Miracle-dz/UniFAR-FTUs huggingface dataset:
A numerical algorithm for the optimal placement of actuators and sensors for flexible structures

The objective of this investigation is to present a methodology for obtaining the optimal location of actuators and sensors in systems which describe the dynamics of flexible structures. First an optimal state feedback gain, parametrized by the unknown actuator locations, is found by minimizing an appropriately chosen (control) performance index. Minimization of the optimal value of the quadratic cost is then performed with respect to (spatial) locations in order to obtain the optimal actuator location. The incorporation of partial measurements, which introduces the sensor location(s) into the control problem, achieves the sensor location in a similar fashion, namely by minimizing the optimal value of a dynamic compensator index with respect to locations. Numerical examples with simulation results are presented to support this investigation.
Employment of Self-Adaptive Bayesian Neural Network for Systematic Antenna Design: Improving Wireless Networks Functionalities

The performance of wireless networks is related to the optimized structure of the antenna. Therefore, in this paper, a Machine Learning (ML)-assisted new methodology named Self-Adaptive Bayesian Neural Network (SABNN) is proposed, aiming to optimize the antenna pattern for next-generation wireless networks. In addition, the statistical analysis for the presented SABNN is evaluated in this paper and compared with the current Gaussian Process (GP). The training cost and convergence speed are also discussed in this paper. In the final stage, the proposed model’s measured results are demonstrated, showing that the system has optimized outcomes with less calculation time.
Overexpression of the cotton trihelix transcription factor GhGT23 in Arabidopsis mediates salt and drought stress tolerance by binding to GT and MYB promoter elements in stress-related genes

Cotton (Gossypium hirsutum L.) is the world’s most economically valuable textile crop. However, cotton plants are often subjected to numerous abiotic stresses that can dramatically limit yield. Trihelix transcription factors (TTFs) play important roles in abiotic stress responses in many plant species, and efforts to better understand their roles in cotton abiotic stress responses are ongoing. In this study, a member of the cotton TTF family (GhGT23) was functionally characterized. This protein contains a SANT domain and is a member of the SIP subfamily of TTF proteins. GhGT23 was significantly (p < 0.05) and highly expressed in cotton fiber compared to relatively low expression in other tissues. A significant (p < 0.05) increase in GhGT23 expression occurred in cotton seedlings within 12 hours of drought, salt, and ABA exposure. The GhGT23 protein localized in the nucleus but exhibited no signs of transactivation activity. GhGT23 overexpression in Arabidopsis conferred enhanced drought and salt stress tolerance. The expression of stress-related genes was higher in transgenic Arabidopsis expressing GhGT23 than in wild-type plants subjected to salt stress. The results of electrophoretic mobility shift assay revealed that GhGT23 could bind to the GT cis-elements GT-1Box (Box II), GT2-Box, GT3-Box, GT-3a (Site1-type), GT-3b, and Box as well as the MYB cis-elements MBS1 and MRE4. Our results demonstrate that GhGT23 positively regulates salt and drought stress responses, possibly by enhancing the expression of stress-related genes.
Robust high-gain observer for nonlinear closed-loop stochastic systems

In this paper, the problem of robust state observation is tackled. A high-gain observer is employed to carry out the state estimation of a continuous time uncertain nonlinear system subject to external perturbations of stochastic nature. Unmodelled dynamics is assumed to be deterministic and belonging to an a priori known class of uncertainties.The control input is constructed based on the state estimates supplied by this observer. An upper bound for the estimation error and the states of this closed-loop system is derived. It is shown to be a linear combination of all a priori given uncertainty levels and turns out to be “tight” (reachable). The proposed scheme is applied to a robot manipulator with unknown friction and inaccessible angular velocities.
Research on Rumor Detection Based on a Graph Attention Network With Temporal Features

The higher-order and temporal characteristics of tweet sequences are often ignored in the field of rumor detection. In this paper, a new rumor detection method (T-BiGAT) is proposed to capture the temporal features between tweets by combining a graph attention network (GAT) and gated recurrent neural network (GRU). First, timestamps are calculated for each tweet within the same event. On the premise of the same timestamp, two different propagation subgraphs are constructed according to the response relationship between tweets. Then, GRU is used to capture intralayer dependencies between sibling nodes in the subtree; global features of each subtree are extracted using an improved GAT. Furthermore, GRU is reused to capture the temporal dependencies of individual subgraphs at different timestamps. Finally, weights are assigned to the global feature vectors of different timestamp subtrees for aggregation, and a mapping function is used to classify the aggregated vectors.
Negatively refracting chiral metamaterials: a review

Chirality extends the class of negatively refracting metamaterials by endowing a richer palette of electromagnetic properties. Chiral metamaterials can support negative refraction, which must be assessed in light of the closely related phenomenons of negative phase velocity and counterposition. Two categories of chiral metamaterials are being examined these days: (a) homogeneous and homogenizable chiral materials, as exemplified by isotropic chiral materials, Faraday chiral materials, and materials with simultaneous mirror-conjugated and racemic chirality characteristics; and (b) structurally chiral materials, as exemplified by helicoidal bianisotropic materials and ambichiral materials. The planewave response of a half-space occupied by a chiral metamaterial is complex, and important distinctions between negative refraction, negative phase velocity, and counterposition emerge.
Ventricular Conduction System Modeling for Electrophysiological Simulation of the Porcine Heart

Depolarization sequences triggering mechanical contraction of the heart are largely determined by the cardiac conduction system $(CS)$. Many biophysical models of cardiac electrophysiology still have poor representations of the $CS$. This work proposes a semiautomatic method for the generation of an anatomically-realistic porcine $CS$ that reproduces ventricular activation properties in swine computational models. Personalized swine biventricular models were built from magnetic resonance images. Electrical propagation was described by the monodomain model. The $CS$ was defined from manually-determined anatomic landmarks using geodesic paths and a fractal tree algorithm. Two $CS$ distributions were defined, one restricted to the subendocardium and another one by performing a subendo-to-intramyocardium projection based on histological porcine data. Depolarization patterns as well as left ventricular transmural and inter-ventricular delays were assessed to describe ventricular activation by the two $CS$ distributions. The electrical excitations calculated using the two $CS$ distributions were in good agreement with reported activation patterns. The pig-specific subendo-intramyocardial $CS$ led to improved reproduction of experimental activation delays in ventricular endocardium and epicardium.
Holding open spaces to explore beyond: Toward a different conceptualization of specialization in high-performance sport

This conceptual analysis aims to challenge the state of high-performance sport by questioning the concept of specialization. To start, we offer a brief, but critical overview of what specialization currently entails. Then, shifting the paradigm, we suggest an expansion rather than a reduction of developmental possibilities once an athlete reaches the “top”. Specifically, rather than athletes conforming to national standards imposed by governing bodies about what it means to be “elite”, we suggest sport systems consider a person-environment fit approach to support ongoing development. Drawing on an ecological dynamics rationale and various socio-cultural theories, we explore how concepts such as affordances and perspectives can be harnessed to create a better “fit” between athletes’ action capabilities and the opportunities within their broader environment. Our conception of specialization requires moving away from a definition of success based on the accumulation of medals, toward one that accounts for the exploration and achievement of the possible. We argue that a person-environment fit welcomes diversity, so long as it sustains the person’s health, wellbeing, and performance. This, it is suggested, is about collectively holding open spaces for each other to explore beyond the constraints of high-performance sport, encouraging all to carry on their lives in directions meaningfully impactful for them. We conclude this conceptual analysis with a brief case example demonstrating what our theorizing could look like in practice.
Enhanced external counterpulsation improves dysfunction of forearm muscle caused by radial artery occlusion

Objective This study aimed to investigate the therapeutic effect of enhanced external counterpulsation (EECP) on radial artery occlusion (RAO) through the oscillatory shear (OS) and pulsatile shear (PS) models of human umbilical vein endothelial cells (HUVECs) and RAO dog models. Methods We used high-throughput sequencing data GSE92506 in GEO database to conduct time-series analysis of functional molecules on OS intervened HUVECs, and then compared the different molecules and their functions between PS and OS. Additionally, we studied the effect of EECP on the radial artery hemodynamics in Labrador dogs through multi-channel physiological monitor. Finally, we studied the therapeutic effect of EECP on RAO at the histological level through Hematoxylin–Eosin staining, Masson staining, ATPase staining and immunofluorescence in nine Labrador dogs. Results With the extension of OS intervention, the cell cycle decreased, blood vessel endothelial cell proliferation and angiogenesis responses of HUVECs were down-regulated. By contrast, the inflammation and oxidative stress responses and the related pathways of anaerobic metabolism of HUVECs were up-regulated. Additionally, we found that compared with OS, PS can significantly up-regulate muscle synthesis, angiogenesis, and NO production related molecules. Meanwhile, PS can significantly down-regulate inflammation and oxidative stress related molecules. The invasive arterial pressure monitoring showed that 30Kpa EECP treatment could significantly increase the radial artery peak pressure (p = 0.030, 95%CI, 7.236–82.524). Masson staining showed that RAO significantly increased muscle interstitial fibrosis (p = 0.002, 95%CI, 0.748–2.128), and EECP treatment can reduce this change (p = 0.011, 95%CI, −1.676 to −0.296). ATPase staining showed that RAO significantly increased the area of type II muscle fibers (p = 0.004, 95%CI, 7.181–25.326), and EECP treatment could reduce this change (p = 0.001, 95%CI, −29.213 to −11.069). In addition, immunofluorescence showed that EECP increased angiogenesis in muscle tissue (p = 0.035, 95%CI, 0.024–0.528). Conclusion EECP improves interstitial fibrosis and hypoxia, and increases angiogenesis of muscle tissue around radial artery induced by RAO.
Developing a maturity model to identify digital skills and abilities of accounting professionals: evidence from Turkey

The digital transformation process has led to the spread of new and advanced technologies in business environments. This situation has affected the accounting profession as well as many professions and has created new opportunities and risks. The biggest risk that arises is that accounting professionals must have up-to-date digital skills to stay relevant in the field. Determining the current digital skills of accounting professionals is important to meet this requirement and constitutes the source of motivation for the study. Objectives: The aim of this study is to investigate the level of digital abilities and skills that will enable accounting professionals to use current and advanced technologies developed as a result of digital transformation. Methods/Approach: This study used a survey method to collected data from 279 professional accountants working in Turkey’s leading industrial companies. The collected data was analyzed to develop a maturity model for digital skills and abilities. Results: According to the findings of the study, professional accountants have a high level of maturity in the technologies they use. However, there is a lack of talent and skill in emerging and evolving technologies that are not currently widely used in the workplace. This study benefits accounting educators, those with accounting career goals, and the development of digital skills and abilities in accounting professionals.
The non-Gaussian statistics of the velocity field in low-resolution large-eddy simulations of homogeneous turbulence

A low-resolution (643) large-eddy model of forced homogeneous turbulence is numerically simulated using Kraichnan's eddy viscosity. The introduction of a reliable statistical estimate of the ζp exponents allows one to perform a detailed statistical analysis of the velocity field and shows that the probability distribution functions, the structure functions and the power-law exponents ζp agree with previous numerical and experimental results obtained at much higher effective resolution. This result shows how a simple modelling of the energy transfer produces self-similar dynamics extending to the small scales and obtains the right statistical properties of the velocity field.
Inclinations of Circumbinary Planets: Assembly of Protoplanetary Discs and Secular Binary-Disc Interaction

Abstract The Kepler satellite has discovered a number of transiting planets around close binary stars. These circumbinary systems have highly aligned planetary and binary orbits. In this paper, we explore how the mutual inclination between the planetary and binary orbits may reflect the physical conditions of the assembly of protoplanetary discs and the interaction between protostellar binaries and circumbinary discs. Given the turbulent nature of star-forming molecular clouds, it is possible that the infalling gas onto the outer region of a circumbinary disc rotates around a different axis compared to the central protostellar binary. Thus, the newly assembled circumbinary disc can be misaligned with respect to the binary. However, the gravitational torque from the binary produces warp and twist in the disc, and the back-reaction torque tends to align the disc and the binary orbital plane. We present a new, analytic calculation of this alignment torque, and show that the binary-disc inclination angle can be reduced appreciably after the binary accretes a few percent of its mass from the disc. Since mass accretion onto the proto-binary is very likely to occur, our calculation suggests that in the absence of other disturbances, circumbinary discs and planets around close (sub-AU) stellar binaries are highly aligned with the binary orbits, while discs and planets around wide binaries can be misaligned.
On photon trajectories and electromagnetics near strongly gravitating cosmic sources

We see and understand the Universe around us through the medium of the electromagnetic spectrum, ranging from the low-frequency radio waves extending up to the high-frequency γ-rays. These electromagnetic waves, generated by different processes within or nearby the various astronomical bodies get modified in their transit through the vast distances of spacetime and its contents that make up the Universe. Depending upon the various physical features of the media they are transiting through, characteristics such as dispersion, polarization and frequency modulation can occur by the intervening forces and fields. While electric and magnetic fields could be strong sources of influence, the weaker force gravity also can be a modifying factor both in the generation and propagation of the electromagnetic waves from distant cosmos. In fact, it is well known that the influence of gravity on light, making it bend while passing near Sun, was the predicted and observed experimental fact that confirmed Einstein’s theory of general relativity as the most successful theory of the twentieth century. It is well known that the passage of electromagnetic waves through plasma leads to several changes in the dispersed waves, a systematic study of which could give information about the characteristics of the medium through which they arrived. Over the past century, several detailed studies have been carried out to analyse the structure and properties of electromagnetic fields of cosmic objects and their behaviour in the presence of gravitational fields. We give a brief review of the subject, starting with the gravitational bending of light and its consequences, viz., gravitational lensing and then consider the influence of gravity on the electromagnetic fields close to compact objects and the behaviour of charged particles in such electromagnetic fields. The changes in their trajectories, that occur because of the curved geometry, can have direct influence on the electromagnetic and plasma processes near bodies like neutron stars and black holes. Further, introduction of a possible non-minimal coupling of electromagnetism and gravity seems to be a possible source for the generation of the cosmic primordial magnetic field, a precursor to the presently observed magnetic field in the Universe.
SSViT-HCD: A Spatial–Spectral Convolutional Vision Transformer for Hyperspectral Change Detection

In recent decades, the wide use of deep-learning-based methods has consistently improved the performance of remote sensing images and is widely used for hyperspectral change detection (HCD) tasks. However, most of the existing HCD method is based on the convolutional neural network (CNN), which shows limitations in long-range dependencies and also cannot mine sequence features well. The change detection (CD) performance still has margins for improvement. In this study, inspired by the excellent performance of transformers in computer vision, which has shown a significant ability to model global dependencies to attenuate the loss of long-range information, we built a hybrid spatial–spectral convolutional vision transformer (SSViT) for HCD. Our proposed method combines the merits of CNN and transformer to fulfill effective and efficient HCD. This study focused on highly reliable pseudo sample data generation by a selection scenario. To generate a pseudo sample, we have used different methods: 1) predicting change and no-change areas by using Euclidean distance; 2) thresholding by the Chan–Vese segmentation method for determining change and no-change pixels for intensity maps; 3) sorting of change and no-change pixels; and 4) selection of the minimum value of initial no-change pixels as pseudo change sample data, in addition to choosing the maximum intensity value for change candidate pixels as change sample data. The highly reliable change pixels were selected, and then, pseudo training data were used to train the SSViT model. At last, the change map is generated by training the SSViT network based on pseudo training data. The performance of the SSViT model is evaluated for real-world hyperspectral (HS) datasets with different change land cover types. Furthermore, a new series of HS images is introduced for CD purposes. The results of CD show that the HS images have a high potential for detecting subtle changes. The experimental results demonstrate that the proposed SSViT could outperform the advanced HCD methods.
The Sensitivity of the Rate of Transient Climate Change to Ocean Physics Perturbations

Abstract “Perturbed physics” ensembles of Hadley Centre climate models have recently been used to quantify uncertainties in atmospheric and surface climate feedbacks under enhanced levels of CO2, and to produce probabilistic estimates of the magnitude of equilibrium climate change. The rate of time-dependent climate change is determined both by the strength of atmosphere–surface climate feedbacks and by the strength of processes that remove heat from the surface to the deep ocean. Here a first small ensemble of coupled atmosphere–ocean climate model experiments in which the parameters that control three key ocean physical processes are perturbed is described. It is found that the perturbations have little impact on the rate of ocean heat uptake, and thus have little impact on the time-dependent rate of global warming. Under the idealized scenario of 1% yr−1 compounded CO2 increase, the spread in the transient climate response is of the order of a few tenths of a degree, in contrast to the spread of order .
Autonomous exploration and mapping of unknown environments

Autonomous exploration and mapping is a vital capability for future robotic systems expected to function in arbitrary complex environments. In this paper, we describe an end-to-end robotic solution for remotely mapping buildings. For a typical mapping system, an unmanned system is directed to enter an unknown building at a distance, sense the internal structure, and, barring additional tasks, while in situ, create a 2-D map of the building. This map provides a useful and intuitive representation of the environment for the remote operator. We have integrated a robust mapping and exploration system utilizing laser range scanners and RGB-D cameras, and we demonstrate an exploration and metacognition algorithm on a robotic platform. The algorithm allows the robot to safely navigate the building, explore the interior, report significant features to the operator, and generate a consistent map - all while maintaining localization.
Spectral form and source term balance of short gravity wind waves

We investigated the spectral structure and source term balance of short gravity waves, based on in situ observations of wave number spectra retrieved by air-sea interaction spar (ASIS) buoys. The behaviors of wave number spectra up to 10 rad/m (the gravity wave regime) were analyzed for a wide range of wind and wave conditions. The observed wave number spectra showed the spectral power laws described by Toba (1973) and Phillips (1958) in addition to the characteristic nodal point at ∼10 rad/m where spectral energy becomes constant over the entire wind speed range. We also improved the third-generation wave model using the nonlinear dissipation term. The wave model reproduced the spectral form in the higher wave number domain. In the equilibrium range, nonlinear transfer played a major role in maintaining equilibrium conditions. On the other hand, in the saturation range, which starts at the upper limit of the equilibrium range, the nonlinear transfer tended to be out of balance with other source terms, and the dissipation term was in balance with wind input.
Macroscopic electric fields driven by lower-hybrid turbulence and acceleration of thermal electrons in the foot of quasi-perpendicular shocks

A new mechanism is suggested that draws non-resonant thermal electrons into a higher-velocity range, where they can be effectively accelerated by waves. We argue that the acceleration of a small number of pre-existing resonant particles influences the dynamics of the bulk plasma and results in a macroscopic electric field. The solution for the spatial dependence of this electric field is obtained, and it appears to be a new type of electrostatic shock, which forms only in the presence of background turbulence. This field enriches the region of resonant particles with thermal electrons, which leads to a build-up of an excess of accelerated particles. The number of accelerated particles is calculated. This mechanism appears as a good candidate to explain electron acceleration in the foot of quasi-perpendicular shocks.