Miracle-dz/UniFAR-FTUs huggingface dataset:
Sleep and delinquency: The context of self-control, social support, and sex differences among French adolescents

Prior research demonstrates that poor sleep is an important predictor of delinquent behavior among adolescents. Engagement in delinquency is linked to a range of negative mental and physical health outcomes over the life course, underscoring a critical need to address adolescent sleep problems to reduce delinquency. However, little scholarly attention has been paid to how the broader context of social support influences the sleep–delinquency relationship. In this study, we analyze a series of structural equation models using a sample of 447 French adolescents to examine how parental and peer support correspond to three related aspects of sleep among adolescents (quantity, quality, and the frequency of sleep disturbance) with implications for delinquency. Furthermore, we assess how sex differences moderate the relationship between social support and sleep. First, we find that all three indicators of sleep are associated with delinquency, significantly mediated by reductions in self-control. Second, both peer and parental support correspond to sleep outcomes with full sequential mediation evident for sleep quality and delinquency. Finally, we find significant differences in the relationship between social support and all sleep indicators for boys and girls. Peer support is more strongly associated with sleep among boys, whereas parental support is more strongly associated with sleep among girls. We discuss the implications of these findings for improving adolescent sleep to reduce delinquency as well as opportunities for future research.
Staphylococcus aureus ST1 promotes persistent urinary tract infection by highly expressing the urease

Staphylococcus aureus (SA) is a relatively uncommon cause of urinary tract infections (UTIs) in the general population. Although rare, S. aureus-induced UTIs are prone to potentially life-threatening invasive infections such as bacteremia. To investigate the molecular epidemiology, phenotypic characteristics, and pathophysiology of S. aureus-induced UTIs, we analyzed non-repetitive 4,405 S. aureus isolates collected from various clinical sources from 2008 to 2020 from a general hospital in Shanghai, China. Among these, 193 isolates (4.38%) were cultivated from the midstream urine specimens. Epidemiological analysis showed UTI-derived ST1 (UTI-ST1) and UTI-ST5 are the primary sequence types of UTI-SA. Furthermore, we randomly selected 10 isolates from each of the UTI-ST1, non-UTI-ST1 (nUTI-ST1), and UTI-ST5 groups to characterize their in vitro and in vivo phenotypes. The in vitro phenotypic assays revealed that UTI-ST1 exhibits an obvious decline in hemolysis of human red blood cells and increased biofilm and adhesion in the urea-supplemented medium, compared to the medium without urea, while UTI-ST5 and nUTI-ST1 did not show significant differences between the biofilm-forming and adhesion abilities. In addition, the UTI-ST1 displayed intense urease activities by highly expressing urease genes, indicating the potential role of urease in UTI-ST1 survival and persistence. Furthermore, in vitro virulence assays using the UTI-ST1 ureC mutant showed no significant difference in the hemolytic and biofilm-forming phenotypes in the presence or absence of urea in the tryptic soy broth (TSB) medium. The in vivo UTI model also showed that the CFU of the UTI-ST1 ureC mutant rapidly reduced during UTI pathogenesis 72 h post-infection, while UTI-ST1 and UTI-ST5 persisted in the urine of the infected mice. Furthermore, the phenotypes and the urease expression of UTI-ST1 were found to be potentially regulated by the Agr system with the change in environmental pH. In summary, our results provide important insights into the role of urease in S. aureus-induced UTI pathogenesis in promoting bacterial persistence in the nutrient-limiting urinary microenvironment.
Disjunctive games with the last player losing

Various authors have discussed the ‘disjunctive compound’ of games with the last player winning (Grundy(2); Guy and Smith (3); Smith (4)). We attempt here to analyse the disjunctive compound with the last player losing, though unfortunately with less complete success. The problem was explored tentatively by the first named author, but the rigorous development is due to the second.
Master-slave synchronization using dynamic output feedback

A method of linear dynamic output feedback for master-slave synchronization of two identical Lur'e systems is introduced. In this scheme, synchronization is obtained using one or at least fewer measurement signals and control signals than the number of state variables of the Lur'e system. A sufficient condition for global asymptotic stability of the error system is derived from a quadratic Lyapunov function and is expressed as a matrix inequality. The dynamic controller is designed by solving a constrained nonlinear optimization problem. The method is demonstrated on Chua's circuit and a hyperchaotic circuit consisting of 2-double scroll cells.
Measurements of surface defects on optical components

An objective scanning optical microscope technique to inspect the surfaces of optical components for imperfections (ranging from sub-micrometre to several micrometres in size) would replace the subjective methods currently in use by human quality controllers. Some laboratory microscope systems have been developed but they are too expensive and complex to be used on production lines. The atomic force microscope, with its image analysis software, has proved to be ideal for characterizing scratches and digs which, it is hoped, will assist the development of simpler optical microscope systems. The atomic force microscope images are repeated by the scanning electron microscope micrographs and both have their particular merits. The Form Talysurf was found to have insufficient resolution for the smallest unacceptable scratches and digs but could measure the waviness and form of large components.
A New Family of Macrocyclic Polyamino Biphenolic Ligands: Acid-Base Study, Zn(II) Coordination and Glyphosate/AMPA Binding

In this study, the ligands 23,24-dihydroxy-3,6,9,12-tetraazatricyclo[17.3. 1.1(14,18)]eicosatetra-1(23),14,16,18(24),19,21-hexaene, L1, and 26,27-dihidroxy-3,6,9,12,15-pentaazatricyclo[20.3. 1.1(17,21)]eicosaepta-1(26),17,19,21(27),22,24-hexaene, L2, were synthesized: they represent a new class of molecules containing a biphenol unit inserted into a macrocyclic polyamine fragment. The previously synthesized L2 is obtained herein with a more advantageous procedure. The acid-base and Zn(II)-binding properties of L1 and L2 were investigated through potentiometric, UV-Vis, and fluorescence studies, revealing their possible use as chemosensors of H+ and Zn(II). The new peculiar design of L1 and L2 afforded the formation in an aqueous solution of stable Zn(II) mono (LogK 12.14 and 12.98 for L1 and L2, respectively) and dinuclear (LogK 10.16 for L2) complexes, which can be in turn exploited as metallo-receptors for the binding of external guests, such as the popular herbicide glyphosate (N-(phosphonomethyl)glycine, PMG) and its primary metabolite, the aminomethylphosphonic acid (AMPA). Potentiometric studies revealed that PMG forms more stable complexes than AMPA with both L1- and L2-Zn(II) complexes, moreover PMG showed higher affinity for L2 than for L1. Fluorescence studies showed instead that the L1-Zn(II) complex could signal the presence of AMPA through a partial quenching of the fluorescence emission. These studies unveiled therefore the utility of polyamino-phenolic ligands in the design of promising metallo-receptors for elusive environmental targets.
Determination of the instantaneous forces on flapping wings from a localized fluid velocity field

Expressions are derived to relate the instantaneous pressure force on a flapping wing to the velocity field on a plane at the trailing edge and on a highly localized region around and near the wing, valid when the vortex sheet is thin. In its more practical version, the formalism is applicable to wings with close to two-dimensional geometry and has the advantage of not using spatial derivatives, but only a time derivative of a surface integral of the velocity. In the purely two-dimensional case, the expression obtained is used to justify a much simpler one that only requires the evaluation of the time derivative of the wing circulation. A comparison with a numerical simulation in a two-dimensional case shows a good representation of the forces, even with the most simplified expression, when the condition of a thin wake is met. Other examples are shown in which the wake is not thin in order to explore the limitations of the formalism. It is found in these cases that the thrust is sometimes not so well repr.
Environmental Impact of Two Plant-Based, Isocaloric and Isoproteic Diets: The Vegan Diet vs. the Mediterranean Diet

Food consumption is one of the major causes of climate change, resource depletion, loss of biodiversity, and other kinds of environmental impact by modern households. According to evidence, a global change in dietary habits could be the single most effective and rapid intervention to reduce anthropic pressure on the planet, especially with respect to climate change. Our study applied Life Cycle Assessment (LCA) to investigate the total environmental impact of two plant-based diets: the Mediterranean and the Vegan diets, according to relevant Italian nutritional recommendations. The two diets share the same macronutrient rates and cover all the nutritional recommendations. Calculations were made on the basis of a theoretical one-week 2000 kcal/day diet. According to our calculations, the Vegan diet showed about 44% less total environmental impact when compared to the Mediterranean diet, despite the fact that the content of animal products of the latter was low (with 10.6% of the total diet calories). This result clearly supports the concept that meat and dairy consumption plays a critical role, above all, in terms of damage to human health and ecosystems. Our study supports the thesis that even a minimal-to-moderate content of animal foods has a consistent impact on the environmental footprint of a diet, and their reduction can elicit significant ecological benefits.
Algorithm Based on the Vertex Similarity of the Network for Detecting Community Structure

In order to quickly and accurately find the community structure of complex networks ,This article start from the similarity of the node ,Proposed a new community discovery algorithm. Introduced similar values and custom node value Q during the process of algorithm design ,Firstly , To Select the nodes with the largest similarity value by calculating the similarity between nodes ,Then to decide to join and expand the nodes by calculating the Q value is greater than 0 or not. Repeat the above process, you can get the whole network of community structure, The process does not require any auxiliary information or other seed nodes. Applied to the actual network experiment results verify the feasibility of the algorithm.
A review of mixture modeling techniques for sub‐pixel land cover estimation

Abstract Five different types of mixture models are reviewed. These are: linear, probabilistic, geometric‐optical, stochastic geometric, and fuzzy models. A summary of the conception and formulation of each of these types of models is presented. A comparative analysis of the different attributes of the models is made. In a general sense, the linear, probabilistic, and fuzzy models are relatively simple while the geometric (geometric‐optical and stochastic geometric) models are complicated, involving the incorporation of parameters of scene geometry. There is some difference in the number and nature of components that can be resolved with the different models. Available information is insufficient to categorize the models in terms of accuracy levels, but it is evident that mixture models produce more accurate land‐cover estimation than conventional classification.
Identification of Box-Jenkins Models Using Structured ARX Models and Nuclear Norm Relaxation

In this contribution we present a method to estimate structured high order ARX models. By this we mean that the estimated model, despite its high order is close to a low order model. This is achieved by adding two terms to the least-squares cost function. These two terms correspond to nuclear norms of two Hankel matrices. These Hankel matrices are constructed from the impulse response coefficients of the inverse noise model, and the numerator polynomial of the model dynamics, respectively. In a simulation study the method is shown to be competitive as compared to the prediction error method. In particular, in the study the performance degrades more gracefully than for the Prediction Error Method when the signal to noise ratio decreases.
Electromagnetic effects on the inhomogeneity of planar symmetry

In this work, we aim to identify the effects of electromagnetic field on the energy density inhomogeneity in self-gravitating plane symmetric spacetime filled with imperfect matter in terms of dissipation and anisotropic pressure. We formulate the Einstein–Maxwell field equation, conservation laws, evolution equations for the Weyl tensor and the transport equation for diffusion approximation. Inhomogeneity factors are identified for some particular cases of non-dissipative and dissipative fluids. For non-dissipative case, we analyze the inhomogeneity factor for dust, isotropic and anisotropic matter distributions while dissipative matter distribution includes the inhomogeneity factor only for geodesic dust fluid. We conclude that electric charge increases the inhomogeneity in the energy density which is due to shear, anisotropy and dissipation.
Changes in the Sensory Odor Profile during Chorizo Maturation and Their Relationship with Volatile Compound Patterns by Partial Least Square Regression (PLS)

Odor is one of the most important attributes to determine the overall acceptance of a product. The aim of this investigation is to evaluate the changes in the odor profile and the volatile compounds during thirty-three days of ripening to obtain the pattern of volatile compounds necessary to integrate the odor profile of chorizo (fermented sausage), using Partial Least Squares (PLS). The chili and pork meat odors were predominant during the first five days, vinegar and fermented odors at days twelve and nineteen days, and finally a rancid odor predominated at the end. Only the vinegar, rancid, and fermented odors could be predicted with a good fit model, with the R2 coefficient above 0.5, using linear PLS, and the pork meat odor using logarithmic PLS. Each group of volatile compounds interacted in different ways; esters had a positive influence on the vinegar and rancid odors, but a negative on the fermented odor. Some volatile compounds contributed to more than one odor, such as hexanal, ethanol, and ethyl octanoate. This work allowed us to understand the pattern of volatile compounds required to generate some of the specific odors of chorizo; further studies are required to explore the effect of other food components on these patterns of odors.
A Robust Strategy to Account for Data Sampling Variability in the Development of Hydrological Models

It is typical to use a single portion of the available data to calibrate hydrological models, and the remainder for model evaluation. To minimize model‐bias, this partitioning must be performed so as to ensure distributional representativeness and mutual consistency. However, failure to account for data sampling variability (DSV) in the underlying Data Generating Process can weaken the model's generalization performance. While “K‐fold cross‐validation” can mitigate this problem, it is computationally inefficient since the calibration/evaluation operations must be repeated numerous times. This paper develops a general strategy for stochastic evolutionary parameter optimization (SEPO) that explicitly accounts for DSV when calibrating a model using any population‐based evolutionary optimization algorithm (EOA), such as Shuffled Complex Evolution (SCE). Inspired in part by the machine‐learning strategy of stochastic gradient descent (SGD), we use various representative random sub‐samples to drive the EOA toward the distribution of the model parameters. Unlike in SGD, derivative information is not required and hence SEPO can be applied to any hydrological model where such information is not readily available. To demonstrate the effectiveness of the proposed strategy, we implement it within the well‐known SCE, to calibrate the GR4J conceptual rainfall‐runoff model to 163 hydro‐climatically diverse catchments. Using only a single optimization run, our Stochastic SCE method converges to population‐based estimates of model parameter distributions (and corresponding simulation uncertainties), without compromising model performance during either calibration or evaluation. Further, it effectively reduces the need to perform independent evaluation tests of model performance under conditions that are represented by the available data.
Oxidative Stress and Inflammation in Acute and Chronic Lung Injuries

Acute and chronic lung injuries are among the leading causes of mortality worldwide. Lung injury can affect several components of the respiratory system, including the airways, parenchyma, and pulmonary vasculature. Although acute and chronic lung injuries represent an enormous economic and clinical burden, currently available therapies primarily focus on alleviating disease symptoms rather than reversing and/or preventing lung pathology. Moreover, some supportive interventions, such as oxygen and mechanical ventilation, can lead to (further) deterioration of lung function and even the development of permanent injuries. Lastly, sepsis, which can originate extrapulmonary or in the respiratory system itself, contributes to many cases of lung-associated deaths. Considering these challenges, we aim to summarize molecular and cellular mechanisms, with a particular focus on airway inflammation and oxidative stress that lead to the characteristic pathophysiology of acute and chronic lung injuries. In addition, we will highlight the limitations of current therapeutic strategies and explore new antioxidant-based drug options that could potentially be effective in managing acute and chronic lung injuries.
Biomimetic Nanotechnology for SARS-CoV-2 Treatment

More than 600 million people worldwide have been infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in the pandemic of coronavirus disease 2019 (COVID-19). In particular, new waves of COVID-19 caused by emerging SARS-CoV-2 variants pose new health risks to the global population. Nanotechnology has developed excellent solutions to combat the virus pandemic, such as ACE2-based nanodecoys, nanobodies, nanovaccines, and drug nanocarriers. Lessons learned and strategies developed during this battle against SARS-CoV-2 variants may also serve as inspiration for developing nanotechnology-based strategies to combat other global infectious diseases and their variants in the future.
Semi‐parametric estimation of covariate effects using the positive stable frailty model

Many biological and medical studies have as a response of interest the time to occurrence of some event, such as the occurrence of a particular symptom or disease, remission, relapse, death due to some specific disease, or simply death. In this paper we study the problem of assessing the effect of potential risk factors on the outcome event of interest through a parametric or semi-parametric frailty model where the lifetimes have a reason to be considered dependent. This dependence may arise because of multiple endpoints within the same individual or because, when studying a single endpoint, there are natural groupings between study subjects. The objective of this paper is to extend both parametric and semi-parametric approaches to regression analysis in which the lifetimes of individuals in a group are effected by the same random frailty which follows a positive stable distribution. Some comparisons of the properties of this frailty distribution with other frailty distributions are made and an example which assesses the effect of a treatment in a litter-matched tumorigenesis study is presented.
Dynamic Output Feedback Fault Tolerant Control for Switched Fuzzy Systems With Fast Time Varying and Unbounded Faults

This article focuses on the fault reconstruction and fault-tolerant control problems of switched fuzzy systems with actuator and sensor faults, where the faults may be fast time-varying and unbounded. The multiple coordinate transformations are introduced, then the reduced-order observer based fault reconstruction method is considered, which can reconstruct the system state, actuator, and sensor faults, simultaneously. For the case that there is no disturbance, the LMI conditions are achieved to ensure that for any switching signal, the error dynamics can be exponentially stable. Utilizing the estimated fault information, the fuzzy dynamic output feedback fault tolerant controllers are designed to compensate the fault effect and stabilize the systems. The root-mean-square gain is considered to reduce the disturbance influence on fault estimation and fault-tolerant control, in which the zero initial condition is not needed. Finally, simulations are conducted to demonstrate the effectiveness of the considered techniques.
Latent Variable Models of Genotype-Environment Covariance

This study was concerned with the identification of genotype-environment covariance (CovGE) on measures of work-related variables. Two approaches to the estimation of CovGE were used, 1 based on a univariate behavior genetic model and the other based on a bivariate behavior genetic model. The sample consisted of 136 pairs of identical twins reared together, 175 pairs of fraternal twins reared together, 83 pairs of identical twins reared apart, and 182 pairs of fraternal twins reared apart, obtained from the Swedish Adoption/Twin Study of Aging (SATSA). Most of the CovGEs examined were significant, suggesting that (a) failure to specify CovGE in behavior genetic models will lead to bias in the estimates of the other parameters, and (b) CovGE is an important influence on individual difference in the workplace.
Comparison of Methods for Estimating and Testing Latent Variable Interactions

Structural equation modeling methods for estimating and testing hypotheses about an interaction between continuous variables were investigated. The methods were (a) Bollen's (1996) 2-stage least squares (TSLS) method, Ping's (1996) 2-step maximum likelihood (ML) method, and Jaccard and Wan's (1995) ML method for the Kenny-Judd model (Kenny & Judd, 1984); (b) a 2-step ML procedure and ML estimation of the Jöreskog-Yang model (Jöreskog & Yang 1996); and (c) ML estimation of a revised Jöreskog-Yang model. The TSLS procedure exhibited more bias and lower power than the other methods. Under ML estimation of the Jöreskog-Yang model, Type I error rates were not well controlled when robust standard errors were used. Among the remaining procedures, the Jaccard-Wan procedure and ML estimation of the revised Jöreskog-Yang procedure were most effective, with the latter having some small advantages over the former.