published: April 2024

Unlike classical systems based on the use of morphological data, modern phylogenetic analyses use genetic information to construct phylogenetic trees. Ongoing research in the field of phylogenetics is evaluating the accuracy of phylogenetic estimation results and the reliability of phylogenetic trees to explain evolutionary relationships. Recently, the probability of stochastic errors in large-scale phylogenetic datasets has decreased, while the probability of systematic errors has increased. Therefore, before constructing a phylogenetic tree, it is necessary to assess the causes of systematic bias to improve the accuracy of phylogenetic estimates. We performed analyses of three datasets (Terebelliformia, Daphniid, and Glires clades) using bioinformatics software to assess systematic error and improve phylogenetic tree accuracy. Then, we proposed a combination of systematic biases capable of discerning the most suitable gene markers within a series of taxa and generating conflicting phylogenetic topologies. Our findings will help improve the reliability of phylogenetic software to estimate phylogenies more accurately by exploiting systematic bias.
Design Optimization of Flexural and Eigenvalue Characteristics of Perforated and Skewed Bio-Composite Functionally Graded Panels
Authors: Joshi Kamal Kishore , Kar Vishesh Ranjan
Published: April 2024

The development of novel materials is of prime importance in the biomedical areas, especially for bone replacements and dental implants. This study uses finite element modeling of skewed functionally graded bio-composite structures with perforations to examine flexural and eigenfrequency responses. Here, the bio-composite structure comprises Titanium (Ti) and Hydroxyapatite (HAp). Voigt’s micromechanical material model via power-law distribution and Representative volume element (RVE) method is utilized to compute the in-homogenous material properties in the thickness direction. The strain field is based on the equivalent single-layer first-order shear deformation theory with five degrees of freedom, and the governing equations are obtained using principle of minimum potential energy. A computer algorithm is developed in a 2D finite element platform using eight-noded quadrilateral elements. The mesh stability of the skewed and perforated structure is confirmed through the smart mesh technique, and the present model’s accuracy is demonstrated by comparing it with the available reported results. Numerous examples reveal the significance of material gradation, skewness, aspect ratios, perforations, and support conditions on bio-composite functionally graded structures’ flexural and eigenfrequency responses. Furthermore, parametric optimization is conducted to minimize the flexural response and maximize the fundamental frequency by employing the response surface methodology (RSM), followed by determining optimal process parameters and valuable findings.
Superconvergence of a Nonconforming Brick Element for the Quad-Curl Problem
Authors: Zhou Xinchen , Meng Zhaoliang , Niu Hexin
Published: April 2024

This paper shows the superconvergence of an [Formula: see text](grad curl)-nonconforming brick element, which is very recently introduced in Wang et al. [Fully [Formula: see text](grad curl)-nonconforming finite element method for the singularly perturbed quad-curl problem on cubical meshes, preprint (2023), arXiv:2301.03172] for the quad-curl problem. The supercloseness is based on proper modifications for both the interpolation and the discrete formulation, leading to superclose [Formula: see text] in the discrete grad, curl norm. Moreover, we propose a suitable postprocessing method to ensure the global superconvergence. Numerical results verify our theory.
Rietveld Refinement, Structural Morphology and Magnetic Properties of La0.57Sm0.1Sr0.33−xBaxMnO3 Manganite Nanoparticles
Authors: Pathan A. N. , Mane M. L. , Barote Vinod K. , Batoo Khalid Mujasam , Hadi Muhammad , Shirsath Sagar E. , Kadam R. H. , Mane D. R.
Published: April 2024

Lanthanide-based manganite perovskites due to their possible integration both in conventional Si-based electronics, and in innovative full-oxide electronics, have led to a massive resurgence of interest. The properties and applicability of these perovskites can be tailored with the interplay of foreign ion substation, and thus lot of efforts have been made by the researchers by using various types of compound combinations. In this work, a systematic study of Ba-substituted lanthanide of a chemical formula La[Formula: see text]Sm[Formula: see text]Sr[Formula: see text]Ba[Formula: see text]MnO3 (where, [Formula: see text], 0.05, 0.1, 0.20 and 0.33) was done and the manganites were synthesized by sol–gel auto-combustion method. The structural and magnetic properties were investigated by thermogravimetric/differential thermal analysis, which was also carried out to investigate the thermal stability of the prepared samples. X-ray diffraction (XRD) patterns, transmission electron microscopy (TEM), scanning electron microscopy (SEM) etc. were employed to investigate the crystallographic structure. XRD patterns and selected area electron diffraction patterns revealed the formation of single-phase La[Formula: see text]Sm[Formula: see text]Sr[Formula: see text]Ba[Formula: see text]MnO3 perovskite materials without any signature of secondary phases. Elemental composition of the synthesized samples was investigated by the energy dispersive analysis of X-ray analysis, which confirmed the expected stoichiometry of the prepared samples. TEM and SEM observations revealed the nano-crystalline nature of the prepared samples, where particle size obtained from TEM ranges from 40[Formula: see text]nm to 70[Formula: see text]nm. It has been found that structural and magnetic properties of the parent La[Formula: see text]Sm[Formula: see text]Sr[Formula: see text]MnO3 system were greatly affected by the Ba substitution.
Global insights into seed dispersal mutualism with cooperative efforts and environmental variability
Authors: Feng Tao , Shan Xiquan , Zhu Zhiwei
Published: April 2024

Seed dispersal mutualisms assume a crucial role in sustaining overall ecosystem functionality. This study extends the foundational framework of seed dispersal mutualism by incorporating animal cooperation and environmental variability. Through the integration of stability theory and phase analysis, we investigate the global dynamics of seed dispersal mutualism in deterministic environments. Theoretical findings reveal that the deterministic system exclusively exhibits equilibrium dynamics, ruling out periodic solutions and chaotic phenomena. Notably, in cases of multiple coexisting equilibria, adjacent equilibria display distinct stability properties. Furthermore, employing stochastic analysis and Lyapunov exponents, we ascertain the uniqueness of global positive solutions in the stochastic model, along with stochastic ultimate boundedness, and precise thresholds for the stochastic persistence and extinction. These results illuminate the theoretical mechanisms governing transitions in seed dispersal mutualism across various stable population levels and underscore the insights into how essential biological factors, including animal cooperation efforts and environmental variability, impact the long-term dynamics of seed dispersal mutualism.
Coexistence and bistability of a modified Leslie–Gower predator–prey model with mixed movement for the predator and Holling-type II schemes
Authors: Zhang Baifeng , Zhang Guohong , Wang Xiaoli
Published: April 2024

This paper centers on the analysis of the dynamics of a modified Leslie–Gower predator–prey model employing Holling-type II schemes, with the prey exhibiting pure random diffusion and the predator undergoing a mixed form of movement. The extinction of species and uniform persistence of this system are explored, and several conditions for the stability, uniqueness and multiplicity of positive steady-state solutions are derived. In contrast to the specialist and generalist predator–prey systems in open advective environments, the dynamics of this system are more intricate. It emerges that multiple positive steady-state solutions and the bistable phenomenon exist for this system when a small advection rate and a moderate predation rate are imposed. Numerical simulations reveal that the increase of diffusion rate for prey disadvantages the survival of itself and has no impact on predator invasion, while the increase of diffusion rate for predators favors the invasion of itself.
Passive Institutions and Long-Run CEO Compensation: Evidence from Proxy Voting
Authors: Jang In Ji
Published: April 2024

A one-standard-deviation increase in passive ownership leads to a 25% increase in the compensation duration. I find proxy voting is the channel through which passive investors affect incentive horizons. Since the passage of the Dodd-Frank Act, passive funds tend to vote more against Say-on-Pay (SOP) proposals, and SOP proposals are less likely to pass with higher passive ownership. Moreover, passive ownership is associated with a greater number of shareholder-sponsored compensation proposals and an increased likelihood of these proposals passing. The overall findings indicate that passive institutions work to lengthen CEO compensation to align incentive horizons, and proxy voting is the mechanism through which they exert influence.
Averages of products of characteristic polynomials and the law of real eigenvalues for the real Ginibre ensemble
Authors: Tribe Roger , Zaboronski Oleg
Published: April 2024

We review an elementary derivation of the Borodin–Sinclair–Forrester–Nagao Pfaffian point process, which characterizes the law of real eigenvalues for the real Ginibre ensemble in the large matrix size limit, in terms of averages of products of characteristic polynomials. This derivation relies on a number of interesting structures associated with the real Ginibre ensemble such as the hidden symplectic symmetry of the statistics of real eigenvalues. It leads to a representation for the [Formula: see text]-point correlation function for any [Formula: see text] in terms of an integral over the symmetric space [Formula: see text] and this paper gives the proof of asymptotic exactness for this integral.
Novel Cholesterol-Based Dihydropyrimidinone Derivatives with Potential Biological Activities: An In-silico Investigation
Authors: Bendi Anjaneyulu , Kaur Navjot , Chinmay  , Vishaka  , Raghav Neera , Kaushik M. P.
Published: April 2024

Steroids play essential physiological roles in the living systems, including their role as sex hormones, glucocorticoids, and mineralocorticoids. Usually, they engage in interactions with steroid receptors. Target cell nuclei, cytosol and plasma membranes all have steroid hormone receptors. Cytoplasmic or nuclear, intracellular receptors start the signal transduction process for steroid hormones and cause gene expression alterations over the course of several hours to days. Certain steroid hormones bind to cell surface receptors, including ion channels, G protein-coupled receptors and several nuclear receptors. Dihydropyrimidinones are also significant moieties with important physiological roles. The hybrid molecules can offer several potential biological activities. In this work, we have checked the in silico interaction of some novel cholesterol–dihydropyrimidinones interactions with the sex hormones, mineralocorticoid and glucocorticoid receptors to screen their potential use in the regulation of the sexual cycle or the carbohydrate metabolism or the mineral imbalance.
The Electronic, Optical, and Mechanical Properties of Quasi-One-Dimensional Molybdenum Sesquisulfide Mo2S3: A Density Functional Theory Study
Authors: Tse Geoffrey
Published: April 2024

In this work, a study on structural, electronic, optical, and mechanical properties of monoclinic-type Mo2S3 (space group P21/M) has been examined. Optimized lattice constants of [Formula: see text][Formula: see text]Å, [Formula: see text][Formula: see text]Å, [Formula: see text][Formula: see text]Å and bond angles of [Formula: see text], [Formula: see text] have been calculated, and it appears that they are in close match to other theoretical and experimental data. Our bandstructure and density of states confirm the metallic properties of the molybdenum sesquisulfide, which also agrees well with other theoretical data. Importantly, the electron orbitals found in conduction (valence) bands can provide an explanation of covalent Mo–Mo (Mo–S) bonding inside the Mo2S3 lattice. For optical properties, a high absorption coefficient of [Formula: see text] has been obtained, suitable for applications within the vacuum ultraviolet (VUV) range. Our high reflectivity calculation suggests the use of metallic coating on other materials to reflect light. For mechanical properties, our elastic data also confirm the material’s stability mechanically, identifying it as covalent, anisotropic, and brittle. The micro-machinability parameter calculated further suggests that such material could be used as lubricants or oils for applications in mechanical engineering.
Supply and Demand and the Term Structure of Interest Rates
Authors: Greenwood Robin , Hanson Samuel , Vayanos Dimitri
Published: April 2024

We survey the growing literature emphasizing the role that supply and demand forces play in shaping the term structure of interest rates. Our starting point is the Vayanos and Vila model of the term structure of default-free bond yields, which we present in both discrete and continuous time. The key friction in the model is that the bond market is partially segmented from other financial markets: The prices of short-rate and bond supply risks are set by specialized bond arbitrageurs who must absorb shocks to the supply and demand for bonds from other preferred-habitat agents. We discuss extensions of this model in the context of default-free bonds and other asset classes.
Electrochemical Oxidative Cross-Coupling Reactions of Ketene Dithioacetals and Dichalcogenides to Construct C−Se/C−S Bonds
Authors: Wang Jiaxu , Liu Xin , Feng Chenglong , Sun Qing , She Yuanbin , Shen Zhenlu , Li Meichao
Published: April 2024

A green protocol for construction of C−Se bonds from ketene dithioacetals and diselenides through direct electrochemical oxidative cross-coupling has been developed. This reaction was carried out in an undivided cell system with NaBF4 as the electrolyte and CH3CN as the solvent through galvanostatic electrolysis. A series of substituted ketene dithioacetals and diselenides were tolerant and the desired tetrasubstituted alkenyl selenides were obtained in moderate to excellent yields. In addition, construction of C−S bond from ketene dithioacetals and disulfides through electrochemical method in the presence of KI was also successfully realized. It exhibited high efficiency and broad functional group tolerance.
Bacterial-Polyhydroxybutyrate for Biocompatible Microbial Electrodes
Authors: de Moura Torquato Lilian Danielle , Lacalamita Dario , Matteucci Rosa Maria , Franco Jefferson Honorio , Labarile Rossella , Perrotta Alberto , Trotta Massimo , Farinola Gianluca Maria , Boldrin Zanoni Maria Valnice , Grattieri Matteo , Stufano Paolo
Published: April 2024

The development of bioelectrochemical systems requires careful selection of both their biotic and abiotic components to obtain sustainable devices. Herein, we report a biophotoelectrode obtained with polyhydroxybutyrate (PHB), a biopolymer, which purple non-sulphur bacteria produce as an energy stock under specific environmental conditions. The electrode was obtained by casting a mixture composed of PHB and carbon fibers in a 3:2 mass ratio. Following, the composite material was modified with polydopamine and thermally treated to obtain a hydrophilic electrode with improved electrochemical behavior. The bio-based electrode was tested with metabolically active cells of Rhodobacter capsulatus embedded in a biohybrid matrix of polydopamine. The system achieved enhanced catalytic activity under illumination, with an 18-fold increase in photocurrent production compared to biophotoelectrodes based on glassy carbon, reaching a current density of 12 ± 3 μA cm−2, after 30 min of light exposure at +0.32 V. The presented biocompatible electrode provides a sustainable alternative to metal-based and critical raw material-based electrodes for bioelectrochemical systems.
Influence of the Hydraulic Circuit Setup on the Dynamic Performance of an Axial Piston Pump by Numerical and Experimental Analysis
Authors: Chakroun Ala Eddin , Battarra Mattia , Mucchi Emiliano
Published: April 2024

The hydraulic circuit in hydraulic mechanisms may be the cause of several vibration anomalies. Flexible pipes, in particular, commonly used in test rigs, may be the source of vibration issues due to their relatively low natural frequencies altering the pump noise, vibration, and harshness (NVH) performance. The purpose of this study is to detail a methodology based on lumped parameter modeling and experiments to analyze the circuit NVH behavior. An experimental study is carried out on two pump designs to determine the outlet pressure fluctuation of various test rig configurations. Numerical simulations are also performed to simulate the actual behavior of the hydraulic system considering these different test configurations. The tests are carried out at a chosen frequency range with a hydraulic circuit configuration representing realistic layouts. In these situations, the hydraulic circuit layout can be the source of NVH anomalies. Realistic design solutions are proposed to modify the test rig NVH behavior in order to achieve a flat response throughout the desired working range.
Italian Fast Speech Reception Threshold Test: A New Method to Investigate Adult Auditory Impairment in Noise
Authors: Cantore Italo , Lapenna Ruggero , Di Nardo Walter , Forli Francesca , Grassia Rosa , Murri Alessandra , Scorpecci Alessandro , Muzzi Enrico , De Lucia Antonietta , De Paolis Fabrizio , Ricci Giampietro , Rolesi Rolando , Berrettini Stefano , Sicignano Stefania , Quaranta Nicola , Marsella Pasquale , Orzan Eva , Della Volpe Antonio , Ruscito Paolo
Published: April 2024

Introduction: Purpose of our study was to compare two competing methods of performing bisyllabic word speech audiometry for the detection of the 50% speech reception threshold in noise (SRT50). Methods: Classic method is performed submitting multiple word lists at a fixed signal-to-noise ratio. A newer Fast method – Italian Fast Speech Reception Threshold 50 (IFastSRT50) – is performed by means of program software with a single list of bisyllabic words and noise intensity shifting. Results: Means comparison between SRT50 Classic and IFastSRT50 shows a slight significant correlation (r = 0.263; p = 0.044) and a wide significant difference: SRT50 Classic = −2.763 dB (SD = 4.1) and IFastSRT50 = −7.803 dB (SD = 2.1) (p < 0.0001). There is a high difference between the test execution time means (SRT50 Classic = 11 min, IFastSRT50 = 2 min; p < 0.0001). The correlation between test results and execution times was higher for SRT50 Classic than IFastSRT50. Conclusion: IFastSRT50 test is a reliable method to quickly investigate signal-to-noise ratio needed to obtain 50% of recognition scores with bisyllabic words; it allows less execution time than SRT50 Classic method and can avoid patient fatigue and other limitations of different speech discrimination tests in noise as sentences based ones.