bluuebunny/crossref_metadata_2025 huggingface dataset:
Clonal response of a recalcitrant understory shrub, Labrador tea (Rhododendron groenlandicum Oeder.) to forest gaps
Authors: Moola Faisal , Ni Yu Zhao , Mallik Azim U.
Published: July 2024

After canopy removing disturbance, recalcitrant understory shrubs can rapidly occupy the forest understory to the detriment of tree regeneration and growth. The expansion of recalcitrant species has been documented following stand replacing disturbances, such as fire and timber harvest. However, there is little information on how these species respond to much smaller canopy gaps created by the senescence and (or) death of single or groups of canopy trees. In this study, we determined the response of Labrador tea ( Rhododendron groenlandicum Oeder.), a recalcitrant ericaceous shrub, to canopy gaps in a late-successional boreal forest in northwestern Ontario, Canada. We evaluated functional traits related to the morphology and regeneration strategy of this plant to elucidate the mechanism of gap filling. We found that R. groenlandicum abundance and vigor were greater at the center of treefall gaps than in gap edges or the forest understory due to aggressive sprouting from buried clonal bud banks. Layering was higher in canopy gaps than in the understory. The composition of ground cover and rooting substrate was more influential on the adventitious rooting of the layered stems than increased light availability in gaps. We found a strong response of R. groenlandicum to small canopy openings, suggesting that the species can form recalcitrant understory layers even in the absence of stand replacing disturbance.
Toy models of gravitational shielding in the framework of Newtonian theory of gravitation
Authors: Berim Gersh O.
Published: July 2024

In the framework of Newtonian theory of gravitation, three toy models of a hypothetical gravitational shield (GS) are developed. To satisfy the energy conservation law which is violated in the presence of GS, an existence of a special kind of energy (“G-energy”) responsible for shielding and stored in GS is postulated. The models differ from each other by the details of the spatial dependence of the net gravitational acceleration in the presence of GS as well as by the dependence of that acceleration on the amount of G-energy in GS. As an example, the rotation of a dumbbell like object located at the boundary between the regions of space where gravity is affected and not affected by GS is analyzed in details. The motivation to study gravitational shielding, the very existence of which is challenged, is the presence of steadily repeating attempts to observe this phenomenon. No doubt, such attempts will continue in the future. The results obtained in the present paper could be useful in designing such a research.
Swarm of drones for surveillance monitoring of a grounded target: an event-triggered approach
Authors: Hashemzadeh F. , Kumbasar T.
Published: July 2024

In this paper, we present a novel formation control approach in the framework of event-triggered (ET) control to provide a solution to the surveillance problem. To do this, we identify two main challenges which are the switching topology of the drones and the limited bandwidth of the communication network, which are also valid in formation applications. To provide a solution to switching topologies, we propose a networked continuous controller that is robust in the presence of connection switching between drones and the target. Then, we propose a networked controller with ET communication in some aperiodic instants which reduces the required bandwidth and load within the communication network. We guarantee the stability of the developed ET controller and prove that the Zeno behavior cannot occur. To validate the method, we present realistic 3D simulation results conducted in the Simulink environment of Matlab® for different scenarios. The results of the study show the effectiveness of the proposed controller, especially for limited bandwidth channels as the ETC scheme has decreased the load within the communication network while resulting in a robust and efficient formation performance. We also considered moving target scenarios with missing possibilities to validate the robustness of the proposed method.
Design and analysis of a novel rotary inertance hydraulic converter with the continuous controlling turntable
Authors: Fang Delei , Jia Guofeng , Wang Jianwei , Wu Guoheng , Cao lin , Zhang Junxia
Published: July 2024

The inertance hydraulic converter is an energy-efficient hydraulic component, its output efficiency and dynamic performance are seriously affected by the switched valve. This paper proposed an innovative a rotary inertance hydraulic converter (RIHC), which uses a continuous controlling turntable to determine the ratio of the high pressure oil and the low pressure oil to change the output energy, instead of the discrete controlling of the switched valve. The working principle and mechanical design of the RIHC are described, and mathematical models are established. The effects of the key variables on energy efficiency are evaluated using numerical analysis. The operating performance is analyzed based on simulation, and a control strategy to achieve stable system output is proposed. The results provide a foundation for theoretical research and practical application of the novel RIHC.
Parabolic Finslerian Allen–Cahn equation and its Harnack inequality
Authors: Shen Bin , Zhang Hao
Published: July 2024

Parabolic Finslerian Allen–Cahn equation is a quasilinear parabolic equation on Finsler metric measure spaces. In this paper, we establish a Harnack inequality for solutions to this equation on compact Finsler metric measure spaces using geometric methods. Moreover, we give a degree 4 polynomial gradient estimate of the traveling wave solution on flat-curved spaces.
Expected Values in Complex Networks Constructed Using a Compression Algorithm to Time Series
Authors: Carareto Rodrigo , El Hage Fabio S.
Published: June 2024

This paper introduces a methodology for computing expected values associated with compression networks resulting from the application of compression algorithms to independent and identically distributed random time series. Our analysis establishes a robust correspondence between the calculated expected values and empirically derived results obtained from constructing networks using nondeterministic time series. Notably, the ratio of the average indegree of a network to the computed expected indegree for stochastic time series serves as a versatile metric. It enables the assessment of inherent randomness in time series and facilitates the distinction between nondeterministic and chaotic systems. The metric demonstrates high sensitivity to nondeterminism in both synthetic and real-world datasets, highlighting its capacity to detect subtle disturbances and high-frequency noise, even in series characterized by a deficient sample rate. Our results extend and confirm previous findings in the field.
Chaotic Dynamic Behavior of a Fractional-Order Financial System with Constant Inelastic Demand
Authors: Gao Xiao-Long , Li Zhi-Yuan , Wang Yu-Lan
Published: July 2024

The establishment of a financial system should not only consider the current situation, but also need to refer to the past. Due to the memory of the fractional derivative, a fractional-order system can more effectively describe the historical significance of the financial system. Most scholars use the prediction–correction scheme to study fractional-order systems. This paper provides a higher-precision numerical method for the financial system, which more effectively simulate the system. Based on the definition of the Grünwald–Letnikov fractional derivative, the integer-order system with nonconstant demand elasticity is extended to the fractional-order setting, and its dynamic behavior is studied, with some novel chaotic attractors found. The research results are helpful for improving the understanding of the financial system and the financial market and for predicting financial risks.
Constructing Memristive Hindmarsh–Rose Neuron with Countless Coexisting Firings
Authors: Zhang Xin , Li Chunbiao , Tang Qianyuan , Yi Chenglong , Yang Yong
Published: June 2024

Memristor synapses have been widely introduced into neuronal models to investigate the effects of external magnetic fields. However, there is a relative lack of research on the external-induced electric fields in neurons. In this paper, a 4D-memristive Hindmarsh–Rose neuron model is constructed by introducing a memristor and an electric field variable, which can generate complex neural firing. Notably, numerical simulations reveal that the initial conditions of the memristor can induce different firing patterns, exhibiting a unique fractal structure in the basin of attractions. Remarkably, the offset parameters of the internal variables of the neuron can be canceled out so that the offset boosting of the variables can be achieved according to the initial values, giving rise to an uncountably many hidden attractors with homogeneous multistability. This model provides the first example of generating uncountably many attractors in a memristive neuron model without relying on trigonometric functions, significantly advancing our understanding of neuronal dynamics. Finally, a digital circuit is designed and implemented on the RISC-V platform to verify the numerical simulation and theoretical analysis. The findings of this study have a certain implication for the development of advanced neuromorphic computing systems and the understanding of complex neuronal behaviors in the presence of external electric fields.
Modeling the Effect of Informal and Formal Jobs on the Dynamics of Unemployment
Authors: Misra A. K. , Kumari Mamta
Published: July 2024

The limited availability of formal jobs in developing nations always heightens the challenge for unemployed individuals in securing regular employment. Temporary employment in the informal sector serves as a source to fulfill their basic needs and enhance their employable skills. In this paper, we introduce a nonlinear mathematical model to study the effect of informal and formal jobs on the dynamics of unemployment. For the model formulation, we categorize the labor force into three classes: unemployed, temporary employed, and regularly employed. A separate dynamical variable is used to represent the available temporary vacancies. It is assumed that temporarily employed individuals may transition into regular employment or self-employment. Furthermore, self-employed individuals contribute to generating temporary vacancies within the informal sector. The long-term behavior of the proposed system is analyzed using the qualitative theory of differential equations. A quantity known as the reproduction number of the system is derived, and it is found that the occurrence of multiple bifurcations for the proposed system is influenced by the value of this threshold quantity. Furthermore, we validate our analytical findings numerically. The findings of this study illustrate that an increase in the shifting rate of individuals from temporary to regular employment is not always effective in increasing the number of regularly employed individuals. Additionally, an increase in the transition of temporarily employed individuals into self-employment, coupled with their involvement in creating more temporary jobs, proves beneficial in reducing unemployment.
Some Interesting Bifurcation Phenomena in the Generalized KdV–mKdV-Like Equation
Authors: Chen Yiren , Liang Yan , Gao Xuefeng , Chen Si , Han Yu
Published: July 2024

We investigate novel bifurcation phenomena in the generalized KdV–mKdV-like equation. Unlike previous phase diagram studies, we choose variables related to wave speed as the coordinate axis, which led us to discover some interesting bifurcation phenomena. Our method can also be extended to study some other bifurcation phenomena in equations.
THE FRACTIONAL DISEN–FISHER PLANE: AN EFFECTIVE APPROACH TO DISTINGUISH COMPLEX TIME SERIES
Authors: LI ANG , SHANG DU , SHANG PENGJIAN
Published: June 2024

With the explosive growth of data quantity and rapid development of nonlinear dynamics as well as the growing demand for complex data classification in the field of artificial intelligence and machine learning, the research of complex time series, generated by complex systems, has attracted enormous interests. However, how to simultaneously distinguish different types of time series data and extract more accurate and detailed information from them in the light of localized and global scale perspectives remains significant and needs to be tackled. Thus, in this paper, we propose the fractional DisEn–Fisher plane, which is innovatively constructed by the fractional form of dispersion entropy and Fisher information measure. These are both effective tools to diagnose the essential properties of complex time series, to analyze the complexity of systems and to depict the contained statistical information with higher accuracy and effectiveness. Several classical entropy plane methods are selected as a comparison to design simulation experiments by simulated data and three real-world datasets. Comparative experimental results show that this method is a feasible and reliable improvement method, which will help to provide more additional information in time series recognition and dynamic characterization. It may not only provide new insights for further improvement of complex time series analysis, but also have important implications for developing complex data clustering methods.
EFFECT OF TiC ADDITION ON MICROSTRUCTURE AND PROPERTIES OF LASER CLADDING AlCoCrFeNi2.1 COATINGS ON H13 STEEL
Authors: YANG CHU , JING CAINIAN , LI NING , XU JUNJIE , LIU ZEJIAO , LIN TAO , ZHAO JINGRUI , GUO WEIMIN
Published: June 2024

[Formula: see text][Formula: see text][Formula: see text][Formula: see text]xwt.%TiC ([Formula: see text], 6, 9) coatings were prepared on H13 steel by laser cladding (LC) technology. It was characterized by a friction and wear test machine, optical microscope (OM), X-ray diffractometer (XRD), hardness tester, etc. The effects of different TiC contents on the microstructure and properties of [Formula: see text] coatings were analyzed. The results show that the coating microstructure without TiC addition is dominated by coarse columnar crystals and dendrites. After the addition of TiC, the coated massive crystals and equiaxed crystals become finer. XRD analysis reveals that the phase structure of the coating has FCC, B2 solid solution phase and TiC-reinforced phase. TiC phase can significantly improve the hardness of the coating. The microstructure reveals that fine TiC particles are widely distributed among the dendrites of the FCC matrix. The hardness and friction wear experiments revealed that the average hardness of the coatings with TiC has increased significantly compared to that of the substrate. The hardness of the [Formula: see text] with 9%TiC coating increased by 184.6% compared to that of the substrate. The friction coefficient was the smallest at 0.748. The lowest self-corrosion current was [Formula: see text][Formula: see text][Formula: see text]. The [Formula: see text] with 9%TiC coating had the best corrosion resistance.
STRUCTURAL CHANGES IN CORTICAL BONE AFTER BOMBARDMENT WITH LOW-ENERGY HYDROGEN IONS
Authors: DESOUKY O. S. , ABDELREHEEM A. M. , EL-MARAKBY S. M. , SELIM N. S.
Published: June 2024

Radiobiological studies focused mainly on tracking the effects of photons (X and gamma rays) and high-energy charged particles over low energy ions, which raises interest in studying their biological effects. Therefore, the aim of this study is to investigate the interaction of low-energy hydrogen ions beam with xcortical bovine bone as a biological model. A hydrogen ions beam was used to bombard cortical bone with different fluences; 45, 70 and [Formula: see text][Formula: see text]ions/cm2 at low energy of 5[Formula: see text]keV. The interaction of hydrogen ions with cortical bone was estimated theoretically by the SRIM/TRIM code. The obtained results showed that the average distribution range and the maximum depth for 5[Formula: see text]keV hydrogen ions are 91 and 150[Formula: see text]nm respectively. The energy losses from incident ions are 4.45[Formula: see text]keV for ionization, 170[Formula: see text]eV for phonons and 18[Formula: see text]eV for vacancies. Also, the energy losses from the recoil atoms are 119[Formula: see text]eV for ionization, 234[Formula: see text]eV for phonons and 8[Formula: see text]eV for vacancies. At the same time, the effect of low-energy hydrogen ions bombardment on the structure of bone was studied by X-ray diffraction (XRD) and FTIR.
Tomato Plant Disease Identification via Deep Learning Technique
Authors: Bhosale Supriya , Chhabria Aditi
Published: June 2024

Tomatoes are edible berries that are utilized extensively around the world. Their scientific name is solanum lycopersicum. Many tomato varietals are primarily produced in temperate climates. Even though tomatoes are used as ingredients in food, they are botanically categorized as berries. Bacterial spot, Black mold, Gray spot, Late blight, and powdery mildew (PM) are the primary diseases that affect tomato plants. The most challenging process in this decade is also the early diagnosis of these disorders. In this study, the suggested method is applied to the assessment of disease severity and disease diagnosis in tomato plant images. There are various stages to the procedure. The tomato plant image is initially pre-processed using the Wavelet technique, and then the modified Watershed algorithm is used to segment the image using improved Double Sigmoid and Erosion (WSA-IDS&E). The segmented image is then processed in the feature extraction stage in order to extract features. The Gray Level Co-occurrence Matrix (GLCM), histogram, illness area, and pixel-based retrieved characteristics are fed into the CNN model, a deep learning method for identifying diseases. In addition, a novel training method, WUDHOA, which adjusts the CNN’s weight, is introduced in this study to improve the performance of deep learning techniques. In addition, the severity of the tomato plant illness is measured in order to improve disease identification outcomes, where this severity assessment is taken into account using a fresh evaluation. Finally, the performance of the detection outcome is compared with other existing works to prove its efficiency. The conventional techniques have the lowest specificity ratings, such as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], whereas the WUDHOA achieved a specificity of 0.9384.
On the μF-subgroups of some finite Abelian groups
Authors: Singh Shailesh , Kharat Vilas , Agalave Manish
Published: June 2024

In this paper, the concept of [Formula: see text]-subgroup is introduced. It is proved that in finite cyclic groups [Formula: see text], the collection [Formula: see text] of all [Formula: see text]-subgroups of [Formula: see text] is a sublattice of [Formula: see text]. It is also proved that [Formula: see text] is not a sublattice of [Formula: see text] in general. Further, a characterization is obtained for [Formula: see text] to be a sublattice of [Formula: see text].
Asymptotic behavior for nonlinear textiles with glued yarns
Authors: Falconi Riccardo , Griso Georges , Orlik Julia
Published: July 2024

This paper is dedicated to the homogenization and dimension reduction for a nonlinear elasticity problem of a textile structure. The structure is represented as a squared piece of cloth and modeled as a woven canvas made of long and thin fibers, crossing each other in a periodic pattern. The squared domain is partially clamped on the left and bottom. The fibers are assumed to be glued, a condition that allows to extend the woven structure to a non-perforate plate. The nonlinear elasticity problem is stated via minimization over the energy functional. The homogenization is made via the periodic unfolding method, with an additional dimension reduction. Since the existence of a minimum of the limit energy functional is not ensured, sufficient conditions for the existence are given by assuming that the material is homogeneous and isotropic.
Fake News Detection: Traditional vs. Contemporary Machine Learning Approaches
Authors: Binay Aditya , Binay Anisha , Register Jordan
Published: June 2024

Fake news is a growing problem in modern society. With the rise of social media and ever- increasing internet accessibility, news spreads like wildfire to millions of users in a very short time. The spread of fake news can have disastrous consequences, from decreased trust in news outlets to overturned elections. Such concerns call for automated tools to detect fake news articles. This study proposes a predictive model that can check the authenticity of a news article. The model is constructed using two different techniques to construct our model: (1) linguistic features and (2) feature extraction. We employed some widely used traditional (e.g. K-nearest neighbour (KNN) and support vector machine (SVM)) as well as state-of-the-art (e.g. bidirectional encoder representations from transformers (BERT) and extreme machine learning (ELM)) machine learning algorithms using feature extraction methods and linguistic features. After generating the models, performance metrics (e.g. accuracy and precision) are used to compare their performance. The model generated via logistic regression using feature hashing vectorisation emerged as the best model, with 99% accuracy. To the best of our knowledge, no extant studies have compared the traditional and contemporary methods in this context and demonstrated the traditional ones to be better performers. The fake news detection model can help curb the spread of fake news by acting as a tool for news organisations to check the authenticity of a news article.
Construction of transcript regulation mechanism prediction models based on binding motif environment of transcription factor AoXlnR in Aspergillus oryzae
Authors: Oka Hiroya , Kojima Takaaki , Kato Ryuji , Ihara Kunio , Nakano Hideo
Published: June 2024

DNA-binding transcription factors (TFs) play a central role in transcriptional regulation mechanisms, mainly through their specific binding to target sites on the genome and regulation of the expression of downstream genes. Therefore, a comprehensive analysis of the function of these TFs will lead to the understanding of various biological mechanisms. However, the functions of TFs in vivo are diverse and complicated, and the identified binding sites on the genome are not necessarily involved in the regulation of downstream gene expression. In this study, we investigated whether DNA structural information around the binding site of TFs can be used to predict the involvement of the binding site in the regulation of the expression of genes located downstream of the binding site. Specifically, we calculated the structural parameters based on the DNA shape around the DNA binding motif located upstream of the gene whose expression is directly regulated by one TF AoXlnR from Aspergillus oryzae, and showed that the presence or absence of expression regulation can be predicted from the sequence information with high accuracy ([Formula: see text]–1.0) by machine learning incorporating these parameters.
Topological Approaches in Characterization of Algebraic Structure of Fuzzy Multiset Finite Automata
Authors: Ruhela Shainky , Verma Sunny , Yadav Vijay Kumar , Tiwari S. P.
Published: June 2024

This paper aims to provide the topological approaches in the characterization of the algebraic structure of fuzzy multiset finite automaton (FMFA). We have shown how the topological concepts of open sets and continuous functions can be utilized to characterize the algebraic structure of FMFA. The topological definition of a continuous function on fuzzy multiset finite automata and its structure preserving qualities are investigated. The operation preserving function between two fuzzy multiset finite automata is introduced, such functions are analogous to a homomorphism between algebraic structures but have an even stronger structure preserving nature than the continuous functions.
A Study on AG-Groups in Spherical Fuzzy Environment
Authors: Preethi D. , Rajareega S.
Published: June 2024

An AG-group is an algebraic structure that satisfies the left invertive law and includes its left identity and inverse elements. This framework is naturally suited for representing and manipulating various real-life applications in civil engineering, information engineering, artificial intelligence, and more. In this paper, we present the structural application of AG-groups in data encryption and in the rotational transformation of water molecules. Additionally, numerous authors have explored fuzzy set theory over AG-group systems, yielding many valuable results. Spherical fuzzy set theory, an extension of fuzzy set theory, allows for the representation of uncertainty in decision-making, where there may be multiple possible choices or uncertainty about the degree of membership of an element in a set. However, no prior work has combined spherical fuzzy set theory with AG-groups, which motivates our study. In this paper, we apply spherical fuzzy set theory to AG-groups and introduce the concept of spherical fuzzy AG-subgroupoids. We provide the characterization of spherical fuzzy AG-subgroupoids over AG-groupoids and examine their related properties. As an application of spherical fuzzy sets over AG-groups, we develop the concept of normal spherical fuzzy groups over AG-groups and investigate their various properties.
Probabilistic Approach for Detection of High-Frequency Periodic Signals Using an Event Camera
Authors: Ben-Ezra David El-Chai , Arad Ron , Padowicz Ayelet , Tugendhaft Israel
Published: June 2024

Being inspired by the biological eye, event camera is a novel asynchronous technology that poses a paradigm shift in acquisition of visual information. This paradigm enables event cameras to capture pixel-size fast motions much more naturally compared to classical cameras.

In this paper, we present a new asynchronous event-driven algorithm for detection of high-frequency pixel-size periodic signals using an event camera. Development of such new algorithms to efficiently process the asynchronous information of event cameras is essential to utilize its special properties and potential, and being a main challenge in the research community.

It turns out that this algorithm, which was developed in order to satisfy the new paradigm, is related to an untreated theoretical problem in probability: Let [Formula: see text] originated from an unknown distribution. Let also [Formula: see text], and [Formula: see text]. What can be said about the probability [Formula: see text] of having more than [Formula: see text] adjacent [Formula: see text]-s pairs that the distance between them is [Formula: see text], up to an error [Formula: see text]? This problem, which reminds the area of order statistic, shows how the new visualization paradigm is also an opportunity to develop new areas and problems in mathematics.
Seismic Performance Assessment of Steel Buildings Equipped with a New Semi-active Displacement-Dependent Viscous Damper
Authors: Kiral Adnan , Garcia Reyes , Petkovski Mihail , Hajirasouliha Iman
Published: June 2024

This paper investigates numerically the seismic behavior of multi-degree-of-freedom (MDOF) systems with novel 2–4 direction and displacement-dependent (2–4DDD) and 2–4 Displacement-Velocity- (2–4DVD) Semi-Active (SA) controls. This study builds upon the novel SA 2–4DDD control system, in which the damper forces are controlled by inter-story drifts. For the first time, this paper investigates numerically the behavior of an MDOF system with 2–4DDD controls. A 3-story steel frame is modeled in OpenSees and then subjected to real earthquake records. The frame is modeled considering three control systems: (i) conventional passive nonlinear viscous dampers (NVDs), (ii) SA 2–4DDD dampers, and (iii) a new 2–4DVD SA damper. Parametric studies are conducted to determine the optimal parameters of 2–4DVD control in the designed frames. New design methodologies for MDOF systems with 2–4DVD and 2–4DDD controls are also proposed. The results are discussed in terms of inter-story drift, base shear force, acceleration, dissipated energy and required damper force. Results from Nonlinear Time History Analyses show that, compared to a frame with traditional NVDs, the inter-story drifts and base shear of the frame with 2–4DVD control are up to 72% and 32% lower, respectively. 2–4DVD control also reduces damping forces and acceleration by up to 60% and 87%, respectively, compared to 2–4DDD control. It is also shown that the 2–4DDD control was not stable in high-frequency earthquake records. Conversely, the new 2–4DVD control leads to smoother damping force changes between quadrants for the case study investigated in this paper. This study contributes toward the development of new seismic retrofitting dampers for nonlinear MDOF systems.
Topological four-manifolds with right-angled Artin fundamental groups: corrigendum
Authors: Hambleton Ian , Hildum Alyson
Published: June 2024

We correct the stability bound in our classification of closed, spin[Formula: see text], topological four-manifolds with fundamental group [Formula: see text] of cohomological dimension [Formula: see text] (up to [Formula: see text]-cobordism), after stabilization by connected sum with copies of [Formula: see text]. If [Formula: see text] is a right-angled Artin group whose defining graphs have no four-cliques, then the new stability bound is [Formula: see text]. The other results of the paper are not affected.
Hamiltonian fragmentation in dimension four with application to spectral estimators
Authors: Alizadeh Habib
Published: June 2024

We prove a new Hamiltonian extension and consequently a fragmentation result in dimension [Formula: see text] for the symplectic manifold [Formula: see text]. Polterovich and Shelukhin have recently constructed a family of functionals on the space of time-dependent Hamiltonian functions on [Formula: see text] for rational [Formula: see text], called Lagrangian spectral estimators. Using our fragmentation result we prove that the restriction of their functionals to the subdomain [Formula: see text] is a uniformly [Formula: see text]-continuous functional where [Formula: see text]. As an application of our results, we show that the complement of a Hofer ball in the group of compactly supported Hamiltonian diffeomorphisms of [Formula: see text] contains a [Formula: see text]-open subset. Finally, we show that the aforementioned group equipped with the Hofer distance admits an isometric embedding of an infinite-dimensional flat space for suitable parameters [Formula: see text] and [Formula: see text].
Functional Interfaces: Chemical Grafting of Starch onto Multiwalled Carbon Nanotubes for Biomedical Applications
Authors: Estévez-Martínez Yoxkin , Cuevas-Yañez Erick , Núñez-Pineda Alejandra , Chavira-Martínez Elizabeth , Huirache-Acuña Rafael , Castaño Victor M.
Published: June 2024

This study provides a detailed investigation into the chemical grafting of multiwalled carbon nanotubes (MWNTs) with starch at various concentrations and reaction temperatures. Utilizing Raman spectroscopy and Fourier-transform infrared spectroscopy (FTIR), we identified structural defects in the MWNTs and characterized the functional groups introduced by the grafting process. Differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) deepened our understanding of the interactions between starch and MWNTs, and quantified the polysaccharide content. Transmission electron microscopy (TEM) unveiled nanostructures arising from the interplay between MWNTs and starch molecules. Our findings highlight the potential of starch-grafted MWNTs for applications in nanotechnology and nanomedicine, positioning them as a promising material for targeted drug delivery and tissue engineering, aligning with Nano LIFE’s multidisciplinary goals in life sciences, nanosciences and nanomedicine.
An Ultra-Wideband Dual Polarization Antenna Array for the Detection and Localization of Bright Fast Radio Transients in the Milky Way
Authors: Gallardo D. , Finger R. , Solis F. , Monasterio D. , Jorquera S. , Pizarro J. , Riquelme J. , Curotto F. , Pizarro F. , Bronfman L.
Published: July 2024

Fast radio bursts (FRBs) are extraordinary astrophysical phenomena characterized by short radio pulses that last only a few milliseconds, yet their power can surpass that of 500 million suns. To date, most detected FRBs originate from beyond our galaxy. However, if an FRB were to originate within the Milky Way, it could be detected using small antennas. In this paper, we propose a compact and ad-hoc antenna array designed for the efficient detection and localization of FRBs within the Milky Way. The antenna operates within the 1200–1800[Formula: see text]MHz range and consists of three sub-arrays placed in an L-shape for source localization, occupying a total volume of [Formula: see text]. Each sub-array consists of 4 miniaturized, dual-polarized, half-space radiation antenna elements, forming a one-dimensional array that allows shaping the radiation pattern to match the form of the Milky Way without exhibiting grating lobes. A prototype was constructed and characterized to validate the design. The measured results exhibit good agreement with the simulations. In addition to having a custom elongated radiation pattern, the array has attractive merits, such as low reflections at the input ports, high radiation efficiency, and a distribution that inhibits the existence of phase ambiguities, thus facilitating source localization.
Neighbor-Enhanced Representation Learning for Link Prediction in Dynamic Heterogeneous Attributed Networks
Authors: Wei Xiangyu , Wang Wei , Zhang Chongsheng , Ding Weiping , Wang Bin , Qian Yaguan , Han Zhen , Su Chunhua
Published: July 2024

Dynamic link prediction aims to predict future connections among unconnected nodes in a network. It can be applied for friend recommendations, link completion, and other tasks. Network representation learning algorithms have demonstrated considerable effectiveness in various prediction tasks. However, most network representation learning algorithms are based on homogeneous networks and static networks for link prediction that do not consider rich semantic and dynamic information. Additionally, existing dynamic network representation learning methods neglect the neighborhood interaction structure of the node. In this work, we design a neighbor-enhanced dynamic heterogeneous attributed network embedding method (NeiDyHNE) for link prediction. In light of the impressive achievements of the heuristic methods, we learn the information of common neighbors and neighbors’ interaction in heterogeneous networks to preserve the neighbors proximity and common neighbors proximity. NeiDyHNE encodes the attributes and neighborhood structure of nodes as well as the evolutionary features of the dynamic network. More specifically, NeiDyHNE consists of the hierarchical structure attention module and the convolutional temporal attention module. The hierarchical structure attention module captures the rich features and semantic structure of nodes. The convolutional temporal attention module captures the evolutionary features of the network over time in dynamic heterogeneous networks. We evaluate our method and various baseline methods on the dynamic link prediction task. Experimental results demonstrate that our method is superior to baseline methods in terms of accuracy.
Toward a Theory of Lifespan Personality Trait Development
Authors: Bleidorn Wiebke
Published: July 2024

The lifespan development of personality traits has evolved from a niche topic to a core subject of psychological science. Looking back at 20 years of research, I review the personality development literature against three criteria for strong psychological theories. Overall, the field has come a long way toward refining our theoretical understanding of lifespan personality trait development. Major accomplishments include the establishment of evidence-based trait measures, the identification of robust patterns of trait stability and change, and the documentation of both environmental and genetic contributions to lifespan personality development. These insights put the field in a position to make transformative advances toward stronger and more precise theories. However, there are still several open questions. I discuss ideas to overcome existing obstacles to the development of strong lifespan personality theories and close with an overall evaluation of the theoretical status of the field.
Empagliflozin attenuates epithelial-to-mesenchymal transition through senescence in peritoneal dialysis
Authors: Lho Yunmee , Park Yeong , Do Jun Young , Kim A-Young , Park Yong-Eun , Kang Seok Hui
Published: July 2024

Epithelial-to-mesenchymal transition (EMT) is considered one of the senescence processes. Antisenescence therapies may effectively reduce EMT in peritoneal dialysis models. Human peritoneal mesothelial cells treated with glucose show an increase in senescence and EMT markers; however, empagliflozin attenuates these changes. Mice undergoing peritoneal dialysis exhibit increased senescence and EMT markers, which are decreased by empagliflozin. These findings suggest that empagliflozin may emerge as a novel strategy for prevention or treatment of peritoneal fibrosis.
BrainNet: Precision Brain Tumor Classification with Optimized EfficientNet Architecture
Authors: Islam Md Manowarul , Talukder Md. Alamin , Uddin Md Ashraf , Akhter Arnisha , Khalid Majdi
Published: June 2024

Brain tumors significantly impact human health due to their complexity and the challenges in early detection and treatment. Accurate diagnosis is crucial for effective intervention, but existing methods often suffer from limitations in accuracy and efficiency. To address these challenges, this study presents a novel deep learning (DL) approach utilizing the EfficientNet family for enhanced brain tumor classification and detection. Leveraging a comprehensive dataset of 3064 T1‐weighted CE MRI images, our methodology incorporates advanced preprocessing and augmentation techniques to optimize model performance. The experiments demonstrate that EfficientNetB(07) achieved 99.14%, 98.76%, 99.07%, 99.69%, 99.07%, 98.76%, 98.76%, and 99.07% accuracy, respectively. The pinnacle of our research is the EfficientNetB3 model, which demonstrated exceptional performance with an accuracy rate of 99.69%. This performance surpasses many existing state‐of‐the‐art (SOTA) techniques, underscoring the efficacy of our approach. The precision of our high‐accuracy DL model promises to improve diagnostic reliability and speed in clinical settings, facilitating earlier and more effective treatment strategies. Our findings suggest significant potential for improving patient outcomes in brain tumor diagnosis.
Mutual Coupling Reduction in a Switched Beamforming Multilayer Antenna Array System
Authors: Jebabli Emna , Hayouni Mohamed , Choubani Fethi
Published: June 2024

In this paper, we present a millimeter‐wave beamforming antenna array for the fifth generation (5G) of mobile networks and beyond. One of our priority objectives was to minimize the antenna array’s total physical size, by paying attention to avoid radiation performance degradation, such as bandwidth and efficiency. Another priority objective was to avoid mutual coupling (MC) between radiation elements and enhance the gain of the antenna to meet the requirements and challenges of the 5G. In these prospects, we have designed a 4 × 3 Chebyshev modified rectangular antenna array, engraved on the dielectric substrate of the top layer. The antenna array is powered across a 4 × 4 Butler matrix, engraved on the dielectric substrate of the bottom layer. The prototype overall size is 35.76 × 45.56 × 1.589 mm3. Hence, four switched main lobes pointed according to the angles ‐14°, +26°, ‐23° and +12°. The corresponded maximum gains at 28 GHz are 11.1, 10.5, 11, and 11.5 dB, respectively. Moreover, a reduction of the MC is ensured by using a CSRR metamaterial carved into the ground plane (GP) of the upper dielectric substrate layer. Experimental and simulation results concord well and show a multiband behavior at 26 GHz and in Ka‐band. The impedance bandwidths are 1.5%, 2.7%, and 2.43% at 26, 28, and 40 GHz, respectively. A low MC, between the antenna array’s elements, is also achieved, and the levels of the transmission coefficients vary between ‐11 dB and ‐68 dB.
Application of Multiobjective Optimization Based on Modified SPEA2 Method for Tuning FOPID plus Second‐Order Derivative Controller in Hydraulic Turbine Governing System
Authors: Tian Tian , Huang Qiang , Lv Jinhua , Zhou Mo , Tang Jian
Published: June 2024

The controller design and parameter tuning of the hydraulic turbine governing system are critical for ensuring stability and safety of operation. In this study, we propose a novel design of fractional‐order PID plus second‐order derivative (FOPID2D) controller design for the HTGS system. In addition, we develop a modified strength Pareto evolutionary algorithm II (MSPEA2) to optimize the design parameters with multiple objectives. By combining fractional calculus and second‐order derivative, the FOPID2D controller offers enhanced control flexibility compared to conventional PID controller. To achieve the Pareto‐front, we employ the proposed MSPEA2 method as an optimizer, which is further improved using a Uniform–Cauchy–Gaussian hybrid mutation strategy. We demonstrate its numerical quality and diversity superiority over the conventional method through test function results. The designed FOPID2D controller, along with PID, fractional‐order PID, and PID plus second‐order derivative controllers, is employed in the load disturbance experiments of the hydraulic turbine governing system. Consequently, the control effect of the proposed FOPID2D controller is validated by comparison with other controllers.
Risk Assessment for Complex Systems Based on Fuzzy Cognitive Maps: A Case of the Biopharmaceutical Industry
Authors: Abbasian Hadi , Yousefi-Zenouz Reza , Amirkhani Abdollah , Shirzadeh Masoud , Abdollahiasl Akbar , Nikfar Shekoufeh , Siahi-Shadabad Mohammadreza , Kebriaeezadeh Abbas
Published: June 2024

Analyzing the supply chain (SC) of biopharmaceutical drugs can be challenging due to their complexity, the existence of a wide variety of risks, and the dynamics of the system. This paper presents a framework for evaluating the SC risks of Iranian biopharmaceutical companies based on cause‐and‐effect relationships and fuzzy cognitive maps (FCMs). We first interviewed several biopharmaceutical supply experts to learn about potential SC risks, causal relationships among FCM concepts, FCM structure, and FCM activation cycle. The most critical and relevant risks and significant elements of the SCs, such as cost, time, and quality, were identified as relevant FCM concepts. Then, we used failure mode and effects analysis (FMEA) and the FCM of the SC risks to assess the impacts of the biopharmaceutical SC risks on each other and on the crucial elements of the SCs. The Hebbian learning algorithms were then applied to train the FCM models. We tested different scenarios to evaluate the impacts of FCM concepts on the SC risks. The proposed approach can prioritize risk factors and, more importantly, predict and analyze the effect of each risk factor/risk group on other risks or the outcome of a given risk. The proposed FCM features and the knowledge gained from evaluating them can provide practical and helpful information to pharmaceutical companies to deal with their supply risks more efficiently.
Supplementing the Diet of Hybrid Grouper (Epinephelus fuscoguttatus ♀ × E. lanceolatus ♂) with Compound Acidifier Is a Good Way to Alleviate Poor Intestinal Growth Caused by High Levels of Cottonseed Protein Concentrate
Authors: Zhang Jiacheng , Deng Hongjin , Liang Weixing , Chi Shuyan , Tan Beiping , Dong Xiaohui , Zhang Shuang
Published: June 2024

This study investigated the effect of adding the compound acidifiers on the intestine health of hybrid grouper (Epinephelus fuscoguttatus ♀ × E. lanceolatus ♂) fed diet with higher cottonseed protein concentrate (CPC). To assess the benefits of compound acidifiers helping CPC to replace more fish meal (FM) for hybrid grouper, five isonitrogen and isolipid experimental diets were formulated. The five diets consisted of a control diet (FM, 50%) and four experimental diets (27.5% FM, 27.27% CPC), each of which contained compound acidifiers to varying degrees (FCA0, FCA0.05, FCA0.1, and FCA0.2). Each diet was fed to three replicates of each group for 8 weeks. In the FCA0.05 group, the results demonstrated a statistically significant increase in protein efficiency ratio, lipid efficiency ratio, and the activity of digestive enzymes in the intestine (P < 0.05). In the FCA0.05 group, there was a clearly enhanced expression of anti‐inflammatory cytokines in the intestines (P < 0.05). In the FCA0.1 group, there may be an increase in the expression of important genes involved in fatty acid metabolism in the intestinal (P < 0.05). Appropriate compound acidifiers decreased the relative abundance of Vibrio and other harmful bacteria in the intestine flora that were brought by high CPC. In conclusion, when the hybrid grouper was given a diet containing more CPC, the FCA0.05 group was able to promote intestinal development, enhance digestive enzyme activity and feed consumption, raise antioxidant enzyme activity and anti‐inflammatory factor expression, and improve intestinal health.
Off‐Pump Coronary Artery Bypass Graft (OCABG) Surgery Outcome: AKI Incidence, Serum Uric Acid, and Cut‐Offs of Variables
Authors: Zare-Khormizi Mohamad Reza , Pourrajab Fatemeh
Published: July 2024

Purpose: One of the most important challenges of the medical community is to find out the success rate of coronary artery bypass surgery and control complications after surgery, including acute kidney injury (AKI). The present study was conducted with the aim of determining the predictive effect of serum uric acid (SUA) (UA) level in patients undergoing off‐pump coronary artery bypass (OCABG) surgery.

Methods: The present descriptive‐analytical study included 144 patients who underwent OCABG and met the inclusion criteria. SUA and related indicators, duration of hospitalization and stay in ICU, AKI and in‐hospital mortality, and 6‐month follow‐up mortality were investigated.

Results: Patients were divided into high and normal groups based on SUA levels. The prevalence of postoperative AKI was 20% and was significantly associated with the preoperative UA levels (OR: 2.04; CI: 95%; 1.03–4.20). The mortality rate of patients was between 2% and 9%, which increased to 13% in patients with high SUA (p value ~0.224). The average duration of ICU and hospitalization in patients with high UA was longer than the other group (p value ~0.06 and p value ~0.002, respectively).

Conclusion: SUA levels are independently associated with a higher risk of AKI and outcome complications after off‐pump CABG, and confounding factors at specific cutoffs affect the odds ratio of UA for AKI occurrence.