Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion/adsorption/advection macrotransport in soils

The aim of this paper is to develop a macroscopic model for pollutant transport in a heterogeneous medium (soil), including diffusion, advection and adsorption. The modelling consists in the derivation of the macroscopic equations governing the average concentration field in the equivalent medium as well as the determination of the macroscopic (equivalent) transport parameters. The models proposed herein have been deduced using the homogenization technique (the double scale asymptotic development analysis), in which the small parameter e is the ratio between two characteristic lengths I (the pore scale) and L (the sample scale). This approach is rigorous in the sense that no prerequisites are imposed on the macroscopic models. The macroscopic parameters depend solely on the microscopic transport parameters and the microscopic geometrical properties of the medium. The important issue that has also been adressed is the existence of problems called non-homogenizable. In such cases the equivalent continuum and the intrinsic equivalent characteristics do not exist. Although one can always perform an experiment trying to evaluate the macroscopic behavior but in a non-homogenizable situation the result obtained will be restricted to a particular case considered and will not be applicable to the site conditions. As an example, the flow of a pollutant in a layered porous medium is considered and the dispersion-adsorption coefficient is calculated. Finally, the concepts introduced in the paper are discussed with respect to available experimental information.
Construction and Assessment of a Prognostic Risk Model for Cervical Cancer Based on Lactate Metabolism-Related lncRNAs

Purpose Cervical cancer (CC) has the fourth highest incidence and mortality rate among female cancers. Lactate is a key regulator promoting tumor progression. Long non-coding RNAs (lncRNAs) are closely associated with cervical cancer (CC). The study was aimed to develop a prognostic risk model for cervical cancer based on lactate metabolism-associated lncRNAs and to determine their clinical prognostic value. Patients and Methods In this study, CESC transcriptome data were obtained from the TCGA database. 262 lactate metabolism-associated genes were extracted from MsigDB (Molecular Characterization Database). Then, correlation analysis was used to identify LRLs. Univariate Cox regression analysis was performed afterwards, followed by least absolute shrinkage and selection operator (LASSO) regression analysis and multiple Cox regression analysis. 10 lncRNAs were finally identified to construct a risk score model. They were divided into two groups of high risk and low risk according to the median of risk scores. The predictive performance of the models was assessed by Kaplan-Meier (K-M) analysis, subject work characteristics (ROC) analysis, and univariate and multivariate Cox analyses. To assess the clinical utility of the prognostic model, we performed functional enrichment analysis, immune microenvironment analysis, mutation analysis, and column line graph generation. Results We constructed a prognostic model consisting of 10 LRLs at CC. We observed that high-risk populations were strongly associated with poor survival outcomes. Risk score was an independent risk factor for CC prognosis and was strongly associated with immune microenvironment analysis and tumor mutational load. Conclusion We developed a risk model of lncRNAs associated with lactate metabolism and used it to predict prognosis of CC, which could guide and facilitate the progress of new treatment strategies and disease monitoring in CC patients.
A Figure-Ground Discrimination Algorithm Inspired by Border-Ownership Selective Cells

We developed a figure-ground discrimination algorithm that is suitable for robot vision. The algorithm is inspired by the response properties of border-ownership (BO)-selective cells, which possibly support figure-ground discrimination in the visual nervous system. The output of our algorithm is affected by spatial parameters such as the characteristics of the spatial filter used for edge enhancement and the interval of model BO-selective cells. Therefore, we investigated the relationship between the algorithm output with various spatial parameters and object sizes
Cone-beam x-ray luminescence computed tomography reconstruction from single-view based on total variance

As an emerging hybrid imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) has been proposed based on the development of X-ray excitable nanoparticles. Fast three-dimensional (3-D) CB-XLCT imaging has attracted significant attention for the application of XLCT in fast dynamic imaging study. Currently, due to the short data collection time, single-view CB-XLCT imaging achieves fast resolving the three-dimensional (3-D) distribution of X-ray-excitable nanoparticles. However, owing to only one angle projection data is used in the reconstruction, the single-view CB-XLCT inverse problem is inherently ill-conditioned, which makes image reconstruction highly susceptible to the effects of noise and numerical errors. To solve the ill-posed inverse problem, using the sparseness of the X-ray-excitable nanoparticles distribution as the prior, a new reconstruction approach based on total variance is proposed in this study. To evaluate the performance of the proposed approach, a phantom experiment was performed based on a CB-XLCT imaging system. The experiments indicate that the reconstruction from single-view XCLT can provide satisfactory results based on the proposed approach. In conclusion, with the reconstruction approach based on total variance, we implement a fast XLCT reconstruction of high quality with only one angle projection data used, which would be helpful for fast dynamic imaging study. In future, we will focus on how to applying the proposed TV-based reconstruction method and CB-XLCT imaging system to image fast biological distributions of the X-ray excitable nanophosphors in vivo.
Passive Flow Control Application Using Single and Double Vortex Generator on S809 Wind Turbine Airfoil

The current study is aimed at investigating the influences of vortex generator (VG) applications mounted to the suction and pressure surfaces of the S809 wind turbine airfoil at low Reynolds number flow conditions. Both single and double VG applications were investigated to provide technological advancement in wind turbine blades by optimizing their exact positions on the surface of the airfoil. The results of the smoke-wire experiment for the uncontrolled case reveal that a laminar separation bubble formed near the trailing edge of the suction surface, and it was moved towards the leading edge as expected when the angle of attack was increased, resulting in bubble burst and leading-edge flow separation at α = 12°. The u/U∞, laminar kinetic energy and total fluctuation energy contours obtained from the numerical study clearly show that both the single and double VG applications produced small eddies, and those eddies in the double VG case led the flow to be reattached at the trailing edge of the suction surface and to gain more momentum by energizing. This situation was clearly supported by the results of aerodynamic force; the double VG application caused the lift coefficient to increase, resulting in an enhancement of the aerodynamic performance. A novel finding is that the VG at the pressure surface caused the flow at the wake region to gain more energy and momentum, resulting in a reattached and steadier flow condition.
Analysis of best practices for interactive content design and development for digital communication

Introduction. Several authors practice and disseminate good practices related to interactivity and agile, and from different areas and disciplines, as part of their activities, but few integrate them to develop projects. Objective. This paper presents the results of a review in which the level of dissemination of good practices related to these areas and those proposed for structuring, designing, and evaluating interactive content are investigated. Method. To conduct reliable literature reviews, it is necessary to build an initial protocol in which the research methodology is structured. Results. The final sample is made up of 100 works distributed mainly among articles, presentations at events, and online contributions. It was found that 47 % of the researchers publish about good practices to indicate an area or discipline of application, while 21 % describe them from interactivity and 24 % from agile. Conclusions. Furthermore, the good practices found are the result of personal experiences, not general validations, which makes it impossible to conclude whether they are really good.
Flexible Capacitive Kirigami Electrode: Experimental Investigation and Analytical Model

Flexible electronics have recently garnered increasing attention due to their promise for a wide range of applications, from energy storage to flexible screens, over sensors to wearables. The trend in flexible electronics is toward the fabrication of devices composed of fully flexible materials and components. However, flexible devices still present many limitations, primarily due to the negative Poisson ratio of the materials used, which affects the dimensions and characteristics of the materials when bent or stretched. In this work, we propose a novel design for capacitive electrodes aimed to improve the flexibility of devices without affecting the properties of the materials involved: the design is based on Kirigami, the traditional Japanese art of paper cutting which, when applied to engineering, enables the shaping of stretchable and deformable structures by performing simple cuts on traditional substrates and films, thereby ensuring compatibility with existing manufacturing methods. We formulate a novel analytical model to explain in detail the behavior of the Kirigami electrode applied to an arbitrary nonflat surface. The efficacy of the novel design has been verified by means of capacitive measurements in different nonflat configurations: the results obtained confirm both the validity of the analytical model and the robustness of the novel Kirigami approach, with capacitive values increasing up to 115% for the Kirigami electrode compared to the non-Kirigami one.
A Bivariate Weibull Family with Applications

SYNOPTIC ABSTRACT In reliability theory, Weibull distribution is extensively employed for modelling lifetime data and is considered as a versatile family of life distributions. In this article, we derive a family of bivariate Weibull distributions and study its properties. The general form of the copula is Archimedean, which is popularly used in empirical modeling. The dependency structure of the family is investigated. Finally, the family of distributions is applied to two real life data sets.
Frecuencia serológica de Toxoplasma gondii en gatos domésticos provenientes de albergues de Lima Metropolitana

El objetivo del estudio fue determinar la frecuencia de anticuerpos serológicos de Toxoplasma gondii en gatos domésticos (Felis silvestris catus) provenientes de albergues de Lima Metropolitana. Para ello se diseñó un estudio observacional descriptivo de corte transversal, seleccionando 125 gatos de albergues localizados en los distritos de Lurín, Miraflores y Santiago de Surco. Los animales escogidos eran adultos, de ambos sexos, sin distinción de su condición sanitaria, y elegidos de manera proporcional y aleatoria en cada albergue. Las muestras de sangre (1 mL) fueron procesadas mediante la prueba de hemoaglutinación indirecta para la detección serológica de anticuerpos IgG e IgM contra T. gondii. La frecuencia de anticuerpos IgG contra T. gondii fue de 15.2 %, mientras que la de anticuerpos IgM contra T. gondii fue de 3.2 %. Se observó una asociación significativa entre la edad del gato y lafrecuencia serológica de T. gondii. Al utilizar la prueba de chi cuadrado, no se observó asociación entre el restode las características de los animales en estudio y las variables epidemiológicas recopiladas con la positividadserológica de T. gondii.
Decoding Argentina's path to World Cup glory: Unveiling the winning factors in match result analysis

The use of technology in evaluating the results of football matches has been used in various countries. This study aimed to identify and analyze the match results of the Argentina national team as the 2022 World Cup champion team. This research was a descriptive quantitative research that was analyzed in statistical form. The data sources were collected by the researcher by analyzing statistical data and video recordings of matches from the official FIFA website, Whoscored and Vidio. A total of 7 matches had been played by the Argentina national team in the 2022 World Cup competition, analyzed in terms of goals, ball possession, attempts at goal, direction of attack, distribution and defense. The results showed that most goals were scored in the 31-45th minute and most conceded in the 76-90 th minute, with the most ways being open play, most goals scored in area 3 with the striker being the top scorer. Argentina is quite dominant and controls the match in ball possession, attempt on target and total distribution (passing success, crossing success, and line breaks success) in every match with many attacks started from the right. When carrying out defensive pressure and tackles, Argentina is also more effective than its opponent. In this study, it could be concluded that the parameters to achieve victory were not only from ball possession, attempt success, and passing success but also seen from distribution parameters (crossing and line break success) and defensive parameters, especially defensive pressure which was also an indicator of team success in a match. It is hoped that in the future there will be further research discussing the successful journey of a team in several competitions followed by analysis parameters that are not much different, especially with a more detailed analysis of distribution and defense systems.
Changing times and subjective well-being in urban China 2003–2013: An age-period-cohort approach

This paper analyzes the intersection of individual lives and historical context by examining how cohort membership, historical conditions, and individual maturation influence subjective well-being in urban China. We use cross-classified multilevel models and repeated measures of happiness from seven waves of the Chinese General Social Survey (CGSS 2003–2013, N = 43,308). The results indicate that individuals born between 1956 and 1961 experienced setbacks at various pivotal moments throughout their life, including education, employment, economic stability, and social connections, and this cohort reports a lower overall sense of happiness when compared to other cohorts. The effect of aging on happiness comprises a U-shaped pattern; the middle-aged are the least happy. We observe an upward trend in happiness from 2003 to 2013. These results are confirmed by using subjective socioeconomic status (SES) as an alternative measure of well-being from CGSS 2003 and CGSS 2005 (N = 11,992). This paper contributes to studies of market transition by identifying the birth cohort as an important mechanism of inequality. It also augments the life-course paradigm by highlighting the significance of timing when individual lives intersect with historical context.
Metáforas sobre a maternidade: uma análise cognitivo-discursiva sobre acórdãos proferidos em recursos sobre a destituição do poder familiar materno

de. Este artigo propõe-se a uma análise do uso feito, em processos judiciais, das leis sobre o exercício da maternidade, por meio da identificação das metáforas sobre as mães em decisões proferidas em graus de recurso em ações de destituição do poder familiar. Utilizou-se não só os estudos seminais de Lakoff e Johnson (2002), mas também a Abordagem da Análise do Discurso à Luz da Metáfora (Cameron, 1999; CAMERON et al., 2009; CAMERON, LARSEN-FREEMAN, 2007), para identificar as metáforas sobre a maternidade, com a concepção de que a teoria da argumentação jurídica deve ser construída interdisciplinarmente, com o auxílio dos estudos sobre o discurso desenvolvidos pela linguística. Tal abordagem alinha-se à perspectiva interdisciplinar nas ciências humanas e sociais (PEDERSON, 2016). As metáforas identificadas indicaram o uso de noções do senso comum sobre a maternidade como fundamento da destituição do poder familiar materno, contrariando os princípios constitucionais da igualdade e da não discriminação.
The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies

Abstract. The ocean mixed layer is the interface between the ocean interior and the atmosphere or sea ice and plays a key role in climate variability. It is thus critical that numerical models used in climate studies are capable of a good representation of the mixed layer, especially its depth. Here we evaluate the mixed-layer depth (MLD) in six pairs of non-eddying (1∘ grid spacing) and eddy-rich (up to 1/16∘) models from the Ocean Model Intercomparison Project (OMIP), forced by a common atmospheric state. For model evaluation, we use an updated MLD dataset computed from observations using the OMIP protocol (a constant density threshold). In winter, low-resolution models exhibit large biases in the deep-water formation regions. These biases are reduced in eddy-rich models but not uniformly across models and regions. The improvement is most noticeable in the mode-water formation regions of the Northern Hemisphere. Results in the Southern Ocean are more contrasted, with biases of either sign remaining at high resolution. In eddy-rich models, mesoscale eddies control the spatial variability in MLD in winter. Contrary to a hypothesis that the deepening of the mixed layer in anticyclones would make the MLD larger globally, eddy-rich models tend to have a shallower mixed layer at most latitudes than coarser models do. In addition, our study highlights the sensitivity of the MLD computation to the choice of a reference level and the spatio-temporal sampling, which motivates new recommendations for MLD computation in future model intercomparison projects.
Optimal selection of regularization parameter for ℓ1-based image restoration based on SURE

To exploit the sparsity in transform domain (e.g. wavelets), the image deconvolution can be typically formulated as a ℓ1-penalized minimization problem, which, however, generally requires proper selection of regularization parameter for desired reconstruction quality. The key contribution of this paper is to develop a novel data-driven scheme to optimize regularization parameter, such that the resultant restored image achieves minimum prediction error (p-error). First, we develop Stein's unbiased risk estimate (SURE), an unbiased estimate of p-error, for image degradation model. Then, we propose a recursive evaluation of SURE for the basic iterative shrinkage/thresholding (IST), which enables us to find the optimal value of regularization parameter by exhaustive search. The numerical experiments show that the proposed SURE-based optimization leads to nearly optimal deconvolution performance in terms of peak signal-to-noise ratio (PSNR).
The Impact of Institutional Investors' Shareholding on The Efficiency of Corporate Investment

This study investigates the impact of institutional shareholding on corporate investment efficiency and identifies the role played by information asymmetry as well as agency costs. The results show that (1) institutional shareholding promotes corporate investment efficiency, with state-owned institutions playing a more pronounced role. (2) Institutional investors' shareholding is negatively related to information asymmetry. (3) Institutional investors' shareholding is negatively related to agency costs. (4) Institutional investors' shareholding can improve corporate investment efficiency by reducing corporate information asymmetry and agency costs, which are reflected in reducing corporate information opacity and analysts' forecast divergence.
Metabolomic analysis reveals a differential adaptation process of the larval stages of Anisakis simplex to the host environment

Introduction: Anisakis simplex are parasitic nematodes that cause anisakiasis. The possibility of infection with this parasite is through consumption of raw or undercooked fish products. A. simplex infections are often misdiagnosed, especially in subclinical cases that do not present with typical symptoms such as urticaria, angioedema, and gastrointestinal allergy. The resulting allergic reactions range from rapid-onset and potentially fatal anaphylactic reactions to chronic, debilitating conditions. While there have been numerous published studies on the genomes and proteomes of A. simplex, less attention has been paid to the metabolomes. Metabolomics is concerned with the composition of metabolites in biological systems. Dynamic responses to endogenous and exogenous stimuli are particularly well suited for the study of holistic metabolic responses. In addition, metabolomics can be used to determine metabolic activity at different stages of development or during growth. Materials and methods: In this study, we reveal for the first time the metabolomes of infectious stages (L3 and L4) of A. simplex using untargeted metabolomics by ultra-performance liquid chromatography-mass spectrometry. Results: In the negative ionization mode (ESI-), we identified 172 different compounds, whereas in the positive ionization mode (ESI+), 186 metabolites were found. Statistical analysis showed that 60 metabolites were found in the ESI- mode with different concentration in each group, of which 21 were more enriched in the L3 larvae and 39 in the L4 stage of A. simplex. Comparison of the individual developmental stages in the ESI + mode also revealed a total of 60 differential metabolites, but 32 metabolites were more enriched in the L3 stage larvae, and 28 metabolites were more concentrated in the L4 stage. Discussion: The metabolomics study revealed that the developmental stages of A. simplex differed in a number of metabolic pathways, including nicotinate and nicotinamide metabolism. In addition, molecules responsible for successful migration within their host, such as pyridoxine and prostaglandins (E1, E2, F1a) were present in the L4 stage. In contrast, metabolic pathways for amino acids, starch, and sucrose were mainly activated in the L3 stage. Our results provide new insights into the comparative metabolome profiles of two different developmental stages of A. simplex.
The advantages of artificial intelligence-based gait assessment in detecting, predicting, and managing Parkinson’s disease

Background Parkinson’s disease is a neurological disorder that can cause gait disturbance, leading to mobility issues and falls. Early diagnosis and prediction of freeze episodes are essential for mitigating symptoms and monitoring the disease. Objective This review aims to evaluate the use of artificial intelligence (AI)-based gait evaluation in diagnosing and managing Parkinson’s disease, and to explore the potential benefits of this technology for clinical decision-making and treatment support. Methods A thorough review of published literature was conducted to identify studies, articles, and research related to AI-based gait evaluation in Parkinson’s disease. Results AI-based gait evaluation has shown promise in preventing freeze episodes, improving diagnosis, and increasing motor independence in patients with Parkinson’s disease. Its advantages include higher diagnostic accuracy, continuous monitoring, and personalized therapeutic interventions. Conclusion AI-based gait evaluation systems hold great promise for managing Parkinson’s disease and improving patient outcomes. They offer the potential to transform clinical decision-making and inform personalized therapies, but further research is needed to determine their effectiveness and refine their use.