Miracle-dz/UniFAR-FTUs huggingface dataset:
The QME AERI LBLRTM: A Closure Experiment for Downwelling High Spectral Resolution Infrared Radiance

Abstract Research funded by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m−2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM). A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three.
High-order accurate entropy stable numercial schemes for hyperbolic conservation laws

The role of entropy for the stability of hyperbolic conservation laws is well-understood, and to some extent, also for firstand second-order accurate numerical schemes. The stability of higher-order accurate schemes, however, is to a large degree an open problem. In this thesis we adopt the framework of entropy stability as a design principle. We combine entropy conservative fluxes with appropriate diffusion operators, and to obtain high order accuracy, we consider diffusion operators using the ENO reconstruction procedure. We show that the ENO procedure satisfies the so-called sign property, which ensures entropy stability of our (arbitrarily) high-order accurate finite difference scheme. Moreover, we pose and argue for a conjecture on the total variation of the ENO reconstruction, which would imply a weak total variation bound for our scheme. For hyperbolic systems, the reconstruction is performed using a novel, computationally efficient characteristic-wise decomposition. The scheme is easily generalized to multi-dimensional systems on Cartesian meshes. To study the convergence properties of our scheme for scalar equations, we consider the framework of compensated compactness. Under the assumption that our conjecture on the total variation bound of ENO holds, we prove convergence to the entropy solution. For multidimensional hyperbolic systems we are able to prove convergence to an entropy measurevalued solution. The robustness, accuracy and computational efficiency of the scheme are demonstrated in a series of numerical experiments.
Urban Road Traffic Flow Prediction with Attention-Based Convolutional Bidirectional Long Short-Term Memory Networks

Accurate traffic prediction is critical for industry practitioners and researchers in intervening and dredging future traffic in advance to avoid traffic congestion. Considering that most prediction models fail to effectively capture the complex nonlinearity of traffic data and thus cannot obtain satisfactory prediction results, we propose a novel deep-learning architecture for traffic flow prediction, called AC-BLSTM (attention-based convolutional bidirectional long short-term memory). The proposed model captures traffic information through multilayer network architectures composed of convolutional bidirectional long short-term memory (conv-BiLSTM) network and attention mechanism. The spatiotemporal features of traffic flow are extracted by convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) network. Then attention mechanism combines the outputs of CNN and BiLSTM to assign corresponding weights to the features extracted at different times. In addition, we employ a parallel sub-module structure to model three temporal properties of traffic flow, that is, weekly, daily, and recent dependencies. Finally, the results of these three parts are fused to predict the traffic flow values through the fully connected (FC) layers. Experiment results using a real-world urban road traffic dataset demonstrate that compared with other competing models, the proposed model has better prediction performance.
Antioxidant and Antiproliferative Activities of Kale (Brassica oleracea L. Var. acephala DC.) and Wild Cabbage (Brassica incana Ten.) Polyphenolic Extracts

Brassicaceae are rich in healthy phytochemicals that have a positive impact on human health. The aim of this study was to analyze the phenolic compounds and antioxidant and anticancer potential of traditional Croatian kale (Brassica oleracea L. var. acephala DC.) and wild cabbage (Brassica incana Ten.) extracts. The phenolic groups and antioxidant activity were determined by spectrophotometry, selected phenolic compounds (ferulic acid, sinapic acid, salicylic acid, kaempferol, and quercetin) were analyzed by LC-MS/MS, and anticancer potential was evaluated in vitro using HeLa cells. The extracts of both plant species are rich in phenolic compounds and showed significant antioxidant activity at similar levels. LC-MS/MS detected sinapic acid as the most abundant phenolic acid, followed by ferulic acid, while salicylic acid was present at lower concentrations. A comparative analysis showed that wild cabbage contained significantly more sinapic acid, while kale contained more kaempferol and quercetin. Both Brassica extracts at a concentration of 50 µg mL−1 showed an antiproliferative effect on HeLa cells, while they did not affect the proliferation of normal human skin fibroblasts. Wild cabbage extract also showed an antiproliferative effect on HeLa cells at a lower applied concentration of 10 µg mL−1 of extracts. The clonogenic analysis also revealed the inhibitory effect of the extracts on HeLa colony growth.
Accretion magnetosphere stability. I. Adiabatic gas model.

We assess the local interface stability of a vacuum dipole magnetic field that is confined by gravitationally trapped plasma external to the star. For simplicity, we take the radial dependence of the plasma pressure to be P=P/sub 0/r/sup -//sup K/, and find: a) For K< or =K/sub c/ the resultant axially symmetric magnetopause is buoyantly stable, the equatorial magnetopause pressure is about 8 times larger than B/sup 2//8.pi. for an unconfined dipole at the same distance, and the magnetic pressure increases below the equatorial magnetopause approximately as r/sup -2//sup . //sup 5/ at the equator. b) For K/sub c/
Android-IoT Malware Classification and Detection Approach Using Deep URL Features Analysis

Currently, malware attacks pose a high risk to compromise the security of Android-IoT apps. These threats have the potential to steal critical information, causing economic, social, and financial harm. Because of their constant availability on the network, Android apps are easily attacked by URL-based traffic. In this paper, an Android malware classification and detection approach using deep and broad URL feature mining is proposed. This study entails the development of a novel traffic data preprocessing and transformation method that can detect malicious apps using network traffic analysis. The encrypted URL-based traffic is mined to decrypt the transmitted data. To extract the sequenced features, the N-gram analysis method is used, and afterward, the singular value decomposition (SVD) method is utilized to reduce the features while preserving the actual semantics. The latent features are extracted using the latent semantic analysis tool. Finally, CNN-LSTM, a multi-view deep learning approach, is designed for effective malware classification and detection.
A Systematic Review and Meta-Analysis of the Effectiveness of Virtual Reality-Based Rehabilitation Therapy on Reducing the Degree of Pain Experienced by Individuals with Low Back Pain

Background: The concept of virtual reality (VR)-based rehabilitation therapy for treating people with low back pain is of growing research interest. However, the effectiveness of such therapy for pain reduction in clinical settings remains controversial. Methods: The present study was conducted according to the reporting guidelines presented in the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. We searched the PubMed, Embase, CENTRAL, and ProQuest databases for both published and unpublished papers. The Cochrane risk of bias tool (version 2) was used to evaluate the quality of the selected studies. GRADEprofiler software (version 3.6.4) was used to evaluate the level of evidence. We analyzed the included research results using RevMan software (version 5.4.1). Results: We included a total of 11 articles in the systematic review and meta-analysis, with a total of 1761 subjects. Having assessed the quality of these studies, the risk of bias was generally low with high heterogeneity. The results revealed a small to medium effect (standardized mean difference = ±0.37, 95% confidence interval: 0.75 to 0) based on evidence of moderate overall quality. Conclusion: There is evidence that treatment using VR improves patients’ pain. The effect size was small to medium, with the studies presenting evidence of moderate overall quality. VR-based treatment can reduce pain; therefore, it may help in rehabilitation therapy.
Image denoising using least squares wavelet support vector machines

We propose a new method for image denoising combining wavelet transform and support vector machines (SVMs). A new image filter operator based on the least squares wavelet support vector machines (LS-WSVMs) is presented. Noisy image can be denoised through this filter operator and wavelet thresholding technique. Experimental results show that the proposed method is better than the existing SVM regression with the Gaussian radial basis function (RBF) and polynomial RBF. Meanwhile, it can achieve better performance than other traditional methods such as the average filter and median filter.
Perturbations of countable Markov chains and processes

AbstractIfP is a transition matrix of a Markov chain, and $$\tilde P$$ is derived by perturbing the elements ofP, then we find conditions such that $$\tilde P$$ is also positive recurrent whenP is, and relate the invariant probability measures for the two. Similar results are found for recurrence of chains, and the methods then yield analogues for continuous time processes also.
Steric Changes Associated With the Fast Sea Level Rise in the Upper South Indian Ocean

This study provides a quantitative assessment of steric changes associated with sea level rise in the upper (0–500 m) South Indian Ocean (SIO) during 1993–2017, using the latest ocean state estimate of Estimating the Circulation and Climate of the Ocean (ECCO) combined with in‐situ observations from Argo. Both the observations and ECCO estimate show a sea level rise in the low‐latitude (0°–30°S) SIO that is faster than its South Pacific and South Atlantic counterparts by a factor at least two. Much of this fast sea level rise is due to warming and freshening of the upper ocean, with no significant contribution from the deeper layers (>500 m). We emphasize the importance of halosteric effect, whose contribution to sea level rise is comparable with that of thermosteric effect in the eastern basin. On interannual time scale, up to 90% of the region's sea level variability can be explained by steric changes that in turn are dominated by upper ocean convergence.
Adaptive control of a solar energy plant : Exploiting accessible disturbances

This paper deals with temperature control in an industrial-scale distributed collector solar field. The need for adaptive control arises from the highly time-varying behaviour of both the plant dynamics and the solar radiation effects in the collector field due to atmospheric changes. The control problem consists of keeping constant the field outlet oil temperature by acting on the oil flow. The manipulated variable is chosen so as to minimize a receding horizon quadratic cost. The underlying control law is of model-based predictive control type, adaptively implemented by a MUSMAR algorithm, modified so as to exploit the information conveyed by the accessible disturbances. Experimental results are reported showing the significance on the achievable performance of the feedforward term depending on the accessible disturbances. © 1997 John Wiley & Sons, Ltd.
Designing and In Silico Evaluation of Some Non-Nucleoside MbtA Inhibitors: On Track to Tackle Tuberculosis

: The WHO database shows that mycobacterium tuberculosis has become an epidemic worldwide due to its pathogenicity and virulence, which have magniﬁed its infectiousness. The situation becomes grimmer with the prevalence of MDR-TB, XDR-TB, emergence of cross-resistance, ineffectiveness of novel therapeutic targets, failure of novel medications in clinical trials, currently available drugs losing their therapeutic efﬁcacy, lack of drug discovery efforts due to poor ROI, and the existence of co-infections; i.e., HIV, TB, COVID, and HIV-TB-COVID. Following our prior studies described by Stirret et al. in 2008, Ferreras et al. in 2011, and Shyam et al. in 2021, herein we focus on exploring pyrazoline-based mycobactin analogs (non-speciﬁc mycobactin biosynthesis inhibitors) targeting the MbtA enzyme (ﬁrst step of mycobactin biosynthesis) with a hope of ﬁnding a more potent analog showing a high afﬁnity for MbtA . The design strategy involves retaining the structural features of mycobacterial siderophores. Herein, a small library (12 molecules) of mycobactin analogs were designed, keeping the necessary skeleton (diaryl-substituted pyrazoline (DAP)) intact and assessed their stability using in silico tools. In order to determine the binding modes and inhibitory proﬁles of the designed ligands, docking was carried out in the active pocket of MbtA (analogous with the homologous structure with PDB ID: 1MDB). The best energy conformation (lowest score) of each docked ligand was represented graphically. The ADMET proﬁle of each molecule was analyzed. The best molecule that revealed a good ADMET proﬁle was taken up for MD simulation study (45 ns). Results revealed that the designed compounds GV08 ( − 8.80 kcal/mol, 352.58 nM), GV09 ( − 8.61 kcal/mol, 499.91 nM), GV03 ( − 8.59 kcal/mol, 508.51 nM), and GV07 ( − 8.54 kcal/mol, 553.44 nM) had a good docking score and inhibition constant. Of these, GV08 showed a good ADME proﬁle with all the major parameters lying in the acceptable ranges. They also showed the least toxicity with no hepatotoxicity and skin sensitization. MD simulation studies of GV08 also suggest that it was stable throughout the course of simulation. This could be justiﬁed by RMSD, RMSF, and H-bond plots. The future scope invalidates these ﬁndings through synthesis
Combined atomic force microscopy-Raman mapping of electric field enhancement and surface-enhanced Raman scattering hot-spots for nanosphere lithography substrates

Surface-enhanced Raman spectroscopy (SERS) substrates formed by nanosphere lithography were investigated for their spatial distribution and magnitude of electric field en- hancement. An integrated atomic force microscopy and Raman micro-spectroscopy system was used to establish, with high accuracy, the correlation between the local SERS mappings and substrate topography. Using a monolayer of rhodamine 6G as a probe of the local electric field, the high resolution Raman mappings, showed that the highest electric field enhancement orig- inates from the metallic nanostructures rather than the gaps between them. The enhancement factor of the substrates is calculated from Raman spectra of the substrates covered in a mono- layer of p-aminothiophenol and spatial measurements, giving a value on the order of 10 5 . T he experimental results were confirmed by theoretical calculations using the finite element method.
Investigation of UV photodetector properties of zirconium (Zr)-doped zinc oxide (ZnO)

We report the effect of Zr-doping on the structural, morphological, optical, and UV detection properties of ZnO samples. Pure and zirconium (Zr) (1 wt%, 3 wt%, and 5 wt%)-doped ZnO samples are prepared by the conventional hydrothermal method. The X-ray diffraction (XRD) analysis revealed hexagonal wurtzite structure of ZnO. Hi-resolution scanning electron microscope (HR-SEM) images showed the formation of hexagonal nanoprism morphology in all the samples. In XPS data analysis, it was found that the 3 wt% sample had larger area for oxygen vacancies as compared to other samples. Over the UV illumination these oxygen vacancies increases the number of electrons thereby increase the photocurrent of the sample. The improvement in UV detection properties of 3 wt% Zr-doped ZnO samples makes them useful for optoelectronic applications. Graphical abstract
Extended local Born Fourier migration method

A migration approach based on a local application of the Born approximation within each extrapolation interval contains a singularity that can make direct application unstable. Previous authors have suggested adding an imaginary part to the vertical wavenumber to eliminate the singularity. However, their method requires that the reference slowness must be the maximum slowness of a given layer; consequently, the slowness perturbations are larger than those when the average slowness is selected as a reference slowness. Therefore, its applicability is limited. We develop an extended local Born Fourier migration method that circumvents the singularity problem of the local Born solution and makes it possible to choose the average slowness as a reference slowness. It is computationally efficient because of the use of a fast Fourier transform algorithm. It can handle wider angles (or steeper interfaces) and scattering effects of heterogeneities more accurately than the split‐step Fourier (SSF) method, which acco.
Single photon sources in the infrared

This thesis reports the study of single photon sources that emit one infrared wavelength photon at a time, creating cavity quantum electrodynamical effects for applications such as quantum information processing. This work considers two major single photon sources: a) InAs single quantum dots and b) single carbon nanotubes, which both emit in the infrared range. Photonic crystal slabs and photonic crystal waveguides are served as distinctive passive devices with manipulated photonic band-gaps to control the propagating light. A simulation of leaky modes of two-dimensional photonic crystal slabs is introduced to constrain model parameters in the device design. Fullerenes are used as fluorescent material to achieve resonance of a leaky mode with excitation 1492 nm and emission at 1519 nm and to see enhancement of the PL. We include novel characterization techniques and PL measurements to show sharp emission peaks from single quantum dots and successfully couple them to micro-cavities. The strong coupling effect is observed and is amongst the best examples of cavity-dot structures achieved to date. Single-walled carbon nanotubes have shown anti-bunched light emission, thus we systematically study them as another possible candidate of single photon sources. PLE spectra show clear evidence of the existence of excited states, and time evolution measurements reveal the disorder induced diffusion, which separate the tubes into a series of quantum dots. These strongly confined states are concluded as the origin of the possibility that single-walled carbon nanotubes are single photon sources.
Information entropy and dimension calculation on heart rate variability

An approach to construct the probability density curve (PDC) of a phase response curve (PRC), in which the PRC reflects directly heart rate fluctuations by phase shifts during different vagal stimuli, is presented. It was found that the width of the PDC usually represents the amount of heart rate variation. The narrow PDC with high peaks implies less heart rate variability, while the wide and flat PDC implies high heart rate variability. Based on the PDC, information entropy has been calculated. Information entropy can give the amount of information needed to specify the state of the PRC or the state of the heart rate variability to an accuracy of the box size. Current work has indicated that large information entropy means large heart rate variability and less predictability. On the other hand, information dimension has been derived from information entropies of the different box sizes. Information dimension is an index of the complexity of a system that generated the data. A low dimension means that less states are needed to describe the system while a large dimension means more states are required to describe the system. <<ETX>>
Role of two RpoN in Bradyrhizobium sp. strain DOA9 in symbiosis and free-living growth

RpoN is an alternative sigma factor (sigma 54) that recruits the core RNA polymerase to promoters of genes. In bacteria, RpoN has diverse physiological functions. In rhizobia, RpoN plays a key role in the transcription of nitrogen fixation (nif) genes. The Bradyrhizobium sp. DOA9 strain contains a chromosomal (c) and plasmid (p) encoded RpoN protein. We used single and double rpoN mutants and reporter strains to investigate the role of the two RpoN proteins under free-living and symbiotic conditions. We observed that the inactivation of rpoNc or rpoNp severely impacts the physiology of the bacteria under free-living conditions, such as the bacterial motility, carbon and nitrogen utilization profiles, exopolysaccharide (EPS) production, and biofilm formation. However, free-living nitrogen fixation appears to be under the primary control of RpoNc. Interestingly, drastic effects of rpoNc and rpoNp mutations were also observed during symbiosis with Aeschynomene americana. Indeed, inoculation with rpoNp, rpoNc, and double rpoN mutant strains resulted in decreases of 39, 64, and 82% in the number of nodules, respectively, as well as a reduction in nitrogen fixation efficiency and a loss of the bacterium’s ability to survive intracellularly. Taken together, the results show that the chromosomal and plasmid encoded RpoN proteins in the DOA9 strain both play a pleiotropic role during free-living and symbiotic states.