Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Measurement of the 8 B Solar Neutrino Energy Spectrum at the Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory (SNO) has successfully demonstrated the phenomenon of neutrino flavour transformation in the flux of neutrinos from the Sun. Its unique use of heavy water as a detection medium allowed a measurement of both the total active solar neutrino flux, via the Neutral Current (NC) interaction, and the pure electron neutrino component via the Charged Current (CC) interaction. This thesis presents the most detailed analysis of the CC spectrum using the combined data from the first two phases of the experiment: the pure D2O and the salt phases. The neutrino fluxes and spectra have been extracted down to an effective electron kinetic energy threshold of 3.5 MeV, lower than that achieved by any previous water Čerenkov experiment. The significant improvements made in the evaluation of the systematic uncertainties result in the most precise measurement of the total active solar neutrino flux ever reported: Φ NC = 5.191 +0.156 −0.155(stat) +0.132 −0.099(syst) × 10 cm s which is in good agreement with the flux predicted by the Standard Solar Model. The ratio of the CC and NC fluxes is found to be: Φ CC Φ NC = 0.312 +0.013 −0.013(stat) +0.011 −0.010(syst) which is a measure of the fraction of electron neutrinos in the total active neutrino flux from the Sun. The strong suppression observed is evidence for matter enhanced oscillations occurring in the Sun, as predicted by the MSW effect. In addition to the observed overall νe flux suppression, a two-dimensional test of the MSW prediction for the spectral shape has been performed in order to extract the most likely values for the neutrino oscillation parameters. The resulting values are: ∆m12 = 6.03 × 10 eV tan θ12 = 0.42 with reduced uncertainties in the value of tan θ12 in comparison to previous SNO results. The addition of data from other experiments, such as KamLAND, should enable the most accurate determination of both these mixing parameters. “Though this be madness, yet there is method in’t” Hamlet 2.2. 193-206 – W. Shakespeare
Directional Torsion Sensor Based on a Two-Core Fiber with a Helical Structure

A fiber-optic torsion sensor based on a helical two-core fiber (HTCF) is proposed and experimentally demonstrated for simultaneously measuring torsion angle and torsion direction. The sensor consists of a segment of HTCF and two single-mode fibers (SMFs) forming a Mach–Zehnder interferometer (MZI). The helical structure is implemented by pre-twisting a 1 cm long two-core fiber (TCF). The performance of the sensor with pre-twisted angles of 180°, 360°, and 540° is experimentally analyzed. The results show that the sensor can realize the angular measurement and effectively distinguish the torsion direction. It is worth noting that the sensor has maximum sensitivity when the pre-twist angle is 180 degrees. The obtained wavelength sensitivities of torsion and temperature are 0.242 nm/(rad/m) and 32 pm/°C, respectively. The sensor has the advantages of easy fabrication, low cost, compact structure, and high sensitivity, which is expected to yield potential applications in fields where both torsion angle and direction measurements are required.
Citizenship education under authoritarian Islamic nationalism: an exploration of teachers’ conceptions of citizenship in Turkey

ABSTRACT This study explores a group of social studies teachers’ conceptions of citizenship by taking into consideration the country’s increasingly authoritarian political culture. It offers an analysis of semi-structured interviews carried out with 20 teachers working at state middle schools in a relatively secular city. The study found that the majority of the teachers are subscribed to a non-democratic conception of citizenship that prioritizes an uncritical loyalty to the nation, inculcates passive compliance, relies on a pro-Muslim notion of human rights, and makes little room for political issues discussion. Despite that, some teachers seem to develop oppositional discourses and seek ways to claim their agencies. The study concludes that the authoritarian Islamic nationalism in power has intensified the ethno-religiously nationalist, statist, and duty-centric aspects of citizenship education (CE). Some teachers’ explicit emphasis on pro-Islamic and anti-western discourses and almost all teachers’ explicit concern to stay away from politics emerge as novel characteristics that are consistent with the dictates of Turkey’s authoritarian regime. It seems authoritarian populist nationalism redresses citizenship as an exclusionary notion grounded in race, ethnicity, religion, and civilizational claims. Insights from this research may help the advocates keep CE supportive of democratic values under authoritarian conditions.
Combined field integral equation formulation for inhomogeneous two- and three-dimensional bodies: the junction problem

A combined field integral equation (CFIE) formulation is presented for two- and three-dimensional bodies having discrete dielectric and conducting regions. A three-dimensional case is restricted to bodies of revolution (BORs). The two-dimensional case is analogous to the BOR case when the Fourier mode number is zero. The method of moments (MM) is used to solve the CFIE in terms of two integral operators. It is shown that the CFIE formulation yields accurate answers for scattering problems where the scatterer may be internally resonant. The CFIE results were validated using Mie series results and measured data. The junction problem associated with the CFIE-based formulation is explicated, and several geometries with multiple junctions are used to validate the general CFIE formulation. A number of configurations are tested where the penetrable region consisted of a free-space coating. Extensive numerical studies have shown that such limiting cases are sensitive indicators of the stability of MM solutions and allow direct comparison of different configurations. >
Television signal deghosting by noncausal recursive filtering

A signal corrupted by a ghosting channel can be deghosted by the appropriate inverse system. If the channel is nonminimum-phase, the inverse system has a noncausal impulse response. It is pointed out that the inverse system can be implemented with recursive digital filters, provided there are system elements to time-flip the signal. Such noncausal recursive filtering has advantages over strictly causal recursive filtering in its ability to equalize the phase as well as the magnitude response of the channel. It also has advantages over nonrecursive nonminimum-phase deghosting in that it requires much lower filter order. <<ETX>>
Optimum Designs in Regression Problems

0. Summary. Extending the results of Kiefer and Wolfowitz [10], [11], methods are obtained for characterizing and computing optimum regression designs in various settings, and examples are given where D-optimum designs are computed. In Section 1 we introduce the main definitions and notation which will be used in the paper, and discuss briefly the roles of invariance, randomization, number of points at which observations are taken, and nonlinearity of the model, in our results. In Section 2 we prove the main theoretical results. We are concerned with the estimation of s out of the k parameters, extending an approach developed in [10] and [11] in the case s = k. There is no direct way of ascertaining whether or not a given design t* is D-optimum for (minimizes the generalized variance of the best linear estimators of) the s chosen parameters, and Theorems 1 and 2 provide algorithms for determining whether or not a given t* is D-optimum. If all k parameters are estimable under t*, we can use (2.7) to decide whether t* is D-optimum, while if not all k parameters are estimable we must use the somewhat more complicated condition (2.17) (of which part (a) or (b) is necessary for optimality, while (a), (c), or (d) is sufficient). An addition to Theorem 2 near the end of Section 3 provides assistance in using (2.17) (b). Theorem 3 of Section 2 characterizes the set of information matrices of the D-optimum designs. In Section 3 we give a geometric interpretation of the results of Section 2, and compare the present approach with that of [10]. In the case s = k, the present approach reduces to that of Section 5 of [10] and of [11]. When 1 < s < k, we obtain an algorithm which differs from that of Section 4 of [10] and which appears to be computationally easier to use. When s = 1, the results of the present paper are shown to reduce to those of Section 2 of [10]; in particular, we obtain the game-theoretic results without using the game-theoretic machinery of [10]. In Section 4 we determine D-optimum designs for the problems of quadratic regression on a q-cube and polynomial regression on a real interval with 1
Anisotropic absorption and emission of bulk (11̄00) AlN

The intrinsic anisotropic optical properties of wurtzite AlN are investigated in absorption and emission. Full access to the anisotropy of the optical response of the hexagonal material is obtained by investigating the (1100) plane of a high-quality bulk crystal allowing electric field E polarization perpendicular (E ⊥ c) and parallel (E ‖ c) to the optical axis c. Spectroscopic ellipsometry yields the ordinary (e⊥) and extraordinary (e‖) dielectric functions (DFs) from 0.58 up to 20 eV. The comparison of the experimental data with recently calculated DFs demonstrates that Coulomb interaction has a strong impact not only on the spectral dependence around the fundamental absorption edge but also on the high-energy features usually discussed in terms of van Hove singularities. The fits of the second-order derivatives of e‖ and e⊥ provide the transition energies for the main features in this range. The DFs close to the fundamental absorption edge, dominated by free excitons, exciton-phonon complexes, and the exciton continuum, are independently confirmed by reflectivity and synchrotron-based photoluminescence excitation studies. Values for the band gaps, the crystal field ( cf = −221 ± 2 meV), and spin-orbit splittings ( so = 13 ± 2 meV) are obtained. Furthermore, we obtain accurate values for the static dielectric constants of eS⊥ = 7.65 and eS‖ = 9.21, entering, e.g., the calculations of exciton binding energies. Photoluminescence is used to investigate the emission properties of the same sample.
Theory and three‐dimensional simulation of light filamentation in laser‐produced plasma

A desire to interpret recent experiments on filamentation with and without beam‐smoothing techniques led to the development of a three‐dimensional fluid model that includes the effects of nonlocal electron transport and kinetic ion damping of the acoustic waves. The damping of the electron‐temperature perturbations that drive thermal filamentation by nonlocal electron conduction, valid in the diffusive limit, is supplemented in the present model by electron Landau damping in the collisionless limit when the wavelength of the perturbation is much less than the electron–ion scattering mean‐free path. In this collisionless limit, Landau damping of the ‘‘temperature’’ fluctuations makes ponderomotive forces universally more important than thermal forces. Simulations in plasmas of current interest illustrate the relative importance of thermal and ponderomotive forces for strongly modulated laser beams. Although thermal forces may initiate filamentation, the most intense filaments are associated with ponderomot.
Robust signal parameter estimation in the presence of array perturbations

Signal parameter estimators which are less sensitive to perturbations in the array manifold are presented. A parametrized stochastic model for the array uncertainties is introduced. The unknown array parameters can include the individual gain and phase responses of the sensors as well as their positions. Based on this model, a maximum a posteriori (MAP) estimator is formulated. This results in a fairly complex optimization problem which is computationally expensive. The MAP estimator is simplified by exploiting properties of the weighted subspace fitting method. An approximate method that further reduces the complexity is also presented, assuming small array perturbations. A compact expression for the MAP Cramer-Rao bound (CRB) on the signal and array parameter estimates is derived. A simulation study indicates that the proposed robust estimation procedures achieve the MAP-CRB even for moderate sample sizes. <<ETX>>
Effectiveness of Radiomic ZOT Features in the Automated Discrimination of Oncocytoma from Clear Cell Renal Cancer

Background: Benign renal tumors, such as renal oncocytoma (RO), can be erroneously diagnosed as malignant renal cell carcinomas (RCC), because of their similar imaging features. Computer-aided systems leveraging radiomic features can be used to better discriminate benign renal tumors from the malignant ones. The purpose of this work was to build a machine learning model to distinguish RO from clear cell RCC (ccRCC). Method: We collected CT images of 77 patients, with 30 cases of RO (39%) and 47 cases of ccRCC (61%). Radiomic features were extracted both from the tumor volumes identified by the clinicians and from the tumor’s zone of transition (ZOT). We used a genetic algorithm to perform feature selection, identifying the most descriptive set of features for the tumor classification. We built a decision tree classifier to distinguish between ROs and ccRCCs. We proposed two versions of the pipeline: in the first one, the feature selection was performed before the splitting of the data, while in the second one, the feature selection was performed after, i.e., on the training data only. We evaluated the efficiency of the two pipelines in cancer classification. Results: The ZOT features were found to be the most predictive by the genetic algorithm. The pipeline with the feature selection performed on the whole dataset obtained an average ROC AUC score of 0.87 ± 0.09. The second pipeline, in which the feature selection was performed on the training data only, obtained an average ROC AUC score of 0.62 ± 0.17. Conclusions: The obtained results confirm the efficiency of ZOT radiomic features in capturing the renal tumor characteristics. We showed that there is a significant difference in the performances of the two proposed pipelines, highlighting how some already published radiomic analyses could be too optimistic about the real generalization capabilities of the models.
Maintaining Well-Being During the COVID-19 Pandemic: A Network Analysis of Well-Being Responses from British Youth

COVID-19 has significant impacts on young peoples’ lives and emotions. Understanding how young people maintain well-being in the face of challenges can inform future mental health intervention development. Here we applied network analysis to well-being data gathered from 2532 young people (12-25 years) residing in the UK during the COVID-19 pandemic to identify the structure across well-being and crucially, its central defining features. Gender and age differences in networks were also investigated. Across all participants, items emerged in two clusters: 1) optimism, positive self-perception, and social connectedness, and 2) processing problems and ideas. The two central features of well-being were: “I’ve been dealing with problems well” and “I’ve been thinking clearly”. There were minimal age and gender differences. Our findings suggest that the perception of being able to process problems and ideas efficiently could be a hallmark of well-being, particularly in the face of challenging circumstances. These findings contrast with pre-pandemic studies that point to positive affect as central aspects of well-being networks. Future interventions that encourage problem-solving and mental flexibility could be useful in helping young people maintain well-being during times of stress and uncertainty.
The evolution of rotating stars. III. Predicted surface rotation velocities for stars which conserve total angular momentum.

Predicted surface rotation velocities are presented for Population I stars at 10, 7, 5, 3, and 1.5M/sub sun/. The surface velocities have been computed for three different cases of angular momentum redistribution: no radial redistribution (rotation on decoupled shells), complete redistribution (rigid-body rotation), and partial redistribution as predicted by detailed consideration of circulation currents in rotation stars. The velocities for these cases are compared to each other and to observed stellar rotation rates (upsilon sin i). Near the main sequence, rotational effects can substantially reduce the moment of inertia of a star, so nonrotating models consistently underestimate the expected velocities for evolving stars. The magnitude of these effects is sufficient to explain the large numbers of Be stars and, perhaps, to explain the bimodal distribution of velocities observed for the O stars.On the red giant branch, angular momentum redistribution reduces the surface velocity by a factor of 2 or more, relative to the velocity expected for no radial redistribution. This removes the discrepancy between predicted and observed rotation rates for the K giants and makes it unlikely that these stars lose significant amounts of angular momentum by stellar winds. Our calculations indicate that improved observations (by the Fourier-transform technique) of themore » red giants in the Hyades cluster can be used to determine how angular momentum is redistributed by convection. « less
On the asymptotic behavior of a discrete time inspection game

Abstract In many material processing and storing plants an inspector performs during some reference time interval, e.g. one year, a number of inspections because it can not be excluded that the plant operator acts illegally by violating agreed rules, e.g., diverts valuable material. The inspections guarantee that any illegal action is detected at the earliest inspection following the beginning of that illegal action. We assume that the inspector wants to choose the time points for his inspections such that the time which elapses between the beginning of the illegal action and its detection is minimized whereas the operator wants to start his illegal action such that the elapsed time is maximized. Therefore, this inspection problem is modelled as a zero‐sum game with strategies and payoffs as described. Depending on the concrete situation the start of the illegal action and the inspections can take place either at a finite number of time points or at every time point of a reference period. The first case c.
Physiologically based pharmacokinetic-pharmacodynamic evaluation of meropenem in CKD and hemodialysis individuals

Objective: Chronic kidney disease (CKD) has significant effects on renal clearance of drugs. The application of antibiotics in CKD patients to achieve the desired therapeutic effect is challenging. This study aims to determine meropenem plasma exposure in the CKD population and further investigate optimal dosing regimens. Methods: A healthy adult PBPK model was established using the meropenem’s physicochemical parameters, pharmacokinetic parameters, and available clinical data, and it was scaled to the populations with CKD and dialysis. The differences between the predicted concentration, Cmax, and AUClast predicted and observed model values were assessed by mean relative deviations (MRD) and geometric mean fold errors (GMFE) values and plotting the goodness of fit plot to evaluate the model’s performance. Finally, dose recommendations for CKD and hemodialysis populations were performed by Monte Carlo simulations. Results: The PBPK models of meropenem in healthy, CKD, and hemodialysis populations were successfully established. The MRD values of the predicted concentration and the GMFE values of Cmax and AUClast were within 0.5–2.0-fold of the observed data. The simulation results of the PBPK model showed the increase in meropenem exposure with declining kidney function in CKD populations. The dosing regimen of meropenem needs to be further adjusted according to the renal function of CKD patients. In patients receiving hemodialysis, since meropenem declined more rapidly during the on-dialysis session than the off-dialysis session, pharmacodynamic evaluations were performed for two periods separately, and respective optimal dosing regimens were determined. Conclusion: The established PBPK model successfully predicted meropenem pharmacokinetics in patients with CKD and hemodialysis and could further be used to optimize dosing recommendations, providing a reference for personalized clinical medication.
Privacy-preserving transfer learning-based secure quantum image retrieval in encrypted domain for cloud environment

Abstract. Nowadays, the rapid growth of personal handheld electronic devices encourages the individual and organizations to upload their information to cloud for storage and processing purposes. To ensure privacy, the images are encrypted using cryptographic schemes that are outsourced to the cloud. Though images are encrypted, searching for similar images leads the cloud server to access the image data as it performs computation over plaintext. Thus, to ensure the privacy of the images during image retrieval, the proposed framework presents a transfer learning-based secure quantum image retrieval scheme over encrypted cloud. The confidentiality of the images is guaranteed by introducing quantum-based image encryption. Meanwhile, clustered image feature vectors are extracted through the transfer learning model and protected using secure multiparty computation. During retrieval, the proposed system introduces a similarity comparison model for performing computation on encrypted data. The experiments and performance analysis show the effectiveness and security of the proposed scheme.
Estimation of the derivative of a stationary measure with respect to a control parameter

The paper deals with a problem which arises in the Monte Carlo optimization of steady state or ergodic systems which can be modelled by Markov chains. The transition probability depends on a parameter, and one wishes to find the parameter value at which some performance function is minimum. The only available data are obtained from either simulation or actual operating information. For such a problem one needs good statistical estimates of the derivatives. Conditions are given for the existence of the derivative of the stationary measure with respect to the parameter, in the sense that the derivative is a signed measure, and is the limit of the natural approximating sequence. Some properties and a useful characterization of the derivative are obtained. It is also shown that, under appropriate conditions, the derivative of the n-step transition function converges to the derivative of the stationary measure as n tends to ∞. This latter result is of particular importance whether one is simply estimating or is actually optimizing via some sequential Monte Carlo procedure, since the basic observations are always taken over a finite time interval.