Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetoelectric metglas/bidomain y + 140°-cut lithium niobate composite for sensing fT magnetic fields

We investigated the magnetoelectric properties of a new laminate composite material based on y + 140°-cut congruent lithium niobate piezoelectric plates with an antiparallel polarized “head-to-head” bidomain structure and metglas used as a magnetostrictive layer. A series of bidomain lithium niobate crystals were prepared by annealing under conditions of Li2O outdiffusion from LiNbO3 with a resultant growth of an inversion domain. The measured quasi-static magnetoelectric coupling coefficient achieved |αE31| = 1.9 V·(cm Oe)−1. At a bending resonance frequency of 6862 Hz, we found a giant |αE31| value up to 1704 V·(cm Oe)−1. Furthermore, the equivalent magnetic noise spectral density of the investigated composite material was only 92 fT/Hz1/2, a record value for such a low operation frequency. The magnetic-field detection limit of the laminated composite was found to be as low as 200 fT in direct measurements without any additional shielding from external noises.
Pricing methods for Asian options

We present various methods of pricing Asian options. The methods include Monte Carlo simulations designed using control and antithetic variates, numerical solution of partial differential equation and using lower bounds. The price of the Asian option is known to be a certain risk-neutral expectation. Using the Feynman-Kac theorem, we deduce that the problem of determining the expectation implies solving a linear parabolic partial differential equation. This partial differential equation does not admit explicit solutions due to the fact that the distribution of a sum of lognormal variables is not explicit. We then solve the partial differential equation numerically using finite difference and Monte Carlo methods. Our Monte Carlo approach is based on the pseudo random numbers and not deterministic sequence of numbers on which Quasi-Monte Carlo methods are designed. To make the Monte Carlo method more effective, two variance reduction techniques are discussed. Under the finite difference method, we consider explicit and the Crank-Nicholson’s schemes. We demonstrate that the explicit method gives rise to extraneous solutions because the stability conditions are difficult to satisfy. On the other hand, the Crank-Nicholson method is unconditionally stable and provides correct solutions. Finally, we apply the pricing methods to a similar problem of determining the price of a European-style arithmetic basket option under the Black-Scholes framework. We find the optimal lower bound, calculate it numerically and compare this with those obtained by the Monte Carlo and Moment Matching methods. Our presentation here includes some of the most recent advances on Asian options, and we contribute in particular by adding detail to the proofs and explanations. We also contribute some novel numerical methods. Most significantly, we include an original
The Relationship between Human Capital and Public Services Performance: The Role of Islamic Work Ethics as a Mediating Variable A Case Study of Public Sector Organizations of Bahrain

Ethics are the basis for achieving individual, group and societal happiness. This research paper studies the role of Islamic work ethics as a mediating variable in the relationship between human capital and public services performance in the public sector of Bahrain. The scarcity of previous studies in the field of Islamic work ethics as a mediating variable in the relationship between human capital and public services performance is the motivating factor of this study. A total of 640 questionnaires were distributed to the citizens in the four governorates of Bahrain, i.e., Southern, Muharraq, Northern and the Capital, using the systematic random sampling method, A five point Likert scale was used to measure all variables. A total of 384 questionnaires were returned of which 368 were usable questionnaires. The findings of this research paper show a significant and positive relationship between human capital and public services performance. Islamic work ethics, as the mediating variable, has a highly positive effect on the relationship between human capital and public services performance.
Vibrational spectroscopy of compound semiconductor nanocrystals

A review of recent applications of Raman spectroscopy as a fast, sensitive, and non-destructive technique for exploring II–VI semiconductor nanocrystals fabricated by various methods (colloidal chemistry, Langmuir–Blodgett method, diffusion-limited growth) is presented. Specific size-related features revealed in the nanocrystal Raman spectra (phonon confinement, surface phonons) are analysed, as well as more complicated size effects for ultrasmall nanocrystals (NCs) related to the activation of the phonon density of states modified by surface reconstruction. Similarities and differences of the Raman scattering in II–VI and III–V or elemental (Si) semiconductor NCs are briefly analysed. Implementation of resonant conditions and application of infrared absorption analysis, complementary to the Raman spectroscopy—resulting in the observation of phonon modes ‘silent’ in conventional Raman scattering processes—are discussed. Furthermore, Raman spectroscopy is employed for fast and efficient assessment of the composition of matrix-embedded ternary II–VI nanocrystals, as well as more complicated multimode quaternary II–VI systems. Selective probing of electronic and vibrational spectra of different parts of heterogeneous NCs (such as core–shell systems) by tuning the excitation wavelength in resonant Raman scattering is considered. The analysis of phonon spectra is applied to the quantitative estimation of strain in the core and shell, and degree of interface intermixing, as well as to checking the surface oxidation. The above approaches and phenomena are further explored in more complex compound NCs beyond II–VI, such as CuInS2/ZnS. Recent results in the field of surface- and tip-enhanced Raman spectroscopy and surface-enhanced infrared absorption are analysed showing the perspectives of Raman spectroscopy as a tool for investigation of single-nanocrystal phonon spectra.
Determinant of Osteoporosis Preventive Behaviors among Perimenopausal Women: A Cross-Sectional Study to Explore the Role of Knowledge and Health Beliefs

Osteoporosis is a silent chronic disease, and many people did not discover it until they were diagnosed with a fracture. Therefore, regular scanning and appropriate Osteoporosis Preventive Behaviors (OPB) are the management cornerstone. OPB is strongly affected by personal knowledge and health beliefs. This study explores the role of knowledge and health beliefs as determinants of OPB among perimenopausal women. This cross-sectional study was performed on 1075 perimenopausal women in Najran City, Saudi Arabia, from January 2023 to March 2023. The data collection instrument is a self-reported questionnaire consisting of basic data, the OPB scale, an osteoporosis knowledge assessment tool, and the osteoporosis health belief scale. The current study results showed that approximately one-quarter (27.8%) of the study participants had high OPB with an overall mean of 20.83 ± 5.08 grade. The group practicing high OPB demonstrated a higher knowledge mean (11.37 ± 2.99) than the low OPB group (9.93 ± 3.51). In addition, all health beliefs constructs significantly differed among the low and high OPB groups (p ˂ 0.05). The participant’s age, occupational status, educational level, attendance of training courses, and history of bone fractures were significantly associated with high OPB. Osteoporosis knowledge, perceived susceptibility, perceived seriousness, exercises’ perceived benefits, and health motivations are positive predictors of high OPB (p ˂ 0.05). The study concluded that osteoporosis-related knowledge and health beliefs—especially perceived susceptibility, perceived seriousness, exercises’ perceived benefits, and health motivations—are positive predictors of high OPB. The health belief model can be an effective tool used to determine high-risk groups who practice low OPB and build need-based educational interventions.
A Bayesian approach to estimate uncertainty for full-waveform inversion using a priori information from depth migration

ABSTRACTFull-waveform inversion (FWI) enables us to obtain high-resolution subsurface images; however, estimating model uncertainties associated with this technique is still a challenging problem. We have used a Bayesian inference framework to estimate model uncertainties associated with FWI. The uncertainties were assessed based on an a posteriori covariance operator, evaluated at the maximum a posteriori model. For the prior distribution, we have used a spatially nonstationary covariance operator based on a plane-wave construction with local dips measured from migrated images. Preconditioned frequency-domain FWI was used to estimate the maximum a posteriori model. Efficient manipulation of the posterior covariance was based on a low-rank approximation of the data misfit Hessian preconditioned by the prior covariance operator. The strong decay of the singular values indicated that data were mostly informative about a low-dimensional subspace of model parameters. To reduce computational cost of the random.
Singular vector distribution of covariance matrices

We consider a class of covariance matrices of the form $Q=\Sigma^{\frac{1}{2}}XX^{*} \Sigma^{\frac{1}{2}},$ where $X=(x_{ij})$ is an $M \times N$ rectangle matrix consisting of i.i. d entries and $\Sigma$ is a diagonal positive definite matrix satisfying some regularity conditions. Assume $M$ is comparable to $N$, we prove that the distribution of the components of the singular vectors close to the edge singular values agree with that of Gaussian ensembles provided the first two moments of $x_{ij}$ coincide with the Gaussian random variables. For the singular vectors associated with the bulk singular values, the same conclusion holds if the first four moments of $x_{ij}$ match with those of Gaussian random variables.
Effect of Physical Properties on Mechanical Behaviors of Sandstone under Uniaxial and Triaxial Compressions

Mechanical properties of sandstone, such as compressive strength and young’s modulus, are commonly used in the design of geotechnical structures and numerical simulation of underground reservoirs using models such as the digital groundwater, equivalent porous medium, and Discrete Fracture Network (DFN) models. A better understanding of the mechanical behaviors of sandstone under different loading conditions is imperative when assessing the stability of geotechnical structures. This paper highlights the effect of the physical properties (i.e., porosity, mean grain size) and environmental conditions (i.e., water content and confining stress) on uniaxial compressive strength, triaxial compressive strength, and young’s modulus of sandstone. A series of uniaxial and triaxial compression experiments are conducted on sandstone formations from Wyoming. In addition, experimental data on sandstones from the literature are compiled and integrated into this study. Prediction equations for the compressive strengths and young’s modulus of sandstone are established based on commonly available physical properties and known environmental conditions. The results show that the mean Uniaxial Compressive Strength (UCS) decreases as the porosity, water content, and mean grain size increase. Furthermore, a predictive empirical relationship for the triaxial compressive strength is established under different confinements and porosity. The relationship suggests that the mean peak compressive strength increases at a higher confinement and decreases at a higher porosity. The results and recommendations provide a useful framework for evaluating the strength and deformation of most sandstone.
Effects of CeO2 nanoparticles on engine features, tribology behaviors, and environment

ABSTRACT Recently, scientists have developed a variety of approaches and techniques to boost the performance of engines and lower hazardous emissions. One method that has received a lot of interest is the employment of nanoparticles in fuels to address several drawbacks of fuels. Indeed, ceria (CeO2) nanoparticles are a common additive derived from fuel to lower particulate emissions discharged from diesel-powered engines. The preparation techniques and physicochemical features of biodiesel-originated fuels including CeO2 nanoparticles were thoroughly introduced in this review work. Also, the performance, combustion, and emission characteristics and tribological properties of diesel engines running on CeO2-included fuels were completely examined. Furthermore, this paper discussed the noticeable effects of CeO2 nanoparticles on human health and the environment in detail. Generally, adding CeO2 nanoparticles in terms of size ranging from 30–50 ppm into various biodiesel/diesel fuels showed positive impacts in terms of mitigating toxic emissions such as CO, HC, & smoke by the highest of about 94.98%, 91.16%, and 90.3% and improving diesel engine performance with a highest of about 31.25%, though their effects on the ecosystem and human health have been a contentious concern that needs handling in further investigations. The novelty of the current review is to provide comprehensive information on the ppm-specific use of CeO2 nanoparticles as a potential additive to blend with various biodiesel/diesel fuels aiming to improve various engine characteristics, tribological behavior, and environmental impact. GRAPHICAL ABSTRACT
Antibacterial and Antibiofilm Effects of Lactobacilli Strains against Clinical Isolates of Pseudomonas aeruginosa under Conditions Relevant to Cystic Fibrosis

Therapy of lung infections sustained by Pseudomonas aeruginosa in cystic fibrosis (CF) patients is challenging due to the presence of a sticky mucus in the airways and the ability of the bacterium to form biofilm, which exhibits increased antibiotic tolerance. A lung-directed bacteriotherapy through the airway administration of probiotics could represent an alternative approach to probiotic diet supplementation to improve the benefits and clinical outcomes of this kind of intervention in CF patients. This study aims to evaluate the ability of probiotic strains to grow in artificial sputum medium (ASM), mimicking the CF lung microenvironment, and to affect the planktonic and biofilm growth of CF clinical strains of P. aeruginosa in the same conditions. The results demonstrate that Lacticaseibacillus rhamnosus and Lactiplantibacillus plantarum (LP) can grow in ASM. LP inhibited the planktonic growth of P. aeruginosa, while both lactobacilli reduced the pre-formed biofilm of P. aeruginosa. Interestingly, LP was demonstrated to reduce the amount of polysaccharides in the extracellular matrix of P. aeruginosa biofilms and to potentiate the antibiofilm effects of tobramycin. Overall, the results indicated that LP is a promising candidate as an adjuvant in the antimicrobial therapy of P. aeruginosa infections in CF patients.
Convergence Rates of Multivariate Regression Estimators with Errors-In-Variables

ABSTRACT This paper studies the regression estimation with errors-in-variables. We first extend Meister’s theorems (Meister, 2009. Deconvolution Problems in Nonparametric Statistics. Springer, Berlin) from one to multi-dimensional setting, when a noise density has no zeros in the Fourier domain. Then motivated by the work of Delaigle and Meister (Delaigle, Meister, 2011. Nonparametric function estimation under Fourier-oscillating noise. Statistica Sinica 21, 1065–1092), we show a desired convergence rate of a kernel estimator for Fourier-oscillating noises. Finally, two technical conditions are removed, when a wavelet estimator is used.
Phase-shifter-less Vortex Electromagnetic Wave Generation Technology with Tunable Topological Charge/Steering Angle under Random Initial Phase Condition of Phase-locked Source

This paper demonstrates how to implement a vortex electromagnetic wave generation system with beam steering using only delay lines as phase-shifting elements. The system is based on uniform circular array and phased array technology. A detailed theoretical derivation is presented, which yields an input frequency matrix corresponding to each target case. Furthermore, considering the random initial phase problem of the actual phase-locked source, the above scheme is further improved in this paper. By cleverly setting the circuit structure, the influence of the initial phase inconsistency on the phase control system is filtered out. The performance is verified by analytical calculations and full-wave electromagnetic simulations, which are in good agreement with the proposed theory. The scheme proposed in this paper can completely get rid of the phase shifter and realize the free adjustment of the topological charge number/beam steering angle. The adjustment accuracy depends on the tuning accuracy of the phase-locked source, which can achieved an accuracy over 1Hz at a cost of less than six dollars, which makes it an interesting and flexible low-cost vortex electromagnetic wave generation scheme.
Day-to-day fluctuations of fatigue severity in individuals with knee osteoarthritis: an ecological momentary assessment approach

Abstract Objective The variable course of fatigue adds to the disease burden of patients with OA yet it has been poorly understood. This study aimed to describe within-person fluctuations of fatigue severity and explore its associations with pain, positive affect, negative affect, sleep, and perceived exertion of physical activity. Methods Individuals with chronic knee pain or a clinical diagnosis of knee OA ≥40 years of age completed daily assessments about fatigue, pain, positive affect, negative affect, sleep, perceived exertion of physical activity (numeric rating scale 0–10), and overwhelming fatigue (yes/no) on a smartphone over 14 days. Within-person fluctuations of fatigue severity were described by the probability of acute changes (PACs) and s.d. s. Associations with pain, positive affect, negative affect, sleep, and perceived exertion of physical activity were explored using multilevel models. Results Forty-nine individuals were included (mean age 63.4 years; 82% female). PACs and s.d. s of within-person daily fatigue fluctuations ranged from 0.00 to 0.80 and 0.35 to 2.95, respectively. Within-person associations of fatigue severity were moderate for positive affect [β = −0.57 (95% CI −0.67, −0.47)], weak for pain [β = 0.41 (95% CI 0.29, 0.53)] and negative affect [β = 0.40 (95% CI 0.21, 0.58)], and negligible for sleep [β = −0.13 (95% CI −0.18, −0.08)] and perceived exertion of physical activity [β = 0.18 (95% CI 0.09, 0.26)]. Conclusion Some individuals showed almost stable day-to-day levels of fatigue severity, whereas others experienced a substantial number of clinically relevant fluctuations. To reduce the burden of daily fatigue fluctuations, our results suggest that pain, positive and negative affect rather than sleep and perceived exertion of physical activity should be considered as potential targets.
Beta Caryophyllene-Loaded Nanostructured Lipid Carriers for Topical Management of Skin Disorders: Statistical Optimization, In Vitro and Dermatokinetic Evaluation

This work aimed to overcome the disadvantages of the oral administration of beta-caryophyllene and boost efficiency by developing a nanostructured lipid carrier for topical administration of the drug in skin disorders. The heat emulsification method was utilized to produce beta-caryophyllene-loaded nanostructured lipid carriers. The newly created formulation was examined for its particle size, entrapment efficiency, and zeta potential after being improved using the Box–Behnken Design. The chosen formulation underwent tests to determine its ex vivo skin retention, dermatokinetic, in vitro release, antioxidant, and confocal laser scanning microscopy study. The findings of the characterization of the nanostructured lipid carriers demonstrated that the particles had a spherical form and a size of 210.86 nm (0.263 polydispersity index). The entrapment efficiency was determined to be 86.74%, and the zeta potential was measured to be −26.97 mV. The in vitro release investigation showed that nanostructure lipid carriers were capable of releasing regulated amounts of beta-caryophyllene for up to 24 hrs. In comparison to the traditional gel formulation, the ex vivo investigation demonstrated a 1.94-fold increase in the skin’s capacity to retain the substance. According to the findings of the study, nanostructure lipid carriers loaded with beta-caryophyllene have the potential to be investigated for use as a topical administration method in skin disorders with enhanced skin retention and effectiveness.
Multimodal Reaction: Information Modulation for Cross-Modal Representation Learning

In multimodal machine learning, proper handling of cross-modal information is essential for obtaining an ideal joint embedding. Despite the progress made by recent fusion strategies, we hold that before the fusion stage, the unimodal representation inevitably contains noise that may hinder the correct learning of cross-modal dynamics and affect multimodal fusion. It is worthwhile to investigate how the information is being utilized and how to make the full use of it. Rethinking the process of leveraging multiple modalities for the joint embedding, multimodal learning can be regarded as a chemical reaction process and two steps may benefit learning: 1) purification to filter impurity, and 2) catalyst to facilitate learning. In this paper, we propose a Multimodal Information Modulation (MIM) learning framework to modulate the contribution and utilization of the cross-modal information, which identifies and handles the ‘impurity’ and ‘catalyst’ in multimodal learning. Specifically, a Unimodal Purification Network (UPN) is proposed to identify and explicitly filter out the impurity within each modality before fusion, which reduces the possibility of learning incorrect cross-modal dynamics. Besides, based on the intuition that useful information has the potential in the guidance of model updating, it plays a role to facilitate learning, which is achieved by the design of the Knowledge Guidance Scheme (KGS) considering both the intra- and inter-modal scenarios. Different to a majority of works that emphasize the role of useful information in the fusion and inference stage, KGS considers its potential role in assisting the representation learning of weaker components. Besides, it fully considers the modality dominance problem and sample variations for optimization. In short, MIM manages to modulate the useless/useful information to minimize/emphasize their contribution. Experimental results verify the effectiveness of the proposed method.
The impact of an error in selection the pushbacks in the long-term planning of the open pit production on project quality, case study: Open pit Veliki Krivelj, Bor, Serbia

Today, there is a large number of software in which various mathematical algorithms for optimization the open pits are implemented. However, the importance of experience of the mining engineers in planning is still crucial for the quality of mining projects. Proper selection of the pushbacks is one of the most important planning steps in a long-term planning of production at the open pit. Therefore, the mistakes that occur in this planning step have a great impact on the project quality. Using the example of the Veliki Krivelj project, this paper presents the importance of correct selection the Pushbacks from an aspect of satisfying the practical geometric mining constraints.