Miracle-dz/UniFAR-FTUs huggingface dataset:
Landscape Changes and Optimization in an Ecological Red Line Area: A Case Study in the Upper Reaches of the Ganjiang River

The key to optimizing ecological management is to study the spatial configuration of the landscape and the dynamic changes and their driving mechanisms at the landscape scale. The ecological red line area in the hilly area of the upper reaches of the Ganjiang River was chosen as the research area in this study. Based on the theory of landscape ecology and the evolution of biological communities, a multiscale coupling model was adopted and combined with remote sensing (RS) and geographical information system (GIS) technologies to systematically study the evolution of key landscape ecosystems such as forests, patch characteristics, and changes in diversity. The study revealed that: (1) forests represented the largest proportion in the study area, followed by croplands and grasslands; (2) the biological community tended to progress toward climax between 1986 and 1995, but then it moved toward regressive successions between 1995 and 2005 before recovering; (3) the study area was characterized by a high proportion of dominant ecosystems, most of which were at their climax with stable ecological species groups, and which were connected by ecological corridors; and (4) during the period from 1995 to 2010, most landscapes showed a trend of fragmentation. However, during the period from 2010 to 2018, the forest patches were gradually connected. The proportion of dominant landscapes increased, and the landscape uniformity was reduced. Based on the findings, we proposed an ecosystem management strategy that includes strengthening crop management, focusing on the natural restoration of the ecosystems and the cultivation of large patches, exploring disturbances due to mining activities, and applying methods to mitigate damage to and optimize the ecosystem.
Research and Application of Face Mask Detection Algorithm Based on YOLOV4-Tiny

: This paper mainly studies the target detection of face masks. Based on yOLOV4-TINY algorithm, multi-scale feature fusion of FPN structure and feature enhancement network are used to optimize the algorithm structure. First of all, this paper uses the xml.etree. ElementTree (ET) module in python to read the xml file to obtain the key information such as < object > face parameters, < name > face mask wearing status, < bndbox > face bounding box diagonal two vertex coordinates and so on. According to the vertex coordinates (bndbox) in the xml file, the target box is marked on the original image, and the color state of the target box is distinguished according to the wearing state of < name > face mask. Finally, two pictures of "250.png" and "477.png" are selected to be displayed in the body of this text. Then, a face mask detection algorithm based on YOLOv4-Tiny is established. when training the model, the multi-task joint loss of mask detection task is optimized by combining CIOU loss function and label smoothing strategy, and the Mosaic data enhancement method and learning rate cosine annealing attenuation strategy are used to improve the convergence speed and robustness of the model. After many times of detection and verification, the experimental results show that the detection accuracy of the proposed algorithm model is 94.84% (with_mask), 96.04% (without_mask) and 94.86% (mask_weared_incorrect) respectively in the three categories of human face mask detection: with_mask, without_mask and mask_weared_incorrect. Its quantitative indicator < number of faces correctly classified > / < number of all faces included in the tag file >, mAP is as high as 95.25%, and the accuracy is greatly improved.
A simple finite element method for Stokes flows with surface tension using unfitted meshes

This paper presents a simple finite element method for Stokes flows with surface tension. The method uses an unfitted mesh that is independent of the interface. Due to the surface force, the pressure has a jump across the interface. Based on the properties of the level set function that implicitly represents the interface, the jump of the pressure is removed, and a new problem without discontinuities is formulated. Then, classical stable finite element methods are applied to solve the new problem. Some techniques are used to show that the method is equivalent to an easy‐to‐implement method that can be regarded as a traditional method with a modified pressure space. However, the matrix of the resulting linear system of equations is the same as that of the traditional method. Optimal error estimates are derived for the proposed method. Finally, some numerical tests are presented to confirm the theoretical results. Copyright © 2015 John Wiley & Sons, Ltd.
Complexity: Hierarchical Structures and Scaling in Physics

Part I. Phenomenology and Models: 1. Introduction 2. Examples of complex behaviour 3. Mathematical models Part II: 4. Symbolic representations of physical systems 5. Probability, ergodic theory, and information 6. Thermodynamic formalism Part III. Formal Characterization of Complexity: 7. Physical and computational analysis of symbolic signals 8. Algorithmic and grammatical complexities 9. Hierarchical scaling complexities 10. Summary and perspectives.
Prognostic Factors and Nomograms for Overall and Cancer-Specific Survival of Patients with Uveal Melanoma without Metastases: A SEER Analysis of 4119 Cases

Purpose To determine prognostic factors for patients with uveal melanoma without metastases and to construct nomograms to predict their 3- and 5-year overall survival (OS) and cancer-specific survival (CSS). Methods We included 4119 patients who were registered from 2004 to 2015 in the Surveillance, Epidemiology, and End Results database. The median follow-up time was 5.8 years. Independent risk factors affecting OS and CSS were identified with univariate and multivariate Cox regression analyses and used to construct nomograms. Internal and external validation were carried out by using the bootstrap method to calculate the concordance indices (C-indices) and plot the calibration curves. Results Age, primary site, histological type, T-stage, and treatment were independent risk factors for OS and CSS; marital status and sequence number were factors only for OS. The C-indices for internal validation of OS and CSS were 0.713 (95% CI, 0.697–0.729) and 0.708 (95% CI, 0.688–0.728), respectively, and for external validation they were 0.729 (95% CI, 0.705–0.753) and 0.731 (95% CI, 0.700–0.762), respectively. The calibration curves also revealed good agreement between the predicted and actual survival rates. Conclusions We constructed nomograms to predict the 3- and 5-year OS and CSS of patients with uveal melanoma without metastases. Our nomograms may improve prognostication and assist with the development of individualized treatment strategies.
Mesenchymal Stem Cells and Formyl Peptide Receptor 2 Activity in Hyperoxia-Induced Lung Injury in Newborn Mice

Formyl peptide receptor (FPR) 2 is known to play a critical role in regulating inflammation, including either the pro-inflammatory or pro-resolving effects. However, its role in neonatal hyperoxia-induced lung injury has not been delineated. In this study, we investigate whether mesenchymal stem cells (MSCs) attenuate hyperoxia-induced neonatal lung injury by regulating FPR2 activity. We observed a significant increase in FPR2 levels in alveolar macrophages (RAW264.7 cells) after H2O2-induced stress, which decreased after MSC treatment. In the H2O2-induction model, increased levels of inflammatory cytokines (IL-1α and TNF-α) were significantly reduced in RAW264.7 cells after treatment with WRW4, an inhibitor of FPR2, or MSCs. Viability of lung epithelial cells and endothelial cells was significantly improved when cultured in the conditioned media of RAW264.7 cells treated with WRW4 or MSCs, compared to when cultured in the conditioned media of control RAW265.7 cells exposed to H2O2. For the in vivo study, wild-type and FPR2 knockout (FPR2−/−) C57/BL6 mouse pups were randomly exposed to 80% oxygen or room air from postnatal day (P) 1 to P14. At P5, 2 × 105 MSCs were transplanted intratracheally. MSCs reduced the elevated FPR2 activity at P7 and improved the decreased FPR2 activity as well as the increased immuno-stained FPR2 activity in alveolar macrophages in hyperoxic lungs at P14. Both FPR2−/− and MSCs similarly attenuated impaired alveolarization and angiogenesis, and increased apoptosis and inflammation of hyperoxic lungs without synergistic effects. Our findings suggest that the protective effects of MSCs in hyperoxic lung injury might be related to indirect modulation of FPR2 activity, at least of alveolar macrophages in neonatal mice.
Descriptive Study of Friendship Networks in Adolescents and Their Relationship with Self-Efficacy and Alcohol Consumption Using Social Network Analysis

Alcohol is a widely used legal drug. Self-efficacy takes on great importance in an adolescent’s development. Levels of self-efficacy can contribute to the decision-making process of the adolescent. In this phase, a group of friends becomes increasingly important. Alcohol is present in different social aspects. Adolescents use alcohol as a social facilitator or as part of the development of their autonomy. The purpose of this study is to describe and analyze the structure of the friendship network, self-efficacy, and alcohol consumption in adolescents. Methods: We used an online platform with validated self-reported questionnaires to collect the data. The sample consisted of 195 adolescents aged between 16 and 18, from different educational centers in Bierzo (Spain). Results: It was found that 43.6% of the adolescents in our research were high-risk consumers. Significant differences were obtained in terms of self-efficacy and different network metrics. These networks were represented by considering the levels of alcohol consumption. In the friendship network, we observed how the central adolescents presented higher levels of self-efficacy and lower alcohol consumption. Conclusions: Self-efficacy is established as a predictor of coping and not consuming alcohol and adolescence as a crucial moment to implement prevention strategies. Social Network Analysis is a useful tool that provides an image of the context in which adolescents find themselves.
Aerodynamics of the Smallest Flying Insects

We present fluid dynamics videos of the flight of some of the smallest insects including the jewel wasp, \textit{Ampulex compressa}, and thrips, \textit{Thysanoptera} spp. The fruit fly, \textit{Drosophila melanogaster}, is large in comparison to these insects. While the fruit fly flies at $Re \approx 120$, the jewel wasp flies at $Re \approx 60$, and thrips flies at $Re \approx 10$. Differences in the general structures of the wakes generated by each species are observed. The differences in the wakes correspond to changes in the ratio of lift forces (vertical component) to drag forces (horizontal component) generated.
Handwriting digit classification using PCA-transformed image features

: Machine learning model is capable of achieving an incredible great accuracy by training a large amount of data with many dimensions of features in it. To accomplish such a goal, we are currently in desperate need of powerful computers with CPUs (Computation Processing Unit) and GPUs (Graphic Processing Unit) that are competent of the workload of the training process of those machine learning models. Due to the problem that there are multiple disparate computationally intensive tasks that are lengthy period of time during training phase of machine learning, devices like smartphone and personal computer cannot achieve great efficiency during the training phase of machine learning. Instead of enhancing computational performance of devices and improve the machine learning algorithm, another more feasible way to bypass such problem is to apply dimensionality reduction methods on raw data in hope of reducing the number of features that are passing into the machine learning model during the training phase. By doing so, we can shrink the originally large number of features to several dimensions that is accomplishable for our device to compute and meanwhile, sufficient enough to have a model with acceptable accuracy trained. The purpose of this study to explore and investigate the potential benefits and disadvantages of dimensionality reduction on multiple distinct machine learning algorithm by comparing the performances of each machine learning algorithms when passing the features of raw datasets in and when passing the dataset with the features that survived after dimensionality reduction. The performance will be measured by completing a typical machine learning task: handwriting digit classification. Among all the dimensionalities methods that have been discovered, a traditional and conventional dimensionality reduction method, PCA (Principal Components Analysis), is selected. Such method has been proven successful and efficient in generating the set of data with lower dimension features and apply on an image classification task using several supervised machine learning methods, including KNN (k-nearest neighbors), SVM (Support vector machine) and CNN (Convolutional Neural Network).
Ultra-shallow quantum dots in an undoped GaAs/AlGaAs two-dimensional electron gas

We report quantum dots fabricated on very shallow 2-dimensional electron gases, only 30 nm below the surface, in undoped GaAs/AlGaAs heterostructures grown by molecular beam epitaxy. Due to the absence of dopants, an improvement of more than one order of magnitude in mobility (at 2 × 1011 cm−2) with respect to doped heterostructures with similar depths is observed. These undoped wafers can easily be gated with surface metallic gates patterned by e-beam lithography, as demonstrated here from single-level transport through a quantum dot showing large charging energies (up to 1.75 meV) and excited state energies (up to 0.5 meV).
Finite mixtures of distributions from the exponential family

Abstract General “successive substitutions” iteration equations are developed for obtaining estimates for finite mixtures of distributions from the exponential family. These, in general, correspond to relative maximums of the likelihood function. It is assumed that the number of distributions is known, and that the mixtures are from distributions of the same type, but with different parameter values. The particular equations for the Poisson, binomial, and exponential distributions are given, as well as examples of the results of the procedure for each distribution. From the examples tried, it was observed that the likelihood function increased at each iteration. Graphs of the asymptotic variances of the estimates are given, and two sampling experiments comparing estimates obtained by this scheme with moment estimates are also given.
Sodium Accumulation in Infected Cells and Ion Transporters Mistargeting in Nodules of Medicago truncatula: Two Ugly Items That Hinder Coping with Salt Stress Effects

The maintenance of intracellular nitrogen-fixing bacteria causes changes in proteins’ location and in gene expression that may be detrimental to the host cell fitness. We hypothesized that the nodule’s high vulnerability toward salt stress might be due to alterations in mechanisms involved in the exclusion of Na+ from the host cytoplasm. Confocal and electron microscopy immunolocalization analyses of Na+/K+ exchangers in the root nodule showed the plasma membrane (MtNHX7) and endosome/tonoplast (MtNHX6) signal in non-infected cells; however, in mature infected cells the proteins were depleted from their target membranes and expelled to vacuoles. This mistargeting suggests partial loss of the exchanger’s functionality in these cells. In the mature part of the nodule 7 of the 20 genes encoding ion transporters, channels, and Na+/K+ exchangers were either not expressed or substantially downregulated. In nodules from plants subjected to salt treatments, low temperature-scanning electron microscopy and X-ray microanalysis revealed the accumulation of 5–6 times more Na+ per infected cell versus non-infected one. Hence, the infected cells’ inability to withstand the salt may be the integral result of preexisting defects in the localization of proteins involved in Na+ exclusion and the reduced expression of key genes of ion homeostasis, resulting in premature senescence and termination of symbiosis.
Functional Organic Materials for Photovoltaics: The Synthesis as a Tool for Managing Properties for Solid State Applications

The continuous increase in the global energy demand deeply impacts the environment. Consequently, the research is moving towards more sustainable forms of energy production, storage and saving. Suitable technologies and materials are fundamental to win the challenge towards a greener and more eco-friendly society. Organic π-conjugated materials, including small molecules, oligomers and polymers are a wide and versatile class of functional materials with great potentiality, as they can be used as active matrixes in the fabrication of lightweight, flexible, cheap and large area devices. Their chemical and physical properties, both at a molecular level and mainly in the solid state, are a result of many factors, strictly related to the conjugated structure and functional groups on the backbone, which control the intermolecular forces driving solid state aggregations. The synthesis, through the molecular design, the choice of conjugated backbone and functionalization, represents the first and most powerful tool for finely tuning the chemico-physical properties of organic materials tailored for specific applications. In the present review, we report an overview of our works focused on synthetic methodologies, characterization, structure-properties correlation studies and applications of organic materials designed for energy-involving solid-state applications, organic photovoltaics in particular. The impact of functionalization on electro-optical properties and performance in device are discussed, also in relation to the specific applications.
Does high-definition transcranial direct current stimulation change brain electrical activity in professional female basketball players during free-throw shooting?

Differentiated brain activation in high-performance athletes supports neuronal mechanisms relevant to sports performance. Preparation for the motor action involves cortical and sub-cortical regions that can be non-invasively modulated by electrical current stimulation. This study aimed to investigate the effect of high-definition transcranial direct current stimulation (HD-tDCS) on electrical brain activity in professional female basketball players during free-throw shooting. Successful free-throw shooting (n = 2,361) from seven professional female basketball players was analyzed during two experimental conditions (HD-tDCS cathodic and sham) separated by 72 h. Three spectral bio-markers, Power Ratio Index (PRI), Delta Alpha Ratio (DAR), and Theta Beta Ratio (TBR) were measured (electroencephalography [EEG] Brain Products). Multi-channel HD-tDCS was applied for 20 min, considering current location and intensity for cathodic stimulation: FCC1h, AFF5h, AFF1h (−0.5 mA each), and FCC5h (ground). The within EEG analyses (pre and post HD-tDCS) of frontal channels (Fp1, Fp2, F3, F4, FC1, FC3) for 1 second epoch pre-shooting, showed increases in PRI (p < 0.001) and DAR (p < 0.001) for HD-tDCS cathodic condition, and in TBR for both conditions (cathodic, p = 0.01; sham, p = 0.002). Sub-group analysis divided the sample into less (n = 3; LSG) and more (n = 4; MSG) stable free-throw-shooting performers and revealed that increases in pre to post HD-tDCS in PRI only occurred for the LSG. These results suggest that the effect of HD-tDCS may induce changes in slow frontal frequency brain activities and that this alteration seems to be greater for players demonstrating a less stable free-throw shooting performance.
Unveiling the Essential Role of Arkadia’s Non-RING Elements in the Ubiquitination Process

Arkadia is a positive regulator of the TGFβ-SMAD2/3 pathway, acting through its C-terminal RING-H2 domain and targeting for degradation of its negative regulators. Here we explore the role of regions outside the RING domain (non-RING elements) of Arkadia on the E2-E3 interaction. The contribution of the non-RING elements was addressed using Arkadia RING 68 aa and Arkadia 119 aa polypeptides. The highly conserved NRGA (asparagine-arginine-glycine-alanine) and TIER (threonine-isoleucine-glutamine-arginine) motifs within the 119 aa Arkadia polypeptide, have been shown to be required for pSMAD2/3 substrate recognition and ubiquitination in vivo. However, the role of the NRGA and TIER motifs in the enzymatic activity of Arkadia has not been addressed. Here, nuclear magnetic resonance interaction studies with the E2 enzyme, UBCH5B, C85S UBCH5B-Ub oxyester hydrolysis, and auto-ubiquitination assays were used to address the role of the non-RING elements in E2-E3 interaction and in the enzymatic activity of the RING. The results support that the non-RING elements including the NRGA and TIER motifs are required for E2-E3 recognition and interaction and for efficient auto-ubiquitination. Furthermore, while Arkadia isoform-2 and its close homologue Arkadia 2C are known to interact with free ubiquitin, the results here showed that Arkadia isoform-1 does not interact with free ubiquitin.
CMaf-Inducing Protein Promotes LUAD Proliferation and Metastasis by Activating the MAPK/ERK Pathway

Objective Previous studies have shown that cMaf-inducing protein (CMIP) promotes tumorigenesis and progression, however, the role of CMIP in lung adenocarcinoma (LUAD) and its molecular mechanism remain unclear. Methods In this study, the Human Protein Atlas and Kaplan–Meier Plotter database were used to analyze the expression and prognostic value of CMIP in LUAD. Then, the expression levels of CMIP in LUAD tissues and cells were detected by qRT-PCR and western blot. The lentiviral vector was used to establish a stable transfected cell line, and the transfection efficiency was detected by qRT-PCR. MTT assay, colony formation assay, transwell assay, and wound healing assay were used to evaluate the function of CMIP in LUAD. In addition, the effect of CMIP on the MAPK/ERK pathway in LUAD cells was analyzed by western blot. Results The expression level of CMIP was significantly increased in LUAD cell and tissue samples, and the high expression of CMIP was associated with overall survival (OS) and progression-free survival (PFS) in LUAD patients. In vitro experiments showed that CMIP overexpression significantly promoted the proliferation, migration, and invasion of A549 cells. CMIP knockout significantly inhibited the proliferation, migration, and invasion of H1299 cells. In addition, it was observed that the expression levels of the MAPK/ERK pathway-related proteins were significantly increased in CMIP-overexpressed A549 cells, and promoted cell proliferation, migration, and invasion, while U0126 could significantly reverse the activation of the MAPK/ERK pathway by CMIP overexpression, and inhibit the proliferation, migration, and invasion of A549 cells. Conclusion Our study shows that CMIP, as an oncogene, is associated with poor patient prognosis, and may promote the proliferation and metastasis of LUAD by activating the MAPK/ERK pathway. Therefore, CMIP may be a new potential therapeutic target for LUAD.