Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Solution of the spectral problem for arbitrary self-adjoint extensions of the Schr\"odinger equation on manifolds with boundary

A numerical scheme to compute a large class of self-adjoint extensions of the Laplace-Beltrami operator on manifolds with boundary in any dimension is presented. The algorithm is based on the characterisation, recently obtained by the authors, of a large class of self-adjoint extensions of Laplace-Beltrami operators in terms of their associated quadratic forms. Such extensions are determined by a unitary operator $U$ defined on the space of data at the boundary and possessing a gap property at the eigenvalue $-1$. The convergence of the scheme is proved by applying an iterated min-max argument to a specific finite elements approximation of the domain of the corresponding quadratic form that depends on the choice of the unitary map $U$. An algorithm for dimension 2 is implemented effectively. It is needed a suitable approximation of the unitary operators acting on the infinite-dimensional space of data of the boundary. This is in contrast with the one-dimensional situation explored by the authors already [18], where the space of boundary data is finite-dimensional. As a consequence of the implementation of the boundary conditions in terms of a unitary operator, the numerical scheme proposed is able to treat essential and natural boundary conditions in a unified way. Several numerical experiments are computed, showing that the algorithm is able to treat a wide variety of boundary conditions including, for instance, quasi-periodic boundary conditions (also called Bloch-periodic) or mixed type boundary conditions. As in the one-dimensional situation, the experiments confirm the existence of self-adjoint extensions where the lower eigenvalues are localised near the boundary. Such localised states play an important role in condensed state physics like Quantum Hall effect or topological insulators.
Riskiness of value-creating corporate activities and their influence on strategic management of engineering companies

This paper presents a procedure for definition and analysis of value-creating corporate activities on an example of a selected engineering company and a newly proposed calculation of riskiness of the production process. The risk calculation is based on an analysis of the value chain or value stream of its primary activities. Three research questions were formulated within the framework of the solution concerning differentiation of the value stream in serial and custom production, significance of individual primary processes for creation of the corporate margin and differentiation of the degree of risk between serial and custom production. The obtained outputs from the model engineering enterprise showed that the intensity of added value creation is lower in serial production than in custom production. In terms of the importance of the primary activities for serial and custom production in the value chain, the production process can be considered dominant from the viewpoint of margin generation, followed by the technical preparation process. In addition to the already mentioned reduced level of generation of added value, the lower average riskiness of the production process was also found for serial production compared to custom production. The graphical presentation at the end of the paper suggests a correlation between the level of added value creation in partial production operations and their respective level of risk. The authors of the article assume that the presented results have general validity for engineering production enterprises, which will be the subject of follow-up case studies on similar topics.
Critical phenomena in (2+1)-dimensional relativistic fermion systems

In this work we investigate critical phenomena in a variant of the chiral Gross-Neveu model and the Thirring model in 2+1 dimensions. We employ the functional renormalization group (RG), which is an extremely powerful analytical approach to describe strongly-correlated fermion systems at criticality. We compute the critical behavior of the chiral Gross-Neveu model, where we allow for a different number of left- and right-handed fermion flavors. In this sense, this system can be viewed as a toy model for the Higgs-Yukawa sector of the standard model of particle physics. The RG analysis of the Thirring model uses a full basis of fermionic four-point functions. Our results show that the UV complete (asymptotically safe) Thirring model lies in a two-dimensional coupling plane which reduces to the conventional Thirring coupling only in the strict limit of infinite flavor number. This allows for the first time a microscopic explanation for the existence of a critical flavor number above which chiral symmetry remains unbroken for arbitrary large coupling: for large flavor number, chiral symmetry breaking is prohibited due to a competition between different condensation channels. With the help of the dynamical bosonization technique we give detailed quantitative predictions for the critical behavior in terms of universal critical exponents and relate them to the literature.
Absence of self-reported neuropsychiatric and somatic symptoms after Omicron variant SARS-CoV-2 breakthrough infections

Abstract Persistent somatic and neuropsychiatric symptoms have been frequently described in patients after infection with severe acute respiratory syndrome coronavirus 2 even after a benign clinical course of the acute infection during the early phases of the coronavirus severe acute respiratory syndrome coronavirus 2 pandemic and are part of Long COVID. The Omicron variant emerged in November 2021 and has rapidly become predominant due to its high infectivity and suboptimal vaccine cross-protection. The frequency of neuropsychiatric post-acute sequelae after infection with the severe acute respiratory syndrome coronavirus 2 Omicron and adequate vaccination status is not known. Here, we aimed to characterize post-acute symptoms in individuals with asymptomatic or mildly symptomatic breakthrough infection with severe acute respiratory syndrome coronavirus 2. These individuals had either proven infection with the Omicron variant (n = 157) or their infection occurred in 2022 where Omicron was the predominant variant of severe acute respiratory syndrome coronavirus 2 in Germany (n = 107). This monocentric cross-sectional study was conducted at the University Medical Center Hamburg-Eppendorf between 11 February 2022 and 11 April 2022. We employed questionnaires addressing self-reported somatic symptom burden (Somatic Symptom Scale 8) and neuropsychiatric symptoms including mood (Patient Health Questionnaire 2), anxiety (Generalized Anxiety Disorder 7), attention (Mindful Attention Awareness Scale) and fatigue (Fatigue Assessment Scale) in a cohort of hospital workers. Scores were compared between 175 individuals less than 4 weeks after positive testing for severe acute respiratory syndrome coronavirus 2, 88 individuals more than 4 weeks after positive testing and 87 severe acute respiratory syndrome coronavirus 2 uninfected controls. The majority (n = 313; 89.5%) of included individuals were vaccinated at least three times. After recovery from infection, no significant differences in scores assessing neuropsychiatric and somatic symptoms were detected between the three groups (severe acute respiratory syndrome coronavirus 2 uninfected controls, individuals less and more than 4 weeks after positive testing) independent of age, sex, preconditions and vaccination status. In addition, self-reported symptom burden did not significantly correlate with the number of vaccinations against severe acute respiratory syndrome coronavirus 2, time from recovery or the number of infections. Notably, in all three groups, the mean scores for each item of our questionnaire lay below the pathological threshold. Our data show that persistent neuropsychiatric and somatic symptoms after recovery from severe acute respiratory syndrome coronavirus 2 infection in fully vaccinated hospital workers do not occur more frequently than that in uninfected individuals. This will guide healthcare professionals in the clinical management of patients after recovery from breakthrough infections with severe acute respiratory syndrome coronavirus 2.
podft: On Accelerating Dynamic Taint Analysis with Precise Path Optimization

—Dynamic taint analysis (DTA) has been widely used in security applications, including exploit detection, data provenance, fuzzing improvement, and information flow control. Meanwhile, the usability of DTA is argued on its high runtime overhead, causing a slowdown of more than one magnitude on large binaries. Various approaches have used preliminary static analysis and introduced parallelization or higher-granularity abstractions to raise the scalability of DTA. In this paper, we present a dynamic taint analysis framework podft that defines and enforces different fast paths to improve the efficiency of DBI-based dynamic taint analysis. podft uses a value-set analysis (VSA) to differentiate the instructions that must not be tainted from those potentially tainted. Combining the VSA-based analysis results with proper library function abstractions, we develop taint tracking policies for fast and slow paths and implement the tracking policy enforcement as a Pin-based taint tracker. The experimental results show that podft is more efficient than the state-of-the-art fast path-based DTA approach and competitive with the static binary rewriting approach. podft has a high potential to integrate basic block-level deep neural networks to simplify fast path enforcement and raise tracking efficiency.
Bounded-Influence Rank Regression: A One-Step Estimator Based on Wilcoxon Scores

Abstract The Krasker-Welsch (1982) approach to bounding influence is merged with rank regression. I propose a one-step estimator that is analogous to Bickel's (1975) one-step M estimator of Type 1 but uses weights that depend on the design vector and the residuals to reduce the influence of outliers. In fact, the standardized sensitivity of the estimator is made equal to a prechosen constant. It is based, however, on a second-derivative approximation to a dispersion surface that is not convex. This one-step variant avoids the problem of multiple roots. The estimator is shown to be consistent and asymptotically multivariate normal. An example shows that it yields results similar to those of the Krasker-Welsch estimator.
The Impact of TBI on Intermediate Students’ Writing skills in Online Classes at a Private Institute in Cartagena de Indias

This qualitative research project aims to determine the impact that Task-Based Instruction had on fifteen Intermediate English language students´ writing skills in online classes at a private institute in Cartagena. A journal, a questionnaire, and a checklist were used as instruments to collect information during the diagnostic stage. During the action stage, six workshops were implemented, each with a different writing strategy: webbing, peer-editing, asking questions to revise writing, revising and editing, using templates, and reorganizing ideas. At this stage, the same instruments were used to measure the impact of the strategy and to achieve the research objectives. Results show that implementing six online workshops predicated on the task-based instruction helped the students to improve their writing, learning new vocabulary, use ICT tools, and writing strategies, thus having a positive impact on their English language learning process not only in writing but also in other skills. TBI was favorably accepted by learners and affected positively their writing skills.
A nonlinear minimization approach to multiobjective and structured controls for discrete‐time systems

In this paper, a nonlinear minimization approach is proposed for multiobjective and structured controls for discrete‐time systems. The problem of finding multiobjective and structured controls for discrete‐time systems is represented as a quadratic matrix inequality problem. It is shown that the problem is reduced to a nonlinear minimization problem that has a concave objective function and linear matrix inequality constraints. An algorithm for the nonlinear minimization problem is proposed, which is easily implemented with existing semidefinite programming algorithms. The validity of the proposed algorithm is illustrated by comparisons with existing methods. In addition, applications of this work are demonstrated via numerical examples. Copyright © 2004 John Wiley & Sons, Ltd.
Identifying Gaps in Sexual Health Education: What Women Learned and What Women Wish They Learned

Abstract Sexual education may vary depending on the sources and what specific topics are discussed. The present study examined themes and sources of sexual education in an early adult women sample (N = 581). Women recalled sources and specific topics and identified missing topics that would have been beneficial. Latent class analysis classified women into two classes: school-only sexual education and multiple sources/eclectic. The eclectic group recalled a greater discussion of contraceptives, sexual activity, emotional aspects, pleasure, and gender and sexual identities. Both groups noted a greater desire for realistic lessons, education on empowerment and normalization, and more variety of resources.
Salivary protein carbonyl and selected antioxidants in relation to dental caries among pregnant women

Background: Pregnancy is a physiological condition that affects the general and oral health.It is also associated with an increase in oxidative stress, which may presispose to oral diseases including dental caries. Aim of the study: This study aimed to measure salivary protein carbonyl, glutathione peroxidase and selenium levels of women who are pregnant and their association with dental caries in comparison to non-pregnant women, and to find out the mostly affected biomarker of oxidative stress during pregnancy. Subjects, materials and methods: A cross-sectional research was performed for a samples of 30 pregnant and 30 non-pregnant women who were chosen from city of Baghdad's Primary Healthcare Centers. Both groups aged 25-30 years. In unstimulated salivary samples protein carbonyl and glutathione peroxidase were determined colorimetrically using spectrophotometer by utilizing ready-made assay kits. Salivary selenium level was obtained by atomic absorption spectrophotometer. Plaque index had been used to determine the thickness of dental plaque. Caries was recorded using the Decayed, Missing, and Filled (DMF) index. described by WHO in 1997. Data was statistically analyzed using descriptive statistics method and Student's t-test, Wilcoxon sum rank test and Spearman’s correlation in addition to Receiver Operating Characteristics Curve (ROC test) (α=5%). Results: The plaque index and salivary protein carbonyl values were significantly higher among pregnant while salivary selenium and glutathione peroxidase recorded significantly lower levels among pregnant women. Dental caries parameters were higher among pregnant with significant difference for MS fraction only. ROC area for protein carbonyl equal one with highest sensitivity and specificity. Conclusion: Pregnant women recorded higher dental caries severity with higher salivary protein oxidation but lowers salivary antioxidant defense mechanisms. Salivary protein carbonyl is more ideal, valid and mostly affected biomarker in revealing the oxidative stress status during pregnancy
Expected estimating equations to accommodate covariate measurement error

Estimating equations which are not necessarily likelihood‐based score equations are becoming increasingly popular for estimating regression model parameters. This paper is concerned with estimation based on general estimating equations when true covariate data are missing for all the study subjects, but surrogate or mismeasured covariates are available instead. The method is motivated by the covariate measurement error problem in marginal or partly conditional regression of longitudinal data. We propose to base estimation on the expectation of the complete data estimating equation conditioned on available data. The regression parameters and other nuisance parameters are estimated simultaneously by solving the resulting estimating equations. The expected estimating equation (EEE) estimator is equal to the maximum likelihood estimator if the complete data scores are likelihood scores and conditioning is with respect to all the available data. A pseudo‐EEE estimator, which requires less computation, is also investigated. Asymptotic distribution theory is derived. Small sample simulations are conducted when the error process is an order 1 autoregressive model. Regression calibration is extended to this setting and compared with the EEE approach. We demonstrate the methods on data from a longitudinal study of the relationship between childhood growth and adult obesity.
Image inpainting by neighborhood similarity

There are many approaches for image restoration,the most commonly used are based on partial differential equations or texture synthesis method.These algorithms are complicated and time-consuming.This paper presents a new method of quick and efficient.A point is chosen whoes priority is highest on the border of damaged region.According to neighborhood information of this point,the pixel's value is calculated to use all the neighborhood similarity.Using this algorithms,estimate all the points in the damaged region.Experiments show that this method is quick and effective.
Ordered upwind methods for static Hamilton–Jacobi equations

We introduce a family of fast ordered upwind methods for approximating solutions to a wide class of static Hamilton–Jacobi equations with Dirichlet boundary conditions. Standard techniques often rely on iteration to converge to the solution of a discretized version of the partial differential equation. Our fast methods avoid iteration through a careful use of information about the characteristic directions of the underlying partial differential equation. These techniques are of complexity O(M log M), where M is the total number of points in the domain. We consider anisotropic test problems in optimal control, seismology, and paths on surfaces.
Emergence of a Narrow H2O Maser Feature in NGC 1052

We report the emergence of a narrow H2O maser feature with an FWHM of 21 km s-1 in the LINER NGC 1052, which has been known to show only a broad (FWHM > 100 km s-1) maser line profile with relatively bright continuum radio emission. The new narrow maser feature with a peak flux density of 47 mJy at VLSR = 1787 km s-1 is redshifted by 328 km s-1 with respect to the systemic velocity. Broad features with peak velocities of 1510 and 1704 km s-1, more redward than ever observed before, are also detected. The profile of the new narrow feature possibly shows brightening by 16% ± 9% and narrowing by 30% ± 12% between 2003 May 30 and June 2. During the same time, the continuum flux density has increased by 21%. Synchronous variation of maser and continuum flux densities on a timescale of days resembles that in Mrk 348, which is also a broad megamaser source with a bright radio continuum. Continuum and maser brightening and narrowing indicate that an increase of the background seed photon and an increase of maser gain have occurred simultaneously. A jet component running behind a mixture of ionized regions and X-ray dissociation regions at a subrelativistic velocity can produce such short-time variation. Another explanation is an interaction between the jet and molecular clouds.
Hypervigilance: An Understudied Mediator of the Longitudinal Relationship Between Stigma and Internalizing Psychopathology Among Sexual-Minority Young Adults

Hypervigilance is often theoretically invoked as a psychological mechanism linking stigma to internalizing psychopathology among sexual minorities. Empirically, however, hypervigilance is rarely explicitly assessed but is instead commonly conflated with putatively related constructs, including sexual-orientation-related rejection sensitivity and rumination, hindering conceptual and mechanistic understandings of this process. We therefore embedded a hypervigilance measure in a longitudinal, population-based study of 811 Swedish sexual-minority young adults (ages 17–34). Hypervigilance—but neither sexual-orientation-related rejection sensitivity nor rumination, with which it was only weakly correlated (rs = .23–.24)—uniquely mediated prospective associations between perceived discrimination and internalizing symptoms 2 years later, explaining up to 40% of these effects. Sexual-orientation-related rejection sensitivity and rumination prospectively predicted hypervigilance on these paths. Findings suggest that hypervigilance represents a distinct construct and transdiagnostic mechanism through which stigma-related experiences and processes undermine sexual-minority mental health. We discuss implications for enhancing psychological interventions for sexual minorities by addressing hypervigilance.
A Hidden Two-Shift Rotation Nurse Scheduling Using Integer Goal Programming

In this study, the author reviews and compares different nurse shift scheduling methods via the criteria of flexibility, fairness, nurse preference, and ergonomics principles. A hidden two-shift rotation is proposed to provide better continuity in sift assignments by reducing the number of integer decision variables to solve a three-shift nurse rotation system. The hidden two-shift scheduling system is modeled as an integer goal programming (IGP) problem. To generate the shift assignments for a unit with 14 nurses, the IGP model takes less than 10 minutes on average, whereas the head nurses spend approximately 2 to 5 hours on shift scheduling.
Comparison of PSO, GAs and Analytical Techniques in Second-Order Design of Deformation Monitoring Networks

Abstract Deformation monitoring is a kind of continuous recording positions (horizontal and vertical coordinates) precisely regardless the deformation pattern and instrument used. In general, a deformation monitoring network can be designed using the trial and error method or analytical methods such as linear programming and nonlinear programming. Recently, a deformation monitoring network may also be designed by heuristic optimization algorithms such as Genetic Algorithms (GAs), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). In this paper, GAs and PSO, which are heuristic optimization techniques, are applied to a geodetic horizontal deformation monitoring networks to solve second-order design problem. The results proved that both GAs and PSO can be used as alternative methods in place of the traditional optimization techniques with high eficiency.
Green functions for multiple scattering as mathematical tools for dense-cloud remote sensing: theory with passive and active applications

We survey radiative Green function theory (1) in linear transport theory where numerical procedures are required to obtain specific results and (2) in the photon diffusion limit (large optical depths) where it is analytically tractable, at least for homogeneous plane-parallel media. We then describe two recent applications of Green function theory to passive cloud remote sensing in the presence of strong three-dimensional transport effects. Finally, we describe recent instrumental breakthroughs in 'off-beam' cloud lidar which is based on direct measurements of radiative Green functions with special attention to the data collected during the Shuttle-based Lidar In-space Technology Experiment (LITE) mission.