Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost-Effective Simulations of Vibrationally-Resolved Absorption Spectra of Fluorophores with Machine-Learning-Based Inhomogeneous Broadening

The results of electronic and vibrational structure simulations are an invaluable support for interpreting experimental absorption/emission spectra, which stimulates the development of reliable and cost-effective computational protocols. In this work, we contribute to these efforts and propose an efficient first-principle protocol for simulating vibrationally-resolved absorption spectra, including nonempirical estimations of the inhomogeneous broadening. To this end, we analyze three key aspects: (i) a metric-based selection of density functional approximation (DFA) so to benefit from the computational efficiency of time-dependent density function theory (TD-DFT) while safeguarding the accuracy of the vibrationally-resolved spectra, (ii) an assessment of two vibrational structure schemes (vertical gradient and adiabatic Hessian) to compute the Franck–Condon factors, and (iii) the use of machine learning to speed up nonempirical estimations of the inhomogeneous broadening. In more detail, we predict the absorption band shapes for a set of 20 medium-sized fluorescent dyes, focusing on the bright ππ★ S0 → S1 transition and using experimental results as references. We demonstrate that, for the studied 20-dye set which includes structures with large structural variability, the preselection of DFAs based on an easily accessible metric ensures accurate band shapes with respect to the reference approach and that range-separated functionals show the best performance when combined with the vertical gradient model. As far as band widths are concerned, we propose a new machine-learning-based approach for determining the inhomogeneous broadening induced by the solvent microenvironment. This approach is shown to be very robust offering inhomogeneous broadenings with errors as small as 2 cm–1 with respect to genuine electronic-structure calculations, with a total CPU time reduced by 98%.
Iterative approximation algorithm of Hessian matrix in structural optimization

To avoid calculating Hessian matrix when the object function and the constraint functions are approximated by the second-order taylor expansion, a first-order method called Davidon and Fletcher-Powell method (DFP method) was used to obtain the inversion of the Hessian matrix, which completely eliminates the need for evaluating the second-order derivatives and performing matrix inversion. The presented method was implemented for the optimization of a cantilever plate with stiffeners. The calculation results show that DFP method is effective for structural optimization.
Comparative Analysis of ANFIS, ARIMA and Polynomial Curve Fitting for Weather Forecasting

Background/Objectives: Weather forecasting is to facilitate the appliance of knowledge and tools to predict the state of the atmosphere for a future time at a given location. Methods/Statistical Analysis: This paper focused to forecast the weather conditions on Indian weather conditions using three approaches such as ANFIS, ARIMA and polynomial curve fitting. It’s disbursed by collection quantitative information regarding state of the atmosphere and past and/or present experiences. Findings: In this analysis, this work reveals the superior performance of polynomial curve fitting through the SSE, RMSE, MAE and R 2 .
Wearable Multisensor Ring-Shaped Probe for Assessing Stress and Blood Oxygenation: Design and Preliminary Measurements

The increasing interest in innovative solutions for health and physiological monitoring has recently fostered the development of smaller biomedical devices. These devices are capable of recording an increasingly large number of biosignals simultaneously, while maximizing the user’s comfort. In this study, we have designed and realized a novel wearable multisensor ring-shaped probe that enables synchronous, real-time acquisition of photoplethysmographic (PPG) and galvanic skin response (GSR) signals. The device integrates both the PPG and GSR sensors onto a single probe that can be easily placed on the finger, thereby minimizing the device footprint and overall size. The system enables the extraction of various physiological indices, including heart rate (HR) and its variability, oxygen saturation (SpO2), and GSR levels, as well as their dynamic changes over time, to facilitate the detection of different physiological states, e.g., rest and stress. After a preliminary SpO2 calibration procedure, measurements have been carried out in laboratory on healthy subjects to demonstrate the feasibility of using our system to detect rapid changes in HR, skin conductance, and SpO2 across various physiological conditions (i.e., rest, sudden stress-like situation and breath holding). The early findings encourage the use of the device in daily-life conditions for real-time monitoring of different physiological states.
Multidimensional Analysis of Nuclear Detonations

Abstract : The focus of this research is to develop the methods for 3-dimensional reconstructions and temperature distributions of early time nuclear fireballs. Initial developments have resulted in the first 2-dimensional temperature distribution of a nuclear fireball using digitized film. This same process was then extended to perform the first limb darkening calculations of nuclear fireballs. Limb darkening coefficients were then used to derive a temperature profile of the nuclear fireball as a function of optical path length. A 3-dimensional reconstruction was performed using a variation of a structure from illuminance technique in combination with limb darkening coefficients to produce structure using a single image. This dissertation also highlights the difficulties in using common computer vision feature descriptors such as Scaled Invariant Feature Transform and Speeded Up Robust Features on nuclear weapons testing data. The use of these techniques to produce accurate dense reconstructions is likely to require both single image and multiple view geometry in order to produce consistently accurate results.
Formulation of Ground States for 2DEG at Rough Surfaces and Application to Nonlinear Model of Surface Roughness Scattering in nMOSFETs

Electron mobility in extremely-thin-body (ETB) nanosheet channels and at cryogenic temperature is known to be dominated by surface roughness scattering. However, the conventional model of surface roughness scattering lacks accuracy because it requires the use of excessive roughness parameters to represent the experimental results. One of the main difficulties for the surface roughness scattering model is that the higher-order perturbations should be accurately included in the model because the surface roughness scattering is a strongly nonlinear phenomenon. Therefore, in this study, the formulation of ground states of two-dimensional electron gas (2DEG) at rough surfaces is derived by introducing a concept of the space-averaged perturbation Hamiltonian. This revised formulation of 2DEG at rough surfaces is different from the conventional solution for 2DEG at the flat surface. The space-averaged perturbation Hamiltonian is invisible in the linearized perturbation system, while its effect is significant in the system with the nonlinear perturbation energy. We combine the revised 2DEG formulation with a nonlinear model of surface roughness scattering and calculate the 2DEG mobility of the bulk Si and ETB Si-on-insulator (SOI) nMOSFETs. As a result, the experimental mobility of bulk and ETB SOI nMOSFETs is well explained in a wide temperature range of 4.2 to 300 K by using the roughness parameters experimentally obtained by transmission electron microscopy (TEM), which also supports the understanding of mobility at cryogenic temperature. The revised nonlinear model reveals that surface roughness scattering under the present model is 13 times stronger than that predicted by the conventional linear model.
Visual Servoing of Rigid-Link Flexible-Joint Manipulators in the Presence of Unknown Camera Parameters and Boundary Output

Exact position control of the flexible-joint manipulator (FJM) is a challenging task due to the manipulator’s nonlinearity and underactuated characteristic. For the three-dimensional (3-D) rigid-link FJM, the image-based visual servoing (IBVS) approach with link-position output constraint and unknown camera parameters is investigated in this article. The controller is designed to deal with three problems. First, the visual servoing control law is divided into two domains based on the singular perturbation method, where the control input for the fast subsystem is developed to damp out the flexible joint’s vibration. Second, the adaptive updating law for estimating the unknown camera parameters is presented in the slow subsystem. Third, to guarantee that the rigid-link position keep in set constraints, the controller for the slow subsystem is designed by introducing a barrier Lyapunov function. According to the Lyapunov theorem of stability, the proposed controller for the FJM is theoretically proved to be asymptotically stable. Several numerical simulation experiments are provided to illustrate that the presented control scheme is effective.
Bioactive Compounds Produced by Endophytic Microorganisms Associated with Bryophytes—The “Bryendophytes”

The mutualistic coexistence between the host and endophyte is diverse and complex, including host growth regulation, the exchange of substances like nutrients or biostimulants, and protection from microbial or herbivore attack. The latter is commonly associated with the production by endophytes of bioactive natural products, which also possess multiple activities, including antibacterial, insecticidal, antioxidant, antitumor, and antidiabetic properties, making them interesting and valuable model substances for future development into drugs. The endophytes of higher plants have been extensively studied, but there is a dearth of information on the biodiversity of endophytic microorganisms associated with bryophytes and, more importantly, their bioactive metabolites. For the first time, we name bryophyte endophytes “bryendophytes” to elaborate on this important and productive source of biota. In this review, we summarize the current knowledge on the diversity of compounds produced by endophytes, emphasizing bioactive molecules from bryendophytes. Moreover, the isolation methods and biodiversity of bryendophytes from mosses, liverworts, and hornworts are described.
Voltage Independent Reactive Current Based Sensor for Static VAr Control Applications

The use of renewable energy-based converters is continuously increasing in modern power systems which inject voltage harmonics in the line. In this work, a novel, simple technique based on a binary (on/off) control of an analog switch is proposed to measure reactive current and reactive power. This method eliminates the requirement of finding sin(<inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>) and its multiplication with the current signal in reactive power computation. The proposed transducer gives a dc signal proportional to the reactive current of a power system, i.e., <inline-formula> <tex-math notation="LaTeX">${I}$ </tex-math></inline-formula>sin(<inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>), which is suitable for static VAr compensator (SVC) applications. This transducer output is sufficient as the terminal voltage is common for the measurement as well as for the compensation current. Thus, the required current of SVC for compensation is equal to or proportional to <inline-formula> <tex-math notation="LaTeX">${I}$ </tex-math></inline-formula>sin(<inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>). Moreover, voltage harmonics are common in a power system. These harmonics affect the measurement of fundamental reactive power. This method eliminates the need for voltage measurement and hence the measurement is independent of the harmonics of the voltage, which reduces the measurement error. The proposed method is proved mathematically, and its performance is successfully validated through simulation analysis and hardware implementation. The advantages of the proposed technique are linearity of the transducer output, simple working, inexpensive hardware realization, fast response, and online measurement capability. The response time of the transducer is one cycle of supply voltage which is suitable for SVC applications.
Wavelet Transform Theory and Its Application in Signal Processing

The wavelet transform has become a new signal processing technology in last decade, it has been imposed great importance by more and more theoretical workers and engineers. Simultaneity, the mathematical theory of the wavelet transform is complicated. In this paper, the basic theory and advantage of wavelet transform is simply revealed by comparing with Fourier transform and short time Fourier transform, deep cognition and understanding of wavelet transform is given by MATLAB simulation. These result shows that wavelet transform is superior to Fourier transform and short time Fourier transform both in time and frequency orientation in signal processing.
Two-Step Matching Approach to Obtain More Control Points for SIFT-like Very-High-Resolution SAR Image Registration

Airborne VHR SAR image registration is a challenging task. The number of CPs is a key factor for complex CP-based image registration. This paper presents a two-step matching approach to obtain more CPs for VHR SAR image registration. In the past decade, SIFT and other modifications have been widely used for remote sensing image registration. By incorporating feature point location affine transformation, a two-step matching scheme, which includes global and local matching, is proposed to allow for the determination of a much larger number of CPs. The proposed approach was validated by 0.5 m resolution C-band airborne SAR data acquired in Sichuan after the 2008 Wenchuan earthquake via a SAR system designed by the IECAS. With the proposed matching scheme, even the original SIFT, which is widely known to be unsuitable for SAR images, can achieve a much larger number of high-quality CPs than the one-step SIFT–OCT, which is tailored for SAR images. Compared with the classic one-step matching approach using both the SIFT and SITF–OCT algorithms, the proposed approach can obtain a larger number of CPs with improved precision.
Relationships between energy cost, swimming velocity and speed fluctuation in elite butterfliers

contribution from anaerobic energetic system to cover total energy expenditure. R=0.70 (p<0.01). The individual correlations between EC and dv controlling the effect of v ranged from R=0.99 (p=0.06) to R=-0.81 Intra-cycle variation of horizontal velocity of centre of body mass (dv) is a widely accepted criterion for biomechanical evaluation of swimming techniques. There are some evidences of positive relationships between high dv and increased energy cost in (p=0.09). For pooled data, the relationship between EC and dv was
Optical microscopic imaging and digitized evaluation system for super-smooth surface defects

An optical microscopic scattering imaging system was proposed in this paper.It was combined by ring distribution of multi -beam LED light source and a microscope system.An image of bright defects in black background was obtained,which was suitable for binary-state processing of digital image.Full aperture measurement could be obtained by X,Y sub-aperture scanning system.A multi-cycle image mosaic algorithm based on both feature classification and the previous "edge-expansion method" was proposed,which would be divided into four types for overlapping regions of the entire sub -aperture image.Then the multi -cycle mosaic was conducted according to different defect features distribution in the overlapped region.Therefore,A full aperture image could be obtained.A group of standard reticules were fabricated by binary optics.It could be used to calibrate the scale of the defects.Experimental results show that the system and the mosaic algorithm for images of defects are suitable for detection and evaluation of the large aperture fine surface.
Dynamic dependencies and return connectedness among stock, gold and Bitcoin markets: Evidence from South Asia and China

Research background: In order to examine market uncertainty, the paper depicts broad patterns of risk and systematic exposure to global equity market shocks for the major South Asian and Chinese equity markets, as well as for specific assets (gold and Bitcoin). Purpose of the article: The purpose of this paper is to investigate the dynamic correlation among the major South Asian equity markets (India and Pakistan), the Chinese equity markets, the MSCI developed markets, Bitcoin, and gold markets. Methods: While applying the GARCH-Vine-Copula model and the TVP-VAR Connectedness approach, major patterns of dependency and interconnectedness between these markets are investigated. Findings & value added: We find that risk shocks from developed equity markets are critical in these dynamic links. A net return spillover from Bitcoin to the Chinese and Pakistani stock markets throughout the sample period is reported. Interestingly, gold can be applied to hedge and diversify positions in China and major South Asian markets, particularly following the COVID-19 outbreak. Our paper presents three main original add valued: (1) This paper adds global factors to the targeted study of risk transmission among South Asian and Chinese stock markets for the first time. (2)The assets of Bitcoin and gold were added to the study of risk transmission among South Asian and Chinese stock markets for the first time, enabling the research in this paper to observe the non-linear link among the South Asian and Chinese stock markets with them. (3) Our research adds to these lines of inquiry by giving empirical evidence on how COVID-19 altered the dependent structure and return spillover dynamics of Bitcoin, gold and South Asian and Chinese stock markets for the first time. Our results have critical implications for investors and policymakers to effectively understand the nature of market forces and develop risk-averse strategies.
Digital image evaluation function based on gray gradient

It is proposed to use vector norm sum of image gray gradient, Roberts gradient sum and Laplacian (8 neighborhood differential) operator sum as evaluation functions of digital image. The mathematical models for the above several evaluation functions are established. The experimental results are given against the defocusing and motion blurring, respectively and a comparison is carried out. All of them have the characteristics of good unbias(s)edness, powerful unimodality and high sensitivity, etc., and can be applied to evaluation of defocusing and motion blurring. The vector norm sum of gray gradient is the best among them.
Determinants Influencing Non-Performing Loan Ratio of Joint Stock Commercial Banks in Vietnam

This study investigates macro and micro determinants of the ratio of non-performing loans (MPG ratio) of Vietnam commercial banks between 2015 and 2021. Data were collected from fifteen banks with total assets accounting for 62.9% of the total banking industry assets. The regression analytical technique is used to determine the impact of some independent variables on the MPG ratio of sample banks. The results reveal that the non -performing loan ratio is negatively correlated with the bank's asset size and loan growth rate but positively correlated with the net interest margin and the credit risk. The variable of Covid-19 has no statistically significant correlation with the non-performing loans ratio. Although a range of previous studies on that topic has been carried out, none of them digs deeper into the impact of these explanatory variables on the ratio of non-performing loans of Vietnamese commercial banks, especially the impact of Covid-19, whereas the banking industry of Vietnam is far-affected by that epidemic. Therefore, these findings can be used by creditors, investors, bank managers, and policy-makers when they have to give decisions relating to commercial banks in this complex period.
3D CONSISTENT VISCOUS-SPRING ARTIFICIAL BOUNDARY AND VISCOUS-SPRING BOUNDARY ELEMENT

The stiffness and damping matrixes of 3D consistent artificial boundary are deduced through viscous-spring artificial boundary theory. 3D equivalent viscous-spring artificial boundary element is developed by comparing the matrixes of general finite element and consistent viscous-spring artificial boundary. This boundary element is applied to uniform and layered half space problems, respectively. The results show that 3D equivalent viscous-spring boundary element has the same precision as viscous-spring artificial boundary, and the former is more applicable and simple.
A Simple & Effective Video Sequence Super-Resolution Algorithm

To solve the problem of sequence to sequence super resolution,a video sequence super resolution algorithm based on a frame of reference high resolution image is proposed in this paper.The algorithm is based on the fact that in most cases,the vidicon device has dual mode:HR(High Resolution) still and LR(Low Resolution) video.In the algorithm,a HR still image acquired from the same scene is used as an example,the high frequency details of it are extracted and then motion compensated and reliability weighted for super resolution of the corresponding low resolution frames.The estimated HR frames are then constraint optimized under the Maximum A Posteriori(MAP) framework to improve its fidelity.Evaluated by several sequences, the proposed algorithm shows obvious performance improvements compared with the traditional bilinear interpolation and the MAP based static batch method.The average PSNR(Peak Signal-to-Noise Ratio) of the reconstructed frames are improved by more than 2.4 dB.
Trajectory planning and control of collaborative systems : Application to trirotor UAVS.

This thesis is dedicated to the creation of a complete framework, from high-level to low-level, of trajectory generation for a group of independent dynamical systems. This framework, based for the trajectory generation, on the resolution of Burgers equation, is applied to a novel model of trirotor UAV and uses the flatness of the two levels of dynamical systems.The first part of this thesis is dedicated to the generation of trajectories. Formal solutions to the heat equation are created using the differential flatness of this equation. These solutions are transformed into solutions to Burgers' equation through Hopf-Cole transformation to match the desired formations. They are optimized to match specific requirements. Several examples of trajectories are given.The second part is dedicated to the autonomous trajectory tracking by a trirotor UAV. This UAV is totally actuated and a nonlinear closed-loop controller is suggested. This controller is tested on the ground and in flight by tracking, rolling or flying, a trajectory. A model is presented and a control approach is suggested to transport a pendulum load.