Miracle-dz/UniFAR-FTUs huggingface dataset:
First-Principles Study of Electronic Structure and Optical Properties of Cubic Perovskite CsCaF3

Electronic, structural and optical properties of the cubic perovskite CsCaF3 are calculated by using the full potential linearized augmented plane wave (FP-LAPW) plus local orbitals method with generalized gradient approximation (GGA) in the framework of the density functional theory. The calculated lattice constant is in good agreement with the experimental result. The electronic band structure shows that the fundamental band gap is wide and indirect at (Γ–R) point. The contribution of the different bands is analyzed from the total and partial density of states curves. The charge density plots show strong ionic bonding in Cs-F, and ionic and weak covalent bonding between Ca and F. Calculations of the optical spectra, viz., the dielectric function, optical reflectivity, absorption coefficient, real part of optical conductivity, refractive index, extinction coefficient and electron energy loss, are performed for the energy range 0–30 eV.
Is the dark triad always detrimental to firm performance? Testing different performance outcomes and the moderating effects of competitive rivalry

There is growing evidence that CEOs who have the ‘dark triad’ of personality traits (Machiavellianism, narcissism, and psychopathy) detrimentally influence firm performance. However, there is still much we do not know. The present study suggests that the CEO dark triad might directly influence typical performance indicators in different ways: positively affecting external performance indicators (breakthrough sales), but negatively affecting internal performance indicators (organizational performance). We argue that the CEO dark triad can be interpreted differently by those external to the firm versus internally, where managers are much closer to the CEO’s dark personality. Our model includes managerial capital as a mediator and competitive rivalry as a moderator, and ultimately tests a moderated mediation model. Using data from 840 New Zealand firms, we find that the dark triad links to outcomes, as expected. While the CEO dark triad is negatively related to managerial capital, managerial capital does positively predict both performance indicators, and partially mediates the CEO dark triad effect. Overall, moderating effects highlight that the CEO dark triad is less detrimental in fiercely competitive business environments, acting as a consistent boundary condition across models. As competitive rivalry increases, the indirect effect of the CEO dark triad on performance decreases. We discuss the implications for understanding the role that the CEO dark triad can play in firms.
A Behavioral Approach to Control of Distributed Systems

This paper develops a theory of control for distributed systems (i.e., those defined by systems of constant coefficient partial differential operators) via the behavioral approach of Willems. The study here is algebraic in the sense that it relates behaviors of distributed systems to submodules of free modules over the polynomial ring in several indeterminates. As in the lumped case, behaviors of distributed ARMA systems can be reduced to AR behaviors. This paper first studies the notion of AR controllable distributed systems following the corresponding definition for lumped systems due to Willems. It shows that, as in the lumped case, the class of controllable AR systems is precisely the class of MA systems. It then shows that controllable 2-D distributed systems are necessarily given by free submodules, whereas this is not the case for n-D distributed systems, $n \ge 3$. This therefore points out an important difference between these two cases. This paper then defines two notions of autonomous distributed systems which mimic different properties of lumped autonomous systems. Control is the process of restricting a behavior to a specific desirable autonomous subbehavior. A notion of stability generalizing bounded input--bounded output stability of lumped systems is proposed and the pole placement problem is defined for distributed systems. This paper then solves this problem for a class of distributed behaviors.
Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation

This paper is concerned with the estimation of covariance matrices in the presence of heteroskedasticity and autocorrelation of unknown forms. Currently available estimators that are designed for this context depend upon the choice of a lag truncation parameter and a weighting scheme. No results are available regarding the choice of lag truncation parameter for a fixed sample size, regarding data-dependent automatic lag truncation parameters, or regarding the choice of weighting scheme. This paper addresses these problems. Asymptotically optimal kernel/weighting scheme and bandwidth/lag truncation parameters are obtained. Using these results, data-dependent automatic bandwidth/lag truncation parameters are introduced. Copyright 1991 by The Econometric Society.
Gender Differences in Relation to Body Composition, Insulin Resistance, and Islet Beta Cell Function in Newly Diagnosed Diabetic or Pre-Diabetic Patients

Objective To assess the correlation between body components with insulin resistance (IR) and islet beta cell function in patients with newly diagnosed type 2 diabetes mellitus (T2DM) or pre-diabetes mellitus (pre-DM) and to explore whether this correlation differs in males and females. Methods 111 newly diagnosed diabetic or pre-diabetic patients were recruited in this cross-sectional study. 75g oral glucose tolerance test was used to determine the diagnosis of DM or pre-DM. Homeostasis model assessment of insulin resistance (HOMA-IR) and glucose disposition index (DI30) was calculated to assess IR and islet beta cell function, respectively. Whole-body and regional lean mass (LM) and fat mass (FM) were obtained by dual-energy X-ray absorptiometry (DEXA). Partial correlation and multiple linear regression analyses were used to determine the associations between body composition, IR, and islet beta cell function. Results More body fat and appendicular fat was observed in female patients than in male, though with similar BMI. Legs fat % was negatively correlated with HOMA-IR, whereas legs lean % was positively associated with HOMA-IR in females (r = −0.673, p = 0.017; r =0.664, p = 0.018, respectively). The regression analysis showed that legs LM was positively correlated with HOMA-IR in females. However, in male patients, android FM was positively correlated with HOMA-IR (r = 0.462, p = 0.007), and trunk LM was negatively associated with DI30 (r = −0.458, p = 0.007). Nevertheless, no significant correlation was observed between body composition and islet beta cell function in female patients. Conclusion Android FM was positively correlated with IR only in male patients but not in females. Besides, relative legs fat and LM were independently associated with IR in female patients but not in males. Further studies are needed to explore the underlying mechanism.
Affective Image Captioning for Visual Artworks Using Emotion-Based Cross-Attention Mechanisms

Within the museum community, the automatic generation of artwork description is expected to accelerate the improvement of accessibility for visually impaired visitors. Captions that describe artworks should be based on emotions because art is inseparable from viewers’ emotional reactions. By contrast, artworks typically do not have unique interpretations; thus, it is difficult for systems to reflect the specified emotions in captions precisely. Most existing methods attempt to leverage predicted emotion labels from images to generate emotion-oriented captions; however, they do not allow users to specify arbitrary emotions. In this paper, we aim to build a model that generates emotion-conditioned captions that describe visual art. We propose an affective visual encoder, which integrates emotion attributes and cross-modal joint features of images into visual information over all encoder blocks. Moreover, we introduce affective tokens that fuse grid- and region-based image features to cover both contextual and object-level information. We validated our method on the ArtEmis dataset, and the results demonstrated that our method outperformed baseline methods on all metrics in the emotion-conditioned task.
Repeatability of measurements: Non-Hermitian observables and quantum Coriolis force

A noncommuting measurement transfers, via the apparatus, information encoded in a system's state to the external “observer. ” Classical measurements determine properties of physical objects. In the quantum realm, the very same notion restricts the recording process to orthogonal states as only those are distinguishable by measurements. Thus, even a possibility to describe physical reality by means of non-Hermitian operators should volens nolens be excluded as their eigenstates are not orthogonal. We show that non-Hermitian operators with real spectra can be treated within the standard framework of quantum mechanics. Further, we propose a quantum canonical transformation that maps Hermitian systems onto non-Hermitian ones. Similar to classical inertial forces this map is accompanied by an energetic cost, pinning the system on the unitary path.
Extending the Link Between Family Financial Stress and Bullying Victimization of Children: A Moderated Mediation Model

ABSTRACT This study aims to examine the association between family financial stress and bullying victimization by incorporating peer and teacher – student relationships into a moderated mediation model. Based on a sample of 40,772 children from the International Survey of Children’s Well-Being, results posit that the link between family financial stress and bullying victimization is mediated by peer relationship, and this mediation is further moderated by teacher – student relationship. Specifically, the direct effect of family financial stress on bullying victimization decreases as the quality of teacher – student relationship increases. Moreover, the effect of peer relationship on bullying victimization is also moderated by teacher – student relationship, with the effect being weaker for children reporting high levels of teacher – student relationship. This study contributes to current understanding of the mediation and moderation through which family economic conditions are linked with bullying victimization. Implications for practice and directions for future research are also discussed.
3D Electrospun Polycaprolactone Scaffolds to Assess Human Periodontal Ligament Cells Mechanobiological Behaviour

While periodontal ligament cells are sensitive to their 3D biomechanical environment, only a few 3D in vitro models have been used to investigate the periodontal cells mechanobiological behavior. The objective of the current study was to assess the capability of a 3D fibrous scaffold to transmit a mechanical loading to the periodontal ligament cells. Three-dimensional fibrous polycaprolactone (PCL) scaffolds were synthetized through electrospinning. Scaffolds seeded with human periodontal cells (103 mL−1) were subjected to static (n = 9) or to a sinusoidal axial compressive loading in an in-house bioreactor (n = 9). At the end of the culture, the dynamic loading seemed to have an influence on the cells’ morphology, with a lower number of visible cells on the scaffolds surface and a lower expression of actin filament. Furthermore, the dynamic loading presented a tendency to decrease the Alkaline Phosphatase activity and the production of Interleukin-6 while these two biomolecular markers were increased after 21 days of static culture. Together, these results showed that load transmission is occurring in the 3D electrospun PCL fibrous scaffolds, suggesting that it can be used to better understand the periodontal ligament cells mechanobiology. The current study shows a relevant way to investigate periodontal mechanobiology using 3D fibrous scaffolds.
Soybean Mosaic Virus 6K1 Interactors Screening and GmPR4 and GmBI1 Function Characterization

Host proteins are essential during virus infection, and viral factors must target numerous host factors to complete their infectious cycle. The mature 6K1 protein of potyviruses is required for viral replication in plants. However, the interaction between 6K1 and host factors is poorly understood. The present study aims to identify the host interacting proteins of 6K1. Here, the 6K1 of Soybean mosaic virus (SMV) was used as the bait to screen a soybean cDNA library to gain insights about the interaction between 6K1 and host proteins. One hundred and twenty-seven 6K1 interactors were preliminarily identified, and they were classified into six groups, including defense-related, transport-related, metabolism-related, DNA binding, unknown, and membrane-related proteins. Then, thirty-nine proteins were cloned and merged into a prey vector to verify the interaction with 6K1, and thirty-three of these proteins were confirmed to interact with 6K1 by yeast two-hybrid (Y2H) assay. Of the thirty-three proteins, soybean pathogenesis-related protein 4 (GmPR4) and Bax inhibitor 1 (GmBI1) were chosen for further study. Their interactions with 6K1 were also confirmed by bimolecular fluorescence complementation (BiFC) assay. Subcellular localization showed that GmPR4 was localized to the cytoplasm and endoplasmic reticulum (ER), and GmBI1 was located in the ER. Moreover, both GmPR4 and GmBI1 were induced by SMV infection, ethylene and ER stress. The transient overexpression of GmPR4 and GmBI1 reduced SMV accumulation in tobacco, suggesting their involvement in the resistance to SMV. These results would contribute to exploring the mode of action of 6K1 in viral replication and improve our knowledge of the role of PR4 and BI1 in SMV response.
Investigation of Unswept Normal Shock Wave/Turbulent-Boundary-Layer Interaction Control

An analytical model for the unswept normal shock wave/turbulent-boundary-layer interaction control using an upstream and downstream unimorph piezoelectric flap actuator has been proposed. The amount of flap deflection controls the bleed/suction rate through a plenum chamber. The cavity allows rapid thickening of the boundary layer approaching a normal shock wave, which splits into a series of weaker shocks forming a lambda shock foot, leading to a reduction in the wave drag. The analysis provides an understanding of the control influences produced in an experimental investigation of an unswept normal shock wave/turbulent-boundary-layer interaction at a Mach number of 1.5. It has also been validated by application to the normal shock wave/boundary-layer interaction control system using mesoflaps for aeroelastic transpiration described in previous transonic/supersonic shock wave/ boundary-layer interaction studies.
Floquet Theory for Partial Differential Equations

CONTENTSIntroduction Chapter I. Preparatory results ? 1. The cokernel of a Fredholm morphism in spaces of sections ? 2. The cokernel of a Fredholm morphism in spaces of sections with bounds Chapter II. The Floquet expansion of solutions of an elliptic equation on the whole space ? 1. Spaces and transformations ? 2. Transformations of operators. Floquet solutions. Multipliers. Quasi-impulses ? 3. Floquet expansion of solutions Chapter III. Properties of the solutions of periodic equations ? 1. The disposition of multipliers and decreasing solutions ? 2. Solubility of the non-homogeneous equation. Bloch's theorem ? 3. Dichotomy ? 4. The dispersion law Chapter IV. Other classes of periodic equations and boundary-value problems ? 1. Elliptic systems ? 2. Hypoelliptic equations and systems ? 3. Elliptic boundary-value problems ? 4. Parabolic boundary-value problems ? 5. The abstract evolution equation ? 6. Pseudodifferential equations ? 7. Relaxation of the conditions on the smoothness of the coefficients ? 8. Equations with deviating argument Comments References
Merely liberals? Du Bois and Plaatje as radical critics of racial capitalism

ABSTRACT A wide range of scholars ratified Du Bois’ Black Reconstruction as his radical turn. Prior to its publication, “liberal” was an epithet used in reference to his work. Across the Atlantic, Plaatje’s Native Life invoked his appellation as a “Black Victorian”. As a counter, this article argues that both intellectuals, who were in communication and whose work resonated with each other, understood the historical development of modern capitalism as an “extension” of an old racialised system. Common threads are found through their analysis; firstly, capitalism required and depended on the exploitation of Black labour. Secondly, the Land dispossession of Black people was a congruent rationale for the accumulation and expansion of capitalism. Lastly, the making of Black people as inferior is entangled with salvaging the white working class. Thus, Plaatje and Du Bois articulated this historical development within the problematic of racial capitalism.
License Plate Recognition Methods Employing Neural Networks

Advances in both parallel processing capabilities because of graphical processing units (GPUs) and computer vision algorithms have led to the development of deep neural networks (DNN) and their utilization in real-world applications. Starting from the LeNet-5 architecture of the 1990s, modern deep neural networks may have tens to hundreds of layers to solve complex problems such as license plate detection or recognition tasks. In this article, we present a review of the state-of-the-art methods related to automatic license plate recognition. Since deep networks have demonstrated a remarkable ability to outperform other machine learning techniques, we focus only on neural network based license plate recognition methods. We highlight the particular types of networks, i.e., convolutional, residual recurrent, or long-short-term-memory, used for the specific tasks of license plate detection, extraction, or recognition in different existing works. The presented summary also highlights some of the most widely used data sets for comparison and shares the results reported in the reviewed papers. We also give an overview of the effects of fog, motion, or the use of synthetic data on license plate recognition. Finally, promising directions for future research in this domain are presented.
Strange particle production in proton-carbon interactions at 31 GeV/c

Spectra of positively charged kaons in p+C interactions at 31 GeV/c have been measured with the NA61/SHINE spectrometer at CERN SPS. The analysis is performed on the dataset collected during the 2007 pilot run (about 678×103 events). The target is a 2 cm long graphite specimen (4% of a nuclear interaction length λI). Charged pion spectra have been already measured with the same dataset [1]. Pion and kaon differential production cross sections are required to improve predictions of the neutrino flux for the T2K long baseline neutrino oscillation experiment in Japan. The knowledge of kaon production is especially important for the precise prediction of the intrinsic electron neutrino component of the T2K beam. The results are presented as a function of laboratory momentum in 2 intervals of the laboratory polar angle covering the range from 20 up to 240 mrad. Kaon spectra as well as K+/π+ ratios are compared with predictions of several hadron production models. In addition, first results from the analysis of the high statistics 2009 data taking are shown.
Multi-component image segmentation using a hybrid dynamic genetic algorithm and fuzzy C-means

Image segmentation is an important task in image analysis and processing. Many of the existing methods for segmenting a multi-component image (satellite or aerial) are very slow and require a priori knowledge of the image that could be difficult to obtain. Furthermore, the success of each of these methods depends on several factors, such as the characteristics of the acquired image, resolution limitations, intensity in-homogeneities and the percentage of imperfections induced by the process of image acquisition. Recently, fuzzy C-means (FCM) and Genetic Algorithms were separately used in segmenting multi-component images but neither of them had successfully addressed the above concerns. GA was enhanced using Hill-climbing, randomising, and modified mutation operators, leading to what is called hybrid dynamic genetic algorithm (HDGA). Coupling HDGA and FCM creates an unsupervised segmentation method which could successfully segment two types of multi-component images (Landsat ETM+, and IKONOS II). Comparison with the four different methods FCM, hybrid genetic algorithm (HGA), self-organizing-maps (SOM), and the combination of SOM and HGA (SOM-HGA) reveals that FCM-HDGA segmentation method gives robust and reliable results, and is more time efficient.
Metabolic behavior for a mutant Oenococcus oeni strain with high resistance to ethanol to survive under oenological multi-stress conditions

Malolactic fermentation (MLF) positively influences the quality of the wine, and it occurs as a result of a lactic acid bacteria’s metabolism, mainly of the Oenococcus oeni species. However, delays and halting of MLF are frequent problems in the wine industry. This is mainly because O. oeni’s development is inhibited by different kinds of stress. Even though the sequencing of the genome of the PSU-1 strain of O. oeni, as well as other strains, has made it possible to identify genes involved in the resistance to some types of stress, all of the factors that could be involved are still unknown. With the aim of contributing to this knowledge, the random mutagenesis technique was used in this study as a strategy for genetic improvement of strains of the O. oeni species. The technique proved to be capable of generating a different and improved strain when compared to the PSU-1 strain (the parent from which it descends). Then, we evaluated the metabolic behavior of both strains in three different wines. We used synthetic MaxOeno wine (pH 3.5; 15% v/v ethanol), red wine (Cabernet Sauvignon), and white wine (Chardonnay). Furthermore, we compared the transcriptome of both strains, grown in MaxOeno synthetic wine. The specific growth rate of the E1 strain was on average 39% higher in comparison to the PSU-1 strain. Interestingly, E1 strain showed an overexpression of the OEOE_1794 gene, which encodes a UspA-like protein, which has been described as promoting growth. We observed that the E1 strain was able to convert, on average, 34% more malic acid into lactate than the PSU-1 strain, regardless of the wine being used. On the other hand, the E1 strain showed a flux rate of fructose-6-phosphate production that was 86% higher than the mannitol production rate, and the internal flux rates increase in the direction of pyruvate production. This coincides with the higher number of OEOE_1708 gene transcripts observed in the E1 strain grown in MaxOeno. This gene encodes for an enzyme fructokinase (EC 2.7.1.4) involved in the transformation of fructose to fructose-6-phosphate.