Miracle-dz/UniFAR-FTUs huggingface dataset:
Alternative results for option pricing and implied volatility in jump-diffusion models using Mellin transforms

In this article, we use Mellin transforms to derive alternative results for option pricing and implied volatility estimation when the underlying asset price is governed by jump-diffusion dynamics. The current well known results are restrictive since the jump is assumed to follow a predetermined distribution (e.g., lognormal or double exponential). However, the results we present are general since we do not specify a particular jump-diffusion model within the derivations. In particular, we construct and derive an exact solution to the option pricing problem in a general jump-diffusion framework via Mellin transforms. This approach of Mellin transforms is further extended to derive a Dupire-like partial integro-differential equation, which ultimately yields an implied volatility estimator for assets subjected to instantaneous jumps in the price. Numerical simulations are provided to show the accuracy of the estimator.
A Novel High-Precision Range Estimation Method Based on Phase of Wideband Radar Echo

High-precision parameter estimation is crucial for micromotion feature acquisitions. A method of high-precision range estimation based on phase of wideband radar echo is proposed in this paper. After the proposed processing, unwrapped signal phases without any ambiguity can be obtained to calculate the relative range of the target. No constraint condition for phase ambiguity resolution is imposed on the proposed method, which means that it could still work well in low signal-to-noise ratio situations. Cramér–Rao lower bound for the root-mean-squared error of the range estimation is derived in analytical expression. Results of several simulations and experiment with FEKO generated data are presented to show the effectiveness and antinoise performance of the proposed method.
A Confirmatory and an Exploratory Factor Analysis of the Cohen-Mansfield Agitation Inventory (CMAI) in a European Case Series of Patients with Dementia: Results from the RECage Study

Background: One of the most widely used instruments for assessing agitation in dementia patients is the Cohen-Mansfield Agitation Inventory (CMAI), nevertheless no global score has been proposed. The aim of this study is: (a) to conduct a confirmatory (CFA) and exploratory factor analysis (EFA) of CMAI on people with dementia and Psychological and Behavioral Symptoms (BPSD), and (b) to propose an alternative structure, based on clinical criteria including all CMAI items. Methods: Confirmatory and exploratory factor analyses were carried out on the CMAI 29 items administered at baseline to 505 patients with dementia (PwD) and BPSD enrolled in the international observational RECage study. Results: The three-factor structure has not been confirmed by the CFA, whilst the EFA was carried out respectively on 25 items disregarding 4 items with a prevalence ≤5% and then on 20 items disregarding 9 items with a prevalence ≤10%. The four-factor structure explaining 56% of the variance comprised Physically Aggressive behavior, Verbally Aggressive behavior, Physically non-aggressive behavior, and Physically and verbally aggressive behavior. Conclusions: A new grouping of all items according to a clinical criterion is proposed, allowing for a more sensible evaluation of the symptoms leading to better differentiation.
AdaHRBF v1.0: gradient-adaptive Hermite–Birkhoff radial basis function interpolants for three-dimensional stratigraphic implicit modeling

Abstract. Three-dimensional (3D) stratigraphic modeling is capable of modeling the shape, topology, and other properties of strata in a digitalized manner. The implicit modeling approach is becoming the mainstream approach for 3D stratigraphic modeling, which incorporates both the off-contact strike and dip directions and the on-contact occurrence information of stratigraphic interface to estimate the stratigraphic potential field (SPF) to represent the 3D architectures of strata. However, the magnitudes of the SPF gradient controlling the variation trend of SPF values cannot be directly derived from the known stratigraphic attribute or strike and dip data. In this paper, we propose a Hermite–Birkhoff radial basis function (HRBF) formulation, AdaHRBF, with an adaptive gradient magnitude for continuous 3D SPF modeling of multiple stratigraphic interfaces. In the linear system of HRBF interpolants constrained by the scattered on-contact attribute points and off-contact strike and dip points of a set of strata in 3D space, we add a novel optimizing term to iteratively obtain the optimized gradient magnitude. The case study shows that the HRBF interpolants can consistently and accurately establish multiple stratigraphic interfaces and fully express the internal stratigraphic attribute and orientation. To ensure harmony of the variation in stratigraphic thickness, we adopt the relative burial depth of the stratigraphic interface to the Quaternary as the SPF attribute value. In addition, the proposed stratigraphic-potential-field modeling by HRBF interpolants can provide a suitable basic model for subsequent geosciences' numerical simulation.
A Comparative Analysis of Electricity Companies’ Sustainability Reporting in Australia and India

This study compares the sustainability reporting efforts by electricity companies in developed (Australia) and emerging (India) economies. Using the GRI G4 sector-specific guidelines for electric utilities on the 2018/2019 annual reports, stand-alone sustainability reports, corporate social responsibility (CSR) reports, and corporate websites, the study finds that the compliance rates with the categories of sustainability reporting in the Indian electricity companies are far low compare to the Australian electricity companies. Overall, the disclosure is low in both countries as the highest compliance rate in Australia is 63.7% and the lowest compliance rate is 43.6%, while in the case of India, the highest compliance rate is 45.7% and the lowest compliance rate is 28.5%. Considering that electric utilities provide essential services to society and have a significant influence on sustainable development, such a low disclosure, particularly by Indian companies, could lead the efforts to gain stakeholders’ legitimacy and sustainable development to crumble.
Subcritical transition scenarios via linear and nonlinear localized optimal perturbations in plane Poiseuille flow

Subcritical transition in plane Poiseuille flow is investigated by means of a Lagrange-multiplier direct-adjoint optimization procedure with the aim of finding localized three-dimensional perturbations optimally growing in a given time interval (target time). Space localization of these optimal perturbations (OPs) is achieved by choosing as objective function either a p-norm (with p ≫ 1 ) of the perturbation energy density in a linear framework; or the classical (1-norm) perturbation energy, including nonlinear effects. This work aims at analyzing the structure of linear and nonlinear localized OPs for Poiseuille flow, and comparing their transition thresholds and scenarios. The nonlinear optimization approach provides three types of solutions: a weakly nonlinear, a hairpin-like and a highly nonlinear optimal perturbation, depending on the value of the initial energy and the target time. The former shows localization only in the wall-normal direction, whereas the latter appears much more localized and breaks the spanwise symmetry found at lower target times. Both solutions show spanwise inclined vortices and large values of the streamwise component of velocity already at the initial time. On the other hand, p-norm optimal perturbations, although being strongly localized in space, keep a shape similar to linear 1-norm optimal perturbations, showing streamwise-aligned vortices characterized by low values of the streamwise velocity component. When used for initializing direct numerical simulations, in most of the cases nonlinear OPs provide the most efficient route to transition in terms of time to transition and initial energy, even when they are less localized in space than the p-norm OP. The p-norm OP follows a transition path similar to the oblique transition scenario, with slightly oscillating streaks which saturate and eventually experience secondary instability. On the other hand, the nonlinear OP rapidly forms large-amplitude bent streaks and skips the phases of streak saturation, providing a contemporary growth of all of the velocity components due to strong nonlinear coupling.
Leading Edge Radius Effects on VAWT Performance

Numerous studies have been conducted to investigate effect of blade geometry of vertical axis wind turbine performance. Most of the evaluations have focused on the airfoil series and airfoil geometry parameters such as thickness and camber of the airfoil. Few studies have examined the effect of other blade geometry parameters on the vertical axis wind turbine performance. In the present study, the effect of geometric change in leading-edge radius (LER) of a vertical axis wind turbine performance has been numerically studied. Hence, modified NACA 0021 airfoil profiles were created using the geometric method (CST). Then, the flow behavior around a Darrieus vertical axis wind turbine was simulated under the influence of the reduction and set-up coefficients of the leading-edge radius at a constant wind speed of 9 m/s and a tip speed ratio of 1.5 to 3.5 using the computational fluid dynamics. Additionally, the effects of the examined parameter (leading-edge radius) on fluid flow and aerodynamic performance coefficients, including the coefficients of power and torque, were investigated. The results indicated that the leading-edge radius affected the near wake flow of the turbine, and the optimization of leading-edge radius parameter controls the dynamic stall and reduces the formation of a vortex. Finally, the optimization of LER revealed that at 20% reduction in the LER the performance of the turbine at tip speed ratio of 1.5 was increased by more than 50%. This reinforces the self-starting capability of a Darrieus wind turbine.
Defining and selecting characteristic values of geotechnical parameters for designs to Eurocode 7

ABSTRACT Recent geotechnical design codes (such as Eurocode 7) aim to achieve geotechnical designs with an appropriate target reliability by applying partial factors to characteristic parameter values. Development in Eurocode 7 of the definition and selection of the characteristic values is traced. A significant development occurred with the definition of the characteristic value as a cautious estimate of the value affecting the occurrence of the limit state. Statistical equations to select characteristic values are presented, including one proposed for the revised of Eurocode 7.An alternative equation reduces the amount of subjective judgement and is more likely to achieve the target reliability.
Poloidal asymmetry in the narrow heat flux feature in the TCV scrape-off layer

Heat flux profiles inferred from a reciprocating probe at the outer midplane of the TCV tokamak during inner wall limited discharges feature radial fall-off lengths that shorten near the last closed flux surface (LCFS) consistent with the so-called narrow feature. The narrow feature is significantly wider on the outboard side compared with that measured on the inner wall by infrared thermography, so it is difficult to discern from the main scrape-off layer feature. After small shifts were applied for alignment, the fraction of the power contained in the narrow feature matches between inboard and outboard measurements, and they scale together with plasma current Ip, suggesting that we are observing the same phenomenon. The outboard side fall-off length within the narrow feature is found to scale closely with the radial correlation length of the edge turbulence as expected if the narrow feature arises due to radially sheared E × B flows. This is found to hold true even for cases where the narrow feature is .
Confocal Microscopy Investigations of Biopolymeric PLGA Nanoparticle Uptake in Arabidopsis thaliana L. Cultured Cells and Plantlet Roots

To date, most endocytosis studies in plant cells have focused on clathrin-dependent endocytosis, while limited evidence is available on clathrin-independent pathways. Since dynamin a is a key protein both in clathrin-mediated endocytosis and in clathrin-independent endocytic processes, this study investigated its role in the uptake of poly-(lactic-co-glycolic) acid (PLGA) nanoparticles (NPs). The experiments were performed on cultured cells and roots of Arabidopsis thaliana. Dynasore was used to inhibit the activity of dynamin-like proteins to investigate whether PLGA NPs enter plant cells through a dynamin-like-dependent or dynamin-like-independent endocytic pathway. Observations were performed by confocal microscopy using a fluorescent probe, coumarin 6, loaded in PLGA NPs. The results showed that both cells and roots of A. thaliana rapidly take up PLGA NPs. Dynasore was administered at different concentrations and exposure times in order to identify the effective ones for inhibitory activity. Treatments with dynasore did not prevent the NPs uptake, as revealed by the presence of fluorescence emission detected in the cytoplasm. At the highest concentration and the longest exposure time to dynasore, the fluorescence of NPs was not visible due to cell death. Thus, the results suggest that, because the NPs’ uptake is unaffected by dynasore exposure, NPs can enter cells and roots by following a dynamin-like-independent endocytic pathway.
Apparent effect of range size and fruit colour on palm diversification may be spurious

Fruit selection by animal dispersers with different mobility directly impacts plant geographical range size, which, in turn, may impact plant diversification. Here, we examine the interaction between fruit colour, range size and diversification rate in palms by testing two hypotheses: (1) species with fruit colours attractive to birds have larger range sizes due to high dispersal ability and (2) disperser mobility affects whether small or large range size has higher diversification, and intermediate range size is expected to lead to the highest diversification rate regardless of disperser.
Advanced machine learning approach for automatic crack detection and classification in concrete surfaces

Nowadays, one of the most commonly used construction materials is concrete. As a building material, concrete can be deformed under various conditions and cracks can form on this material. Depending on their condition and position, these cracks can pose serious hazards. Therefore, the automatic detection and classification of these cracks becomes a very important issue. The detection process, which is usually performed by manual observation, is labor intensive. In this research, a new machine learning method is proposed for automatic detection of cracks in concrete surface. The proposed method utilizes DenseNet201 based deep feature extraction approach. In addition, the model includes ReliefF-based feature selection and SVM-based classification phases. SDNET2018, an open access dataset, is used to test the proposed model. Both holdout cross validation and 10-fold cross validation techniques were applied for validation on this dataset. As a result of the test procedures, 93% classification success was achieved for 10-fold CV. The results obtained with the test procedures prove the success of the proposed method in automatic crack classification.
k-Means Cluster-based Random Undersampling and Meta-Learning Approach for Village Development Status Classification

There is a significant imbalanced class in the village development index (called IDM - Indeks Desa Membangun) dataset, marked by the number of self-supporting classes more than the disadvantaged class. The traditional classifiers are able to achieve high accuracy (ACC) by training all cases of the majority class but forsaking the minority class, so that possible for the classification results to be biased. In this study, a random under-sampling technique was employed based on k-means cluster (KMC) and a meta-learning approach to improving ACC of the village status classification model. Furthermore, the AdaBoost and Random Forest were used as meta technique and base learner, respectively. The proposed model has been evaluated using the area under the curve (AUC), and experimental results showed that it yielded excellent performance compared to the prior studies with the AUC, ACC, precision (PR), recall (RC), and g-mean (Gm) values of 95.50%, 95.52%, 95.5%, 95.5%, and 92.95%, respectively. Similarly, the result of the t-test also showed the proposed model yielded excellent performance compared to previous studies. It can be concluded that the AdaBoost algorithm improved misclassification and changed the distribution of data loss function in random forests. It indicates that the proposed model effectively deals with imbalanced classes in the village development status classification model.
The Health Sector in Jordan: Effectiveness and Efficiency

This paper compares a homogeneous group of countries in terms of capacity and technology, where we picked income as indicator for capacity and technology. We study the case of the Hashemite Kingdom of Jordan. We apply radical data envelopment analysis to 36 middle income countries where we calculate constant returns to scale technical efficiency and variable returns to scale technical efficiency to show the health care sector efficiency in Jordan. Using different factors for input first we studied healthcare expenditure per capita then as percent of GDP and public expenditure as percent of GDP and private as percent of GDP, and last was the number of beds per 1000 population and physicians per 1000 population all to the same output life expectancy. The results show that there is inefficiency in health care expenditure. The inefficiency mainly is shown by two major findings, first the lack of utilization of resources. Secondly, the public-sector inefficiency. The output is justifiable for many challenges faced the health sector in the year of the study one of which is the Syrian refuges crisis. We shed light on factors causing the inefficiency where modifications could yield substantial efficiency gains. As for the mix between public and private sectors and the quality and utilization and distribution of the real resources, nevertheless adding health economists to the management staff for there is a managerial inefficiency.
Modified extended median test

This paper proposes a modified extended median test that adjusts for the effects of any possible ties in the specific data. The proposed method is illustrated with data. A comparison with the extended median test suggests that the proposed method is at least as powerful as the extended median test.In this study, the proposed extended median test presents an example indicating that the proposed modified extended median test is more powerful than the ordinary extended median test. Key words: Median test, tied observation, chi-square, P-value, χ2 distribution.
Numerical Analysis of Trampoline Effect in Extreme Ground Motion

Very large vertical surface acceleration of nearly four times gravity was measured at a strong motion observation station in Iwate Prefecture during the 2008 Iwate-Miyagi Inland, Japan, earthquake (Mw 6.9). The station is located about 3 km southwest of the epicenter and equipped with three-component accelerometers, installed at both the free surface and the bottom of a 260-m borehole. The wave form of the vertical acceleration shows a clearly asymmetric form with large amplitude in the upward direction. Aoi et al. (2008) reported and qualitatively explained the mechanism of this phenomenon by the analogy of bouncing a piece of matter on a trampoline, and thus they called it the “trampoline effect. ” To simulate this recently discovered nonlinear behavior of the surface ground motion, numerical analysis with a finite-element method has been employed with parameters derived from the borehole data at the station. The analysis successfully simulates the asymmetric vertical motion. Results indicate that the asymmetric motion may be characterized by the existence of a lower bound of negative acceleration, which in most cases corresponds to the acceleration of gravity, and high positive pulses caused by the compression stress of the disturbed surface ground material.
Exploiting random perturbations to defend against adversarial attacks

Adversarial examples are deliberately crafted data points which aim to induce errors in machine learning models. This phenomenon has gained much attention recently, especially in the field of image classification, where many methods have been proposed to generate such malicious examples. In this paper we focus on defending a trained model against such attacks by introducing randomness to its inputs.
A Discrete Coarea-type Formula for the Mumford-Shah Functional in Dimension One

We study the convex lift of Mumford-Shah type functionals in the space of rectifiable currents and we prove a generalized coarea formula in dimension one, for finite linear combinations of SBV graphs. We use this result to prove the equivalence between the minimum problems for the Mumford-Shah functional and the lifted one and, as a consequence, we obtain a weak existence result for calibrations in one dimension.
A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings

Remaining useful life (RUL) prediction of rolling element bearings plays a pivotal role in reducing costly unplanned maintenance and increasing the reliability, availability, and safety of machines. This paper proposes a hybrid prognostics approach for RUL prediction of rolling element bearings. First, degradation data of bearings are sparsely represented using relevance vector machine regressions with different kernel parameters. Then, exponential degradation models coupled with the Fréchet distance are employed to estimate the RUL adaptively. The proposed approach is evaluated using the vibration data from accelerated degradation tests of rolling element bearings and the public PRONOSTIA bearing datasets. Experimental results demonstrate the effectiveness of the proposed approach in improving the accuracy and convergence of RUL prediction of rolling element bearings.
Design and analysis of all-dielectric subwavelength focusing flat lens

In this letter, we numerically designed and experimentally demonstrated a compact photonic structure for the subwavelength focusing of light using all-dielectric absorption-free and nonmagnetic scattering objects distributed in an air medium. In order to design the subwavelength focusing flat lens, an evolutionary algorithm is combined with the finite-difference time-domain method for determining the locations of cylindrical scatterers. During the multi-objective optimization process, a specific objective function is defined to reduce the full width at half maximum (FWHM) and diminish side lobe level (SLL) values of light at the focal point. The time-domain response of the optimized flat lens exhibits subwavelength light focusing with an FWHM value of 0. 19λ and an SLL value of 0.23, where λ denotes the operating wavelength of light. Experimental analysis of the proposed flat lens is conducted in a microwave regime and findings exactly verify the numerical results with an FWHM of 0. 192λ and an SLL value of 0.311 at the operating frequency of 5.42 GHz. Moreover, the designed flat lens provides a broadband subwavelength focusing effect with a 9% bandwidth covering frequency range of 5.10 GHz–5.58 GHz, where corresponding FWHM values remain under 0. 21λ. Also, it is important to note that the designed flat lens structure performs a line focusing effect. Possible applications of the designed structure in telecom wavelengths are speculated upon for future perspectives. Namely, the designed structure can perform well in photonic integrated circuits for different fields of applications such as high efficiency light coupling, imaging and optical microscopy, with its compact size and ability for strong focusing.