Miracle-dz/UniFAR-FTUs huggingface dataset:
Sistema Baseado em Microsserviços para Identificação Automática de Impressões Digitais

Biometria por meio das impressões digitais é a forma mais aceita e difundida de distinguir pessoas no mundo atual, devido aos eficientes e acessíveis equipamentos disponíveis (e.g., em celulares, caixas eletrônicos e trancas eletrônicas). Com base neste contexto e a necessidade do governo de utilizar os dados coletados dos cidadãos para diferenciá-los e identificá-los para os mais diversos objetivos, este trabalho relata a implementação de um sistema de identificação de digitais utilizando conceitos de computação concorrente, microsserviços e big data. O sistema consegue cadastrar um indivíduo com dez capturas de seus 10 dedos em um tempo médio de 25,8 segundos, contando com validação de qualidade de cada imagem, extração de características e armazenamento em diferentes bases de dados. O sistema consegue chegar próximo a 90% de assertividade na identificação (1:N) em menos de 5s em um universo de 10 mil indivíduos, também alcançando 84% de acurácia na verificação (1:1). Este trabalho encontra-se em evolução e demonstra resultados promissores com margem para melhorias.
Data Quality Assessment and the Long-Term Trend of Ground Solar Radiation in China

Abstract Solar radiation is one of the most important factors affecting climate and the environment. Routine measurements of irradiance are valuable for climate change research because of long time series and areal coverage. In this study, a set of quality assessment (QA) algorithms is used to test the quality of daily solar global, direct, and diffuse radiation measurements taken at 122 observatories in China during 1957–2000. The QA algorithms include a physical threshold test (QA1), a global radiation sunshine duration test (QA2), and a standard deviation test applied to time series of annually averaged solar global radiation (QA3). The results show that the percentages of global, direct, and diffuse solar radiation data that fail to pass QA1 are 3.07%, 0.01%, and 2.52%, respectively; the percentages of global solar radiation data that fail to pass the QA2 and QA3 are 0.77% and 0.49%, respectively. The method implemented by the Global Energy Balance Archive is also applied to check the data quality of .
Numerical Calculations of Electrostatic Potentials of Protein-Solvent Systems by the Self Consistent Boundary Method

A macroscopic dielectric model for a protein-solvent system has been solved by a numerical calculation using a supercomputer. The whole space including a target protein molecule was first divided into lots of cubes, some of which were inside the protein and the others were embedded in the solvent. Poisson equation and Poisson-Boltzmann equation were then numerically solved inside and outside of the protein, respectively. At the artificial boundary far from the protein for the finite difference procedure, neither the potential nor the field was set to be zero, but they were calculated self-consistently from the field and the potential inside the boundary calculated beforehand. The results by this method agreed well with those by the analytical calculations for some simple model cases. The results of actual protein-solvent systems were quantitatively discussed comparing with the experiments.
Electron-spin-resonance STM on iron atoms in silicon

Electron-spin-resonance\char21{}scanning tunneling microscopy (ESR)-(STM) of iron atoms in silicon was observed: Si(111) surfaces were covered with iron atoms and annealed. This gives surfaces covered with small islands of different silicide phases. We could detect an ESR-STM signal that corresponds to a g value of 2.07. The signal was split by magnetic field modulation, and phase-sensitive detection was applied. This shows that electron-spin-resonance (ESR)-STM signals can be detected on a surface that is imaged with atomic resolution and that it is possible to observe a $g\ensuremath{\ne}2$ spin center. Getting absorption (instead of the expected derivative) line shapes with phase-sensitive detection is explained by the asymmetry in the line shape, which is a result of a rapid scan of the signal. Then, when the integration time of the phase sensitive detector is close to the time it takes to sweep the linewidth of the signal, absorption line shapes are observed.
Using Petrogeochemical Modeling to Understand the Relationship between Paleozoic Magmatism in the Kola Region and Its Precambrian History

The Kola region hosts numerous Paleozoic massifs of ultrabasic alkaline rocks and carbonatites with deposits of commercially valuable metals, such as iron, tantalum, niobium, and rare earth elements. These magmatic complexes are characterized by high contents of alkaline elements at generally low contents of SiO2 and/or Al2O3. In this study, we examined the precursors to the formation of the unique Paleozoic alkaline province through studying the early Precambrian stages in the evolution of the Kola collision area, from where these unique features probably originated. We mathematically modeled the changes in the chemical composition of these rocks. The obtained data can be used for metallogenic forecasting, which indicated a number of Precambrian objects in the region, namely, the Lapland Granulite Belt of the Kola region and granulite belts in Eurasia. The mathematical modeling performed during this research depicted a linear trend that defined the style of the changes in the chemical composition at the transition from the metaultrabasic-basic rocks of the Lapland granulite belt to the group of belts in Eurasia. These differences are statistically significant with respect to the obtained trend (chemical composition projected on the trend), mainly manifested as increased SiO2 and Al2O3 contents with a decreasing total alkalis content, which is opposite to the indicated trends of the changing chemical composition in the Paleozoic alkaline rock units of the Kola region. We concluded that one of the reasons for the unique composition of the Paleozoic magmatism products could be a specific feature of the earlier Neoarchean stages of the tectonic-magmatic activity in the northeastern Baltic Shield, which implies a close relationship between later geological events and the early Precambrian history, at least in the study area.
Lipidomic Predictors of Coronary No-Reflow

The ‘no-reflow’ phenomenon (NRP) after primary percutaneous coronary intervention (PCI) is a serious complication among acute ST-segment elevation myocardial infarction (STEMI) patients. Herein, a comprehensive lipidomics approach was used to quantify over 300 distinct molecular species in circulating plasma from 126 patients with STEMI before and after primary PCI. Our analysis showed that three lipid classes: phosphatidylcholine (PC), alkylphosphatidylcholine (PC(O)), and sphingomyelin (SM), were significantly elevated (p < 0.05) in no-reflow patients before primary PCI. The levels of individual fatty acids and total fatty acid levels were significantly lower (p < 0.05) in no-reflow subjects after PCI. The grouping of patients based on ECG ST-segment resolution (STR) also demonstrated the same trend, confirming the possible role of these differential lipids in the setting of no-reflow. Sphingomyelin species, SM 41:1 and SM 41:2, was invariably positively correlated with corrected TIMI frame count (CTFC) at pre-PCI and post-PCI. The plasma levels of SM 42:1 exhibited an inverse association (p < 0.05) consistently with tumor necrosis factor-alpha (TNF-α) at pre-PCI and post-PCI. In conclusion, we identified plasma lipid profiles that distinguish individuals at risk of no-reflow and provided novel insights into how dyslipidemia may contribute to NRP after primary PCI.
Supersonic flow computations by two-equation turbulence modeling

In the present work a solver for the Reynolds averaged compressible Navier-Stokes equations, to compute high speed turbulent flows characterized by interacting shock waves and viscous layers, is presented. A k-epsilon turbulence model that accounts for compressibility effects is developed. The numerical algorithm is based on a finite volume multistage Runge Kutta technique that is explicit for the solution of the mean flow variables, and implicit for the solution of the k-epsilon equations. The model is validated by extensive comparison with experimental results of flows over compression ramps characterized by interacting shock waves/boundary layers.
Zero index metamaterials with checkerboard structure

A metamaterial design is presented with an effectively zero index of refraction, which utilises Drude-type material blocks arranged in a checkerboard pattern within a nondispersive dielectric host. An averaging effect over constituent materials of the checkerboard structure yields an effective permittivity that approaches zero. This results in a metamaterial with a zero index of refraction and a high intrinsic impedance. A design example and the associated effective medium parameters are provided.
An application of Parameterized Real‐Time Ionospheric Specification Model to regional ionospheric specification

We are currently utilizing the Parameterized Real‐Time Ionospheric Specification Model (PRISM) as a platform for deriving real‐time regional ionospheric specification. This application involves supporting PRISM with a limited set of real‐time sensor input and obtaining from PRISM a specification of ionospheric densities over a region extending to a radius of 2000–3000 km. In the initial work on this effort we have examined both data assimilation and model validation techniques, on a regional basis. We seek improved techniques for regional ionospheric specification using primarily GPS and ionosonde data as model input and mechanisms for both after‐the‐fact and real‐time assessment of the quality of the resulting specification. We will examine, for one region, data selection and application, data quality and accuracy, and approaches for obtaining a figure of merit on the specification product. We will present some results from a short regional test of these methods and discuss issues involved in generalizing to larger studies and other regions.
Damage–viscoplastic consistency model with a parabolic cap for rocks with brittle and ductile behavior under low‐velocity impact loading

This paper presents a damage–viscoplastic cap model for rocks with brittle and ductile behavior under low‐velocity impact loading, which occurs, e.g. in percussive drilling. The model is based on a combination of the recent viscoplastic consistency model by Wang and the isotropic damage concept. This approach does not suffer from ill posedness—caused by strain softening—of the underlying boundary/initial‐value problem since viscoplasticity provides a regularization under dynamic loading by introducing an internal length scale. The model uses the Drucker–Prager (DP) yield function with the modified Rankine criterion as a tension cut‐off and a parabolic cap surface as a compression cut‐off. The parabolic cap is smoothly fitted to the DP cone. The strain softening law in compression is calibrated with the degradation index concept of Fang and Harrison. Thereby, the model is able to capture the brittle‐to‐ductile transition and hardening behavior of geomaterials under highly confined compression, which is the prevailing stress state under a bit‐button in percussive drilling. Rock strength heterogeneity is characterized statistically at the structural level using the Weibull distribution. An explicit time integrator is chosen for solving the FE‐discretized equations of motion. The contact constraints due to the impact of an indenter are imposed with the forward increment Lagrange multiplier method that is compatible with explicit time integrators. The model is tested at the material point level with various uniaxial and triaxial tests. At the structural level confined compression, uniaxial tension tests and a rock sample under low‐velocity impact are simulated. Copyright © 2009 John Wiley & Sons, Ltd.
Fetal Growth Restriction Impairs Lung Function and Neurodevelopment in an Early Preterm Rabbit Model

We previously reported the multi-system sequelae of fetal growth restriction, induced by placental underperfusion, in near-term born rabbits, in the immediate neonatal period and up to pre-adolescence. Herein, we describe the pulmonary and neurodevelopmental consequences of FGR in rabbits born preterm. We hypothesize that FGR has an additional detrimental effect on prematurity in both pulmonary function and neurodevelopment. FGR was induced at gestational day (GD) 25 by placental underperfusion, accomplished by partial uteroplacental vessel ligation in one uterine horn. Rabbits were delivered by cesarean section at GD 29, and placentas were harvested for histology. Neonates underwent neurobehavioral or pulmonary functional assessment at postnatal day 1, followed by brain or lung harvesting, respectively. The neurodevelopmental assessment included neurobehavioral testing and multiregional quantification of cell density and apoptosis in the brain. Lung assessment included functional testing, alveolar morphometry, and airway histology. FGR was associated with higher perinatal mortality, lower birth and placental weight, and a similar brain-to-body weight ratio compared to controls. Placental underperfusion decreased labyrinth and junction zone volumes in FGR placentas. FGR impaired pulmonary function, depicted by higher parenchymal resistance, damping, and elastance. Alveolar morphometry and airway smooth muscle content were comparable between groups. Neurobehavioral tests showed motoric and sensorial impairment in FGR rabbits. In FGR brains, cell density was globally reduced, with higher apoptosis in selected areas. In conclusion, in preterm-born rabbits, placental underperfusion leads to higher mortality, FGR, and impaired lung and brain development in early assessment. This study complements previous findings of placental, pulmonary, and neurodevelopmental impairment in near-term born rabbits in this model.
Modelling of inclined and curved surfaces in the reflection scanning acoustic microscope

An expression is derived for the output signal when an inclined plane surface is imaged by the reflection scanning acoustic microscope, which is modelled as a spherical transducer. This expression is applied to model non‐planar surfaces. The accuracy of this approach is tested for perfectly reflecting spherical surfaces. The influence of inclination on V(z) curves is considered when Rayleigh waves occur.
Higher Oxidative Stress in Endometriotic Lesions Upregulates Senescence-Associated p16ink4a and β-Galactosidase in Stromal Cells

Endometriosis affects a significant proportion of women worldwide; however, no definitive cure for this disease has been discovered to date. Oxidative stress promotes endometriotic lesion maintenance in the peritoneal cavity in women. Furthermore, there is evidence of the mitogen-activated protein kinase (MAPK) signaling pathway and senescence involvement in the physiopathogenesis of endometriosis. Reactive oxygen species (ROS) cause oxidative damage and are expected to trigger senescence in the endometrium while also causing alterations in MAPK signaling. However, the role of ROS in the senescence-associated phenotype in endometriosis remains unknown. In this context, this study attempted to delineate the pathways linking ROS to senescence in endometrial and endometriotic lesions of healthy individuals and those with endometriosis. Our results indicate a higher presence of ROS in endometriotic lesions, and the upregulation of MAPK. Furthermore, we show that endometriotic lesions in stromal cells stimulated with hydrogen peroxide develop more senescence traits than eutopic and non-endometriosis endometrium. Overall, endometriotic cells respond differently to extracellular distress. Our contribution to further research in this field contributed to the roadmap of endometriosis’ search for alternative treatments.
Billiard walk - a new sampling algorithm for control and optimization

Abstract Hit-and-Run is known to be one of the best versions of Markov Chain Monte Carlo sampler. Nevertheless, in practice the number of iterations required to achieve uniformly distributed samples is rather high. We propose new random walk algorithm based on billiard trajectories and prove its asymptotic uniformity. Numerical experiments demonstrate much faster convergence to uniform distribution for Billiard Walk algorithm compared to Hit-and- Run. We discuss a class of global optimization problems that can be efficiently solved with Monte Carlo sampler.
Efficient One-Pot Solvothermal Synthesis and Characterization of Zirconia Nanoparticle-Decorated Reduced Graphene Oxide Nanocomposites: Evaluation of Their Enhanced Anticancer Activity toward Human Cancer Cell Lines

This study mainly deals with an effective one-pot solvothermal synthetic pathway for the preparation of uniformly dispersed zirconium oxide nanoparticles on the flattened rough surface of reduced graphene oxide (ZrO2/rGO NCs) using the aqueous leaf extract of Andrographis paniculata. After obtaining detailed information on the preparation and characterization, the anticancer activity of the synthesized ZrO2/rGO nanocrystals (NCs) was evaluated on two human cancer cell lines (A549 and HCT116) along with one normal human cell line (hMSC). The 3-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide assays revealed that ZrO2/rGO NCs exhibited a dose-dependent cytotoxicity pattern. The cell viability (%) drastically decreases up to 96–98% after exposure to an optimal concentration of 10 ppm nanocomposites. Analysis of both the reactive oxygen species generation and the Annexin V-FTIC staining assays reveal that ZrO2/rGO NCs have the ability to induce apoptosis in A549 and HCT116 cell lines. Thus, the green synthesis of ZrO2/rGO NCs shows potential in developing efficient therapeutic agents for cancer therapy.
On the Classification of Simple Stably Projectionless C*-Algebras

Abstract It is shown that simple stably projectionless ${{\text{C}}^{*}}$ -algebras which are inductive limits of certain specified building blocks with trivial $\text{K}$ -theory are classified by their cone of positive traces with distinguished subset. This is the first example of an isomorphism theorem verifying the conjecture of Elliott for a subclass of the stably projectionless algebras.
Worsening Thrombotic Complication of Atherosclerotic Plaques Due to Neutrophils Extracellular Traps: A Systematic Review

Neutrophil extracellular traps (NETs) recently emerged as a newly recognized contributor to venous and arterial thrombosis. These strands of DNA, extruded by activated or dying neutrophils, decorated with various protein mediators, become solid-state reactors that can localize at the critical interface of blood with the intimal surface of diseased arteries alongside propagating and amplifying the regional injury. NETs thus furnish a previously unsuspected link between inflammation, innate immunity, thrombosis, oxidative stress, and cardiovascular diseases. In response to disease-relevant stimuli, neutrophils undergo a specialized series of reactions that culminate in NET formation. DNA derived from either nuclei or mitochondria can contribute to NET formation. The DNA liberated from neutrophils forms a reticular mesh that resembles morphologically a net, rendering the acronym NETs particularly appropriate. The DNA backbone of NETs not only presents intrinsic neutrophil proteins (e.g., MPO (myeloperoxidase) and various proteinases) but can congregate other proteins found in blood (e.g., tissue factor procoagulant). This systematic review discusses the current hypothesis of neutrophil biology, focusing on the triggers and mechanisms of NET formation. Furthermore, the contribution of NETs to atherosclerosis and thrombosis is extensively addressed. Again, the use of NET markers in clinical trials was considered. Ultimately, given the vast body of the published literature, we aim to integrate the experimental evidence with the growing body of clinical information relating to NET critically.
Transoral Outlet Reduction (TORe) for the Treatment of Weight Regain and Dumping Syndrome after Roux-en-Y Gastric Bypass

Obesity is a chronic relapsing disease of global pandemic proportions. In this context, an increasing number of patients are undergoing bariatric surgery, which is considered the most effective weight loss treatment for long-term improvement in obesity-related comorbidities. One of the most popular bariatric surgeries is the Roux-en-Y gastric bypass (RYGB). Despite its proven short- and long-term efficacy, progressive weight regain and dumping symptoms remain a challenge. Revisional bariatric surgery is indicated when dietary and lifestyle modification, pharmaceutical agents and/or psychological therapy fail to arrest weight regain or control dumping. However, these re-interventions present greater technical difficulty and are accompanied by an increased risk of peri- and postoperative complications with substantial morbidity and mortality. The endoscopic approach to gastrojejunal anastomotic revision, transoral outlet reduction (TORe), is used as a minimally invasive treatment that aims to reduce the diameter of the gastrojejunal anastomosis, delaying gastric emptying and increasing satiety. With substantial published data supporting its use, TORe is an effective and safe bariatric endoscopic technique for addressing weight regain and dumping syndrome after RYGB.
Towards Cross-Lingual Multi-Modal Misinformation Detection for E-Commerce Management

The misinformation detection systems are increasingly important in E-commerce management, which detect misinformation on the commodity display page. Misinformation in E-commerce is usually presented as a mismatch between multi-modal information, the detection systems need to find the misinformation across the multi-model information. Furthermore, with the development of E-commerce globalization, we hope to deploy the system in the international E-commerce platform, which may face the difficulty caused by multi-lingual data. To this end, we propose a Cross-lingual Multi-modal Misinformation Detection (CMMD) framework for E-commerce management. The CMMD framework includes a word alignment network that embeds information from different languages into the same feature space and a multimodal fusion structure that fuses text representations and image representations through two self-supervised tasks. With the cooperation of these two modules, the CMMD model could extract rich cross-lingual multi-modal features to achieve accurate misinformation detection. We conduct experiments on the public multi-modal dataset and further apply the proposed CMMD to the real-world E-commerce international platform. The experimental results show that the proposed framework CMMD achieves better performance on the public dataset than some benchmarks and gets satisfactory results in real-world E-commerce management.