Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of land surface temperature by comparing FY-3C/VIRR with Terra/MODIS and MSG/SEVIRI data

ABSTRACT Land surface temperature (LST) is a key parameter in the physics of land surface processes on a regional and global scale, as it combines the results of all surface–atmospheric interactions and energy fluxes between the atmosphere and the ground. Due to discrepancies in retrieval methods, input parameters, and sensor characteristics, various LST products are different from each other. As one of the important LST contributors, the operational LST product from the visible and infrared radiometer (VIRR) onboard Feng Yun 3C satellite (denoted as VIRR LST1) has not been comprehensively assessed, and the detailed LST retrieval accuracy is still unknown to the public. Taking this into consideration, a new group of VIRR LST (denoted as VIRR LST2) was derived using a generalized split-window method for operational use. Therefore, this study aimed to evaluate the consistency between VIRR LST1 and VIRR LST2 in detail using the LSTs derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Spinning Enhanced Visible and Infrared Imager (SEVIRI) data over the study area (from 11° W to 2° E and 32° N to 44° N). Several LST images in different seasons were used and registered in space, viewing time, and viewing geometry. After that, the LST differences in day-variation, land-cover types, and viewing zenith angles (VZAs) were also investigated. The results indicate that the differences between VIRR LST1 (or VIRR LST2) and MODIS LST were within 2.80 K, and the corresponding values between VIRR LST1 (or VIRR LST2) and SEVIRI LST were within 3.30 K. The VIRR LST1 was always underestimated, and VIRR LST2 was overestimated during the exuberant vegetation day. Furthermore, the mean differences between VIRR LST1 (or VIRR LST2) and MODIS LST for bare soil were larger than those for vegetation since the land surface emissivity for bare soil was often not well produced. On the other hand, the variation was not pronounced when comparing VIRR LST1 (or VIRR LST2) and SEVIRI LST, which could be caused by many more mixed pixels in the SEVIRI data set. In addition, the LST differences seemed to VZA dependent.
Remote state preparation through hyperentangled atomic states

Hyperentangled states have enhanced channel capacity in quantum processing and have yielded` evident increased communication speed in quantum informatics as a consequence of excessively high information content coded over each quantum entity. In the present article, we intend to demonstrate this fact by utilizing atomic states simultaneously entangled both in internal as well as external degrees of freedom, i.e. the de Broglie motion for remote state preparation (RSP). The results clearly demonstrate that we can efficiently communicate two bit information while manipulating only a single quantum subsystem. The states are prepared and manipulated using atomic Bragg diffraction as well as Ramsey interferometry, both of which are now considered as standard, state of the art tools based on cavity quantum electrodynamics. Since atomic Bragg diffraction is a large interaction time regime and produces spatially well separated, decoherence resistant outputs, the schematics presented here for the RSP offer important perspectives on efficient detection as well as unambiguous information coding and readout. The article summarizes the experimental feasibility of the proposal, culminating with a brief discussion.
The skewing effect of outcome evidence

Behaviours are primarily regulated to reduce the risks of a negative outcome to others. This article discusses the use of outcomes as evidence of violations of a legal standard (outcome evidence). The current debate over outcome evidence centres around limited rationality. Opponents argue that factfinders’ estimations are distorted by hindsight bias, while supporters argue that factfinders properly update the probability of fault, given information about the outcome. The article adopts the rationality assumptions and argues that factfinders should nevertheless disregard outcome evidence in most cases unless the outcome can provide evidence that works for or against the defendant or when the law creates inefficient incentives to comply with the legal standard, then using adverse outcomes as evidence may help solve the problem of undercompliance. The article further shows that when evidence cannot be excluded, changes to the law governing primary behaviour are warranted to account for the distortionary effect of outcome evidence.
Fixed‐time stabilization of uncertain strict‐feedback nonlinear systems via a bi‐limit–like strategy

This paper concerns the fixed‐time stabilization problem for uncertain strict‐feedback nonlinear systems. Generally, the so‐called fixed‐time stabilization is an extended concept of global finite‐time stabilization. By using fixed‐time controller, the convergence time of the closed‐loop system can be pre‐set by adjusting design parameters, which has more practical application values. The idea of bi‐limit homogeneity has been introduced to design the fixed‐time controller with two terms, whose orders are tuning by a bi‐limit–like strategy. That is the orders of the two terms are less than 1 and more than 1, respectively. Meanwhile, by utilizing power integral terms in the controller, the problem arising from the growth rates of uncertain nonlinear functions can also be solved. Based on appropriate Lyapunov function and backstepping technology, the parameters of the controller are finally determined, and the developed controller ensures the stabilization of system within a fixed time. Stability analysis and simulation results are respectively given to verify the effectiveness of the proposed method.
Effects of Forest Fragmentation on Connectivity and Genetic Diversity in an Endemic and an Invasive Rodent in Northwestern Madagascar

Habitat loss and fragmentation are of concern to conservation biologists worldwide. However, not all organisms are affected equally by these processes; thus, it is important to study the effects of living in fragmented habitats on species that differ in lifestyle and habitat requirements. In this study, we examined the dispersal and connectivity patterns of rodents, one endemic (Eliurus myoxinus) and one invasive (Rattus rattus), in two landscapes containing forest fragments and adjacent continuous forest patches in northwestern Madagascar. We generated genetic (RADseq) data for 66 E. myoxinus and 81 R. rattus individuals to evaluate differences in genetic diversity as well as inbreeding and connectivity in two landscapes. We found higher levels of inbreeding and lower levels of genetic diversity in E. myoxinus compared with R. rattus. We observed related dyads both within and between habitat patches and positive spatial autocorrelation at lower distance classes for both species, with a stronger pattern of spatial autocorrelation in R. rattus. Across each site, we identified contrasting migration rates for each species, but these did not correspond to habitat–matrix dichotomies. The relatively low genetic diversity in the endemic E. myoxinus suggests ecological constraints that require further investigation.
An Optical 1×4 Power Splitter Based on Silicon–Nitride MMI Using Strip Waveguide Structures

This paper presents a new design for a 1 × 4 optical power splitter using multimode interference (MMI) coupler in silicon nitride (Si3N4) strip waveguide structures. The main functionality of the proposed design is to use Si3N4 for dealing with the back reflection (BR) effect that usually happens in silicon (Si) MMI devices due to the self-imaging effect and the higher index contrast between Si and silicon dioxide (SiO2). The optimal device parameters were determined through numerical optimizations using the beam propagation method (BPM) and finite difference time domain (FDTD). Results demonstrate that the power splitter with a length of 34.6 μm can reach equal distribution power in each output port up to 24.3% of the total power across the O-band spectrum with 0.13 dB insertion loss and good tolerance MMI coupler parameters with a shift of ±250 nm. Additionally, the back reflection range over the O-band was found to be 40.25–42.44 dB. This demonstrates the effectiveness of the incorporation using Si3N4 MMI and adiabatic input and output tapers in mitigating unwanted BR to ensure that a good signal is received from the laser. This design showcases the significant potential for data-center networks, offering a promising solution for efficient signal distribution and facilitating high-performance and reliable optical signal routing within the O-band range. By leveraging the advantages of Si3N4 and the MMI coupler, this design opens possibilities for advanced optical network architectures and enables efficient transmission of optical signals in the O-band range.
Detecting text in natural scenes with multi-level MSER and SWT

The detection of the characters in the natural scene is susceptible to factors such as complex background, variable viewing angle and diverse forms of language, which leads to poor detection results. Aiming at these problems, a new text detection method was proposed, which consisted of two main stages, candidate region extraction and text region detection. At first stage, the method used multiple scale transformations of original image and multiple thresholds of maximally stable extremal regions (MSER) to detect the text regions which could detect character regions comprehensively. At second stage, obtained SWT maps by using the stroke width transform (SWT) algorithm to compute the candidate regions, then using cascaded classifiers to propose non-text regions. The proposed method was evaluated on the standard benchmark datasets of ICDAR2011 and the datasets that we made our own data sets. The experiment results showed that the proposed method have greatly improved that compared to other text detection methods.
Vaccine Hesitancy in College Students

(1) Background: Following the COVID-19 pandemic, vaccine hesitancy has become an increasingly important topic and has created significant concerns in public health. It is important to explore vaccine hesitancy among college students as they have been identified to be a high-risk group for COVID-19 transmission. This study aims to investigate COVID-19 vaccine hesitancy in college students on a midsized midwestern university campus. (2) Methods: Data were collected from 311 undergraduate and graduate college students during June and July 2021. Participants completed a survey on COVID-19 vaccine behaviors, perceptions, and opinions. Quantitative and qualitative analysis was performed to identify vaccine hesitancy and influencing factors in the student population. (3) Results: The results of this study demonstrated significant relationships between older and younger undergraduate students (OR > 1, p < 0.05), students who received a yearly influenza vaccine and those that did not (p < 0.05), and students who had a previous COVID-19 infection and those that did not (OR > 1, p < 0.05). We also determined a significant difference between some racial/ethnic groups and vaccine hesitancy status. (4) Conclusions: COVID-19 vaccine hesitancy exists on college campuses, and is influenced by age and student status, influenza vaccination status, previous COVID-19 infection, and race/ethnicity.
Crowd Simulation Model Integrating "Physiology-Psychology-Physics" Factors

Crowd simulation is a daunting task due to the lack of a comprehensive analysis of crowd movement. In this paper, we present a novel unified model for crowd simulation involving human physiological, psychological, and physical factors. We reveal the inherent relationship between these factors ignored by previous methods: in terms of physiology, we present a method for the computation of human physical strength based on doing work in physics; in terms of psychology, inspired by the James-Lange theory in biological psychology, the relationship between physical strength and emotion is delineated and the traditional SIR (Susceptible-Infectious-Recovered) model is improved; in terms of physics, we propose a method combing the physical strength and emotion together to determine individual movement, considering the fact that physical strength and human emotion always work together to affect individual movement. Physiological, psychological, and physical factors are integrated into the comprehensive model, and the relationship among every part is determined. The proposed model has been verified by simulation experiments. The simulation results show that the proposed method can simulate group behavior that conforms to real-world scenarios. It can reliably predict the physical strength and emotion of a crowd in an emergency.
Effectiveness of Using RFHDS Connected PIP System for Subsea Pipeline Vibration Control

Pipe-in-pipe (PIP) system can be considered as a structure-tuned mass damper (TMD) system by replacing the hard centralizers by the softer springs and dashpots to connect the inner and outer pipes. With properly designed connecting devices, PIP system therefore has the potential to mitigate the subsea pipeline vibrations induced by various sources, such as earthquake or vortex shedding. This study proposes using rotational friction hinge dampers with springs (RFHDSs) to connect the inner and outer pipes. The rotational friction hinge dampers (RFHDs) are used to absorb the energy induced by the external vibration sources and the springs are used to provide the stiffness to the TMD system and to restore the original locations of the inner and outer pipes. To investigate the effectiveness of this new design concept, detailed three-dimensional (3D) finite element (FE) model of the RFHD is developed in ANSYS and the hysteretic behavior of RFHD is firstly studied. The calculated hysteretic loop is then applied to the 3D PIP FE model to estimate the seismic responses. The effectiveness of the proposed system to mitigate seismic induced vibrations is examined by comparing the seismic responses of the proposed system with the conventional PIP system. The influences of various parameters, such as the preload on the bolt, the friction coefficient and the spring stiffness, on the RFHD hysteresis behavior and on the seismic responses of PIP system are investigated and some suggestions on the RFHDS design are made.
Factors associated with dementia attitudes in an adolescent cohort: structural equation modelling

Dementia related stigma is a key barrier to people living well with dementia. The global action plan on the public health response to dementia outlines the need to tackle the stigma towards dementia among the general population (WHO, 2017). Adolescents represent an under researched group among the general population but may already have experience of dementia and will become future carers or healthcare workers. Adolescents are ideal targets for anti‐stigma initiatives since the adolescence period has a key role in attitude formation. Understanding the factors involved in dementia attitude formation is useful when developing anti‐stigma initiatives. This study aims to identify predictors of dementia attitudes in adolescents.
Substrate size selection of microstrip‐fed cylindrical dielectric resonator antennas for lowering the cross‐polarisation

A cylindrical dielectric resonator antenna (DRA) has been excited with a microstrip line in the HEM 11δ mode. It is demonstrated that at the operating frequency, minimum cross-polarisation occurs when the lateral dimension of the substrate is slightly higher than half a free-space wavelength ( λ 0 ). This occurs when direct waves from the DRA interfere appropriately with the waves that are diffracted from the substrate edges. For a 50Ω microstrip-fed cylindrical DRA, numerical prediction suggests a substrate of lateral dimension 0.58 λ 0 for the lowest possible cross-polarisation. In addition, the above optimum substrate size is constant irrespective of the substrate shape (square or circle) or dielectric resonator (DR) properties (permittivity and aspect ratio) for a given substrate permittivity. Numerical results are experimentally verified for a DRA with permittivity 24 and aspect ratio 1.33, for both square and circular substrates at the respective operating frequencies.
A novel electrical muscle stimulation device for neurorehabilitation applications with adaptable parameter optimization using AI algorithms

The application of short trains of electric pulses, of appropriate frequency and power, to muscle or nerve tissue can induce action potentials which in turn lead to muscle contractions. Timing these action potentials appropriately can help enhance functional movements, a methodology called Functional Electrical Stimulation (FES). The motor and sensory recruitment of muscle and nerves by means of FES has been demonstrated to elicit short- and long-term neurophysiological changes in the central nervous system and thus constitutes a powerful therapeutic rehabilitation tool. The most significant signal parameters affecting the quality of muscle contraction and duration of cortical reorganization caused by Functional Electrical Stimulation Therapy (FEST) are pulse intensity (amplitude), frequency, pulse width and the time delay between pulses. While these parameters are particular to the stimulating signal waveform, there are other key factors at play which determine both the duration and quality of changes. Such factors are electrode placement and synchronization of voluntary command with the induced contraction, which partially determine the successful completion of a movement task. The work presented in this paper aims to study, calibrate, automate and optimize the adaptation process of the aforementioned FEST parameters with respect to induced muscle contraction intensity and perceived discomfort reported by the subject, using both conventional AI and machine learning methodologies.
Numerical Study of Bubble Coalescence Heat Transfer During Nucleate Pool Boiling

ABSTRACT Bubble growth during nucleate boiling in a large pool of liquid was modeled by numerically solving the unsteady Navier–Stokes laminar flow equations with the energy equation to predict the vapor and liquid flow fields. The analysis assumed two-phase, transient, three-dimensional, laminar flow with the Boussinesq approximation for the buoyancy. The volume of fluid method was used with the level set method to predict the bubble interface motion. The numerical investigations studied the dynamics and heat transfer rates associated with the coalescence of bubbles generated on two microheaters. The results for various wall superheats and liquid subcoolings illustrate the bubble growth and interaction dynamics throughout the coalescence process and the wall heat fluxes associated with the bubble nucleation and coalescence. In some cases, the bubble coalescence traps an evaporating liquid layer between the bubbles that then quickly evaporates, resulting in high heat fluxes. In other cases, the bubbles very quickly coalescence while the bubbles are still in the fast inertial controlled growth regime and the liquid layer between the bubbles is pushed out without evaporating, resulting in low heat fluxes as the surfaces are covered with vapor. These results show how similar conditions can lead to very different heat fluxes during coalescence as has been seen experimentally.
Generalized cubature quadrature Kalman filters: derivations and extensions

A new Gaussian approximation nonlinear filter called generalized cubature quadrature Kalman filter (GCQKF) is introduced for nonlinear dynamic systems. Based on standard GCQKF, two extensions are developed, namely square root generalized cubature quadrature Kalman filter (SR-GCQKF) and iterated generalized cubature quadrature Kalman filter (I-GCQKF). In SR-GCQKF, the QR decomposition is exploited to alter the Cholesky decomposition and both predicted and filtered error covariances have been propagated in square root format to make sure the numerical stability. In I-GCQKF, the measurement update step is executed iteratively to make full use of the latest measurement and a new terminal criterion is adopted to guarantee the increase of likelihood. Detailed numerical experiments demonstrate the superior performance on both tracking stability and estimation accuracy of I-GCQKF and SR-GCQKF compared with GCQKF.
Distributed Adaptive Output Feedback Leader-Following Consensus Control for Nonlinear Multiagent Systems

This paper investigates the problem of the distributed adaptive output feedback leader-following consensus control for a class of high-order nonlinear multiagent systems with unknown parameters and nonlinear terms. First, the reduced order dynamic gain ${k}$ -filters are built to estimate the unmeasured state variables. The bounds of the unknown parameters are estimated in order to avoid the over-estimation problem. Then, the dynamic surface control technique is used to design the distributed controller, and the computation load of the system is greatly reduced. Finally, a numerical example is shown to verify the effectiveness of the designed controller.
Acquisition and Processing Techniques for Image-Based Prospective Motion Correction in Magnetic Resonance Imaging

The sensitivity to subject motion is one of the major reasons of image quality degradation in magnetic resonance imaging (MRI). Subjects need to be very calm to maintain the relationship between spatial image information and subject anatomy throughout the scan. In case of moving subjects, prospective motion correction can regain this relationship by constantly adapting the image slice positioning to follow the subject in real time. This requires continuous estimates of the current motion state, which is complicated for a variety of MRI applications. In diffusion-weighted imaging, the calculation of accurate motion estimates is difficult due to the strong contrast variation between consecutive image volumes. This thesis proposes to exploit the rotational invariance of the trace of the diffusion tensor to reduce the contrast variation during image acquisition. The approach yields accurate motion estimates when compared to a gold standard with a correlation coefficient of R = 0.9634 for voxel displacements determined across all measurements of the underlying imaging study. Using the motion detection technique for real-time prospective motion correction substantially reduces the level of residual motion between image volumes to under ± 0.2 mm and ± 0.2°, leading to high-quality diffusion parameter maps. In contrast to MRI sequences in which successive image volumes are acquired, high-resolution anatomical imaging itself does not provide sufficient image data for prospective motion correction. This work suggests utilizing echo planar imaging (EPI) navigator slices, which are interleaved with the primary sequence acquisition, to perform a multislice-to-volumebased prospective motion correction. A dedicated slice iteration scheme minimizes the disruption to the magnetization of the primary pulse sequence, which can arise when acquiring additional navigator scans. The technique provides high temporal resolution and is evaluated in conventional spin echo as well as RARE pulse sequences. Human study data show residual motion parameters within ± 0.5 mm and ± 0.5° despite strong, intentional head motion and a higher level of image quality when compared to uncorrected scans or a reference method. Multislice-to-volume-based prospective motion correction is then combined with simultaneous multislice imaging to further increase the temporal resolution of motion correction updates in a way that a single EPI readout train provides enough information for sufficient motion detection. This technique is applied to multiband functional MRI pulse sequences, resulting in up to 50 % reduction of residual motion parameters and improvements in temporal signal-to-noise ratio as well as brain activation study results when compared to conventional, volume-tovolume-based prospective motion correction during in-vivo imaging studies.