Miracle-dz/UniFAR-FTUs huggingface dataset:
Stein Shrinkage for Cross-Covariance Operators and Kernel Independence Testing

Cross-covariance operators arise naturally in many applications using Reproducing Kernel Hilbert Spaces (RKHSs) and are typically estimated using an empirical plugin estimator, which we demonstrate are poor estimators of operator (eigen)spectra at low sample sizes. This paper studies the phenomenon of Stein shrinkage for infinite dimensional cross-covariance operators in RKHSs, as briefly initiated by Muandet et al (2014) who recently suggested two shrinkage estimators. We develop a third family of shrinkage estimators and undertake a study of how shrinkage improves estimation of operator spectra. We demonstrate an important and surprising application, that shrunk test statistics yield higher power for kernel independence tests and we provide insights into why they improve performance.
Microwave spectroscopy of magnetostatic waves in epitaxial ferrite films : Radio Phenomena in solids and plasma

Dispersion characteristics of magnetostatic waves (MSWs) in epitaxial ferrite films with the (100), (110), and (111) orientations are investigated theoretically. Special features associated with magnetic crystallographic anisotropy are considered. A nondestructive technique for determining a complete set of magnetic parameters of the films from MSW spectra is developed. The measurement error effect on the obtained results is estimated. The nonuniformity of parameters is analyzed. Experimental results for yttrium iron garnet (YIG) and gallium substituted yttrium iron garnet (Ga-YIG) films with the (100) and (111) orientations are presented.
Supervised Image Segmentation with Scale Invariance

To cope with scale variations in images, scale invariance is a desired property in many computer vision tasks. Lindeberg’s scale selection method is probably the most successfully and widely used approach for this property. It provides a general technique for image structures at different scales, which can be detected in terms of Gaussian differential operators. For many real-world application, however, it is often difficult or even impossible to explicitly design an operator that is capable to detect image structures of interest in a sensitive and specific way. In this paper, we present a supervised approach to detect image structures, with image segmentation as the application. A trained classifier is used to classify structures of different classes at all scales. The posterior probabilities, outputted by the classifier, is then used to select appropriate scales at all locations. The method can be think of as a supervised version of Lindeberg’s classical scheme.
Exploring Parents' Perceptions of an Early Intervention for Toddlers With Autism

Early intervention (EI) services are intended to be delivered in a family-centered manner. Thus, it is important to obtain family perspectives as they relate to implementation experiences in EI. Using an implementation science framework to guide the questioning. Twelve interviews were conducted with parents who participated in 1 EI program to explore their perceptions of challenges and successes around the intervention practice components, parent coaching processes, and contextual factors in which the intervention was delivered. Parents perceived many of the aspects of the intervention such as specific strategies, strong relationships with their interventionists, and intervention delivery in home and clinic settings as useful and beneficial. They reported challenges related to embedding the intervention into daily activities, feelings of discomfort when practicing intervention strategies, and struggles with scheduling sessions. Implications for research and practice are discussed.
Major Trends in Festivals Events Research: A Bibliometric Study

Purpose – This research provides a bibliometric review on the trend of articles in event management through scopus. The context of Special events such as festival events in scopus can shows the pattern of events being held by the organizer and also the problems that has been facing in organizing events change from time to time according to the current trend. Design/methodology/approach – To explore the progress of organizing an events from 2011 to 2021. The method of the study is using bibliometric analysis based on 3342 articles, conference paper, Journal and book series. Findings – The findings shows a clear trend in event management that change according to current demand from the participants/ attendees. The paradigm shift that organizing a physical events, that had changed to virtual events that cause by the pandemic. However, starting from 2021, not much of researchers had made a study on virtual events due to this implementation are still new. Originality/Value – The current global challenges with the technology advancement in event industry can increase the innovations in event management. Through this bibliometric review of the past research will give the advantage to the future researchers to identify the changes of trend in event industry.
H_∞ controller design for a class of nonlinear Hamilton netw orked contol systems w ith actuator saturation

The H∞state-feedback controller design problem for a class of nonlinear Hamilton netw orked control systems w ith actuator saturation w as investigated. Subject to actuator saturation,uncertain netw orkinduced delays and data packet dropout w ere included in the netw orked control systems. The disturbances of the systems studied have unknow n statistical characteristics but bounded norm. First,according to the structural characteristics of Hamilton systems and the bound of netw orkinduced delays and data packet dropout,netw orkinduced delays and data packet dropout w ere changed into time-varying time-delay. Then,by using the stability theorem of Lyapunov-Krasovskii,the H∞controller w as designed and w hich also satisfied the requirements in H∞performance. The unknow n parameters of the controller w ere obtained by solving a special kind of inequalities. Finally,a example w as given to illustrate the efficiency of the proposed method.
Attention Guided Multi-Task Network for Joint CFO and Channel Estimation in OFDM Systems

The existence of high carrier frequency offset (CFO) and fading channels degrades the performance of communication systems in high mobility environments significantly. To address these challenges, in this paper, we propose an attention guided multi-task network for joint CFO and channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Specifically, considering the correlation between CFO estimation and channel estimation, we construct a multi-task neural network framework which consists of a shared branch (SB), a CFO estimation branch (CFOEB) and a channel estimation branch (CEB). Among them, the SB extracts common features of two tasks, and the CFOEB and CEB make more detailed CFO and channel estimation, respectively. To further suppress the influence of CFO estimation error on channel estimation, we introduce an attention guided module (AGM) which completes the re-calibration of the channel dimension on the basis of different CFO characteristics. We train the whole network by an end-to-end paradigm and construct a suitable multi-task loss function to balance the losses between different tasks. Simulation results demonstrate that the proposed attention guided multi-task learning based joint CFO and channel estimation scheme outperforms the conventional methods and has greater robustness under various conditions.
Combining model checking and theorem proving

We implement a model checker for the modal mu-calculus as a derived rule in a fully expansive mechanical theorem prover, without causing an unacceptable performance penalty. We use a restricted form of a higher order logic representation calculus for binary decision diagrams (BDDs) to interface the model checker to a high-performance BDD engine. This is used with a formalised theory of the modal mu-calculus (which we also develop) for model checking in which all steps of the algorithm are justified by fully expansive proof. This provides a fine-grained integration of model checking and theorem proving using a mathematically rigourous interface. The generality of our theories allows us to perform much of the proof offline, in contrast with earlier work. This substantially reduces the inevitable performance penalty of doing model checking by proof. To demonstrate the feasibility of our approach, optimisations to the model checking algorithm are added. We add naive caching and also perform advanced caching for nested non-alternating fixed-point computations. Finally, the usefulness of the work is demonstrated. We leverage our theory by proving translations to simpler logics that are in more widespread use. We then implement an executable theory for counterexample-guided abstraction refinement that also uses a SAT solver. We verify properties of a bus architecture in use in industry as well as a pedagogical arithmetic and logic unit. The benchmarks show an acceptable performance penalty, and the results are correct by construction.
Cross-Modality Continuous User Authentication and Device Pairing With Respiratory Patterns

At-home screening systems for obstructive sleep apnea (OSA) can bring convenience to remote chronic disease management. However, the unsupervised home environment is subject to spoofing and unintentional interference from the household member. To improve robustness, this work presents SIENNA, an insider-resistant breathing-based authentication/pairing protocol. SIENNA leverages the uniqueness of breathing patterns to automatically and continuously authenticate a user and pairs a mobile OSA app and a physiological monitoring radar system (PRMS). SIENNA does not require biometric enrollment and instead transforms the respiratory measurements taken during the user’s routine physical checkup into breathing biometrics comparable with the PRMS readings. Furthermore, it can operate within a noisy multitarget home environment and is secure against a co-located attacker through the usage of joint approximate diagonalization of eignematric-independent component analysis, fuzzy commitment, and friendly jamming. We fully implemented SIENNA and evaluated its performance with medium-scale trials. Results show that SIENNA can achieve reliable $(>90$ % success rate) user authentication and secure device pairing in a noisy environment against an attacker with full knowledge of the authorized user’s breathing biometrics.
Prevalence and Risk Factors of Depression and Anxiety among Women in the Last Trimester of Pregnancy: A Cross-Sectional Study

Pregnancy represents a psychologically and emotionally vulnerable period, and research indicates that pregnant women have a higher prevalence of symptoms of anxiety and depression, debunking the myth that hormonal changes associated with pregnancy protect the mother. In recent years, several researchers have focused on the study of prenatal anxiety/depression—emotional disorders manifested by mood lability and low interest in activities—with a high prevalence. The main objective of this research was to conduct an antenatal screening in a cohort of pregnant women hospitalized for delivery in order to assess the prevalence of anxiety and depression. The secondary objective was to identify the risk factors associated with depression and anxiety in women in the third trimester of pregnancy. We carried out a prospective study in which we evaluated 215 pregnant women in the third trimester of pregnancy hospitalized for childbirth at the Obstetrics and Gynecology Clinic of the Târgu-Mureș County Clinical Hospital. The research was carried out between December 2019 and December 2021. The results showed that age and the environment of origin are the strongest predictors of mental health during pregnancy (OR = 0.904, 95%CI: 0.826–0.991; p = 0.029). For women from urban areas, there is an increased probability of falling at a higher level on the dependent variable (moderate depression) (OR = 2.454, 95%CI: 1.086–5.545; p = 0.032). In terms of health behaviors, none of the variables were statistically significant predictors of the outcome variable. The study highlights the importance of monitoring mental health during pregnancy and identifying relevant risk factors to provide appropriate care to pregnant women and the need for interventions to support the mental health of pregnant women. Especially in Romania, where there is no antenatal or postnatal screening for depression or other mental health conditions, these results could be used to encourage the implementation of such screening programs and appropriate interventions.
Retrieval and validation of vertical LAI profile derived from airborne and spaceborne LiDAR data at a deciduous needleleaf forest site

ABSTRACT Leaf area index (LAI) is defined as one half of the total green leaf area per unit ground surface area. Its vertical profile is critical for understanding the remote sensing radiative transfer processes. LAI profile has been derived from airborne and spaceborne LiDAR data, such as the Global Ecosystem Dynamics Investigation (GEDI) installed on the International Space Station. However, the capability of various algorithms for the LAI profile estimation with airborne LiDAR is not clearly evaluated, and the estimated LAI profiles, including the GEDI LAI products, are not been fully validated. This study conducted a quantitative retrieval and validation of the LAI profiles using terrestrial and airborne laser scanning (TLS and ALS) and spaceborne GEDI data over a deciduous needleleaf forest site in northern China. The vertical LAI profile was estimated in the field using an upward digital hemispherical photography (DHP) attached to a portable measurement system in 2020 and 2021. A suite of new LiDAR indices combining both LiDAR return number and return intensity was explored for the LAI profile estimation. All LAI profiles obtained from the DHP, TLS, ALS, and GEDI during the leaf-on season and leaf-off season were compared. The DHP shows a good agreement with the TLS LAI profiles (R2 = 0.97). The LAI profile derived from the ALS data using the combined light penetration index (LPIRI) agrees well (R2 ≥0.86) with the DHP, TLS, and GEDI estimates. In general, the LPIRI is advantageous for regional LAI profile mapping from ALS. The GEDI cumulative LAI corresponds well with the DHP during the leaf-on season (R2 = 0.90, RMSE = 0.23), but underestimates during the leaf-off season (R2 = 0.70, RMSE = 0.14, bias=−0.13). The underestimation is attributed to the higher canopy and ground reflectance ratio (ρv/ρg) assigned in the algorithm and the height discrepancy between the GEDI and field measurements. For the GEDI LAI profile product, further validation and improvement are necessary for other biome types and landscape conditions, especially during the leaf-off season.
Experimental and numerical investigation of the flow characteristics of a strut injector for scramjets

A peculiar dynamical interaction of two supersonic counter-rotating vortex pairs (CVPs) has been generated by a pair of overlapping expansion ramps mounted on a strut injector in a Mach 2.5 flow. Similar CVP configurations generated by overlapping ramps on the same modular strut injector have previously been studied by the authors and experimentally corroborated the predictions based on the in-house developed reduced order model, VorTx. Two co-rotating vortices at the center of the generated structure have either merged or begun to orbit each other. However, for the case discussed in this work, experiments have revealed an additional structure; in fact, instead of the expected four streamwise vortices in the flowfield consisting of two inner co-rotating vortices and two oppositely rotating external vortices, the formation of a fifth structure, a central vorticity patch, was detected. The manuscript presents a detailed experimental characterization of the flow of interest via the use of stereoscopic particle image velocimetry and a parallel computational effort based on the solution of the Reynolds Averaged Navier-Stokes equations with the ANSYS Fluent CFD Package. The results of the CFD simulations highlight the near injector flowfield, which is unable to be characterized experimentally, in order to focus upon the mechanism that result in the formation and the effects of the central vorticity patch.
Multifractal Modeling of the Japanese Treasury Term Structure

This paper identifies Multifractal Models of Asset Returns (MMARs) for each of the eight nodal term structure series of monthly Japanese Treasury rates and, after proper synthesis, simulates those MMARs. All nodal rate series are found to be slightly anti-persistent, with the exception of the 20-year rate which is heavily anti-persistent and in the range of being chaotic. This contrasts with our earlier findings of the US term structure (Jamdee-Los, 2005), where the US interest rates are identified to be slightly persistent, although that model identification was based on daily data. The simulations of the identified Japanese interest rate MMARs are compared with the original empirical time series, and also with the simulated results from the corresponding Geometric Brownian Motion (GBM) and GARCH processes. All eight different maturity Japanese Treasury rates are found to be multifractal processes. Identified distributions of all simulated processes are compared with the empirical distributions in both snapshot and time-scale (-frequency) analyses. Using wavelet scalograms, we demonstrate that the MMAR does not clearly outperform either the GBM and GARCH(1, 1) in time-frequency comparisons. The simulated MMAR replicates all attributes of the short maturity empirical distributions, while the simulated GBM and GARCH(1, 1) processes perform better for the long maturity series. Nevertheless, these results are somewhat inconclusive since the MMAR experiences difficulty with the simulations of these anti-persistent, and in one case, possibly chaotic, price diffusion processes.
Object-Aware View Planning for Autonomous 3-D Model Reconstruction of Buildings Using a Mobile Robot

Active mapping ranks among the most critical applications of autonomous mobile robots. In this article, we focus on 3-D model reconstruction of buildings using an outdoor ground robot equipped with a solid-state light detection and ranging (LiDAR) and a gimbal. A view-planning approach is proposed to generate and evaluate view sequences with reference to the characteristics of solid-state LiDAR and the robot configuration. To reconstruct the specific buildings while ignoring unrelated objects in the environment, we introduce object awareness into the map representation, and frontier- and sampling-based strategies are combined to plan the view sequences for the effective observation of a target building. Instead of greedily maximizing information gain, frontier clusters indicating the mapped object’s incomplete surfaces are used to evaluate the sampled views and sampling the minimum view set generates view sequences able to efficiently cover the clusters. Moreover, using object awareness to partition the area of sampled views around the building facilitates a divide-and-conquer strategy that overcomes local characteristics and guides a complete reconstruction. Simulation and real-world experiments revealed that our approach allows the thorough and efficient active reconstruction of various buildings and even outperforms the state-of-the-art approaches.
Implementation of Social Inclusion to Support Refugee Students’ Well-Being in Victoria, Australia: A Study of School Reports and Policies

Abstract This paper explores social inclusion approaches implemented by ten secondary schools in Victoria, Australia, to support refugee students’ well-being, as articulated in their policies, reports, and other published documents. Using an exploratory, qualitative research design, we found that all schools employed a holistic approach to implementing social inclusion programs for refugee students. This paper reports on the best practices and unique examples of social inclusion programs from all schools involved in the study.
QTL Mapping for Ovary- and Fruit-Related Traits in Cucumis sativus-C. hystrix Introgression Line IL52

IL52 is a valuable introgression line obtained from interspecific hybridization between cultivated cucumber (Cucumis sativus L., 2n = 14) and the wild relative species C. hystrix Chakr. (2n = 24). IL52 exhibits high resistance to a number of diseases, including downy mildew, powdery mildew, and angular leaf spot. However, the ovary- and fruit-related traits of IL52 have not been thoroughly investigated. Here, we conducted quantitative trait loci (QTL) mapping for 11 traits related to ovary size, fruit size, and flowering time using a previously developed 155 F7:8 RIL population derived from a cross between CCMC and IL52. In total, 27 QTL associated with the 11 traits were detected, distributed on seven chromosomes. These QTL explained 3.61% to 43.98% of the phenotypic variance. Notably, we identified a major-effect QTL (qOHN4.1) on chromosome 4 associated with the ovary hypanthium neck width and further delimited it into a 114-kb candidate region harboring 13 candidate genes. Furthermore, the QTL qOHN4.1 is co-localized with the QTL detected for ovary length, mature fruit length, and fruit neck length, all residing within the consensus QTL FS4.1, suggesting a plausible pleiotropic effect.
A Neumann Boundary Value Problem in Two-Ion Electro-diffusion with Unequal Valencies

In prior work, a series of two-point boundary value problems have been investigated for a steady state two-ion electro-diffusion model system in which the sum of the valencies $\nu_+$ and $\nu_-$ is zero. In that case, reduction is obtained to the canonical Painleve II equation for the scaled electric field. Here, a physically important Neumann boundary value problem in the generic case when $\nu_+ + \nu_-\neq 0$ is investigated. The problem is novel in that the model equation for the electric field involves yet to be determined boundary values of the solution. A reduction of the Neumann boundary value problem in terms of elliptic functions is obtained for privileged valency ratios. A topological index argument is used to establish the existence of a solution in the general case, under the assumption $\nu_+ + \nu_- \leq 0$.
Temporal Changes in Demography and Genetic Diversity of Oriental Storks at the Stage of Long-Term Captive Propagation and Reintroduction Initiation

Captive propagation and reintroduction are the major steps in the ex-situ conservation of locally extirpated endangered species in a historical region. In a species restoration project conducted in South Korea, we examined temporal changes in demographics and genetic diversity of oriental storks (Ciconia boyciana). Demographic and genetic data from 1996–2018 were analyzed for 80% of all captive and recently reintroduced individuals. Founder establishment and pair formation induced increases in population size and genetic diversity during the early stage of captive propagation. The degree of genetic diversity was found to become saturated and stable with long-term captive propagation. However, this might be a concern for future genetic diversity of both captive and reintroduced populations simultaneously due to the extraction of captive populations at the early stage of reintroduction. Our findings suggest that periodic evaluation of genetic diversity and selection for releasing individuals, using effective genetic markers, would assist in balancing the genetic diversity of the captive and reintroduced oriental storks at the early stage of reintroduction.