Miracle-dz/UniFAR-FTUs huggingface dataset:
Uncertainties, complexities and possible forecasting of Volcán de Colima energy emissions (Mexico, years 2013–2015) based on a fractal reconstruction theorem

Abstract. The effusive–explosive energy emission process in a volcano is a dynamic and complex physical phenomenon. The importance of quantifying this complexity in terms of the physical and mathematical mechanisms that govern these emissions should be a requirement for deciding to apply a possible forecasting strategy with a sufficient degree of certainty. The complexity of this process is determined in this research by means of the reconstruction theorem and statistical procedures applied to the effusive–explosive volcanic energy emissions corresponding to the activity in the Volcán de Colima (western segment of the Trans-Mexican Volcanic Belt) along the years 2013–2015. The analysis is focused on measuring the degree of persistence or randomness of the series, the degree of predictability of energy emissions, and the quantification of the degree of complexity and “memory loss” of the physical mechanism throughout an episode of volcanic emissions. The results indicate that the analysed time series depict a high degree of persistence and low memory loss, making the mentioned effusive–explosive volcanic emission structure a candidate for successfully applying a forecasting strategy.
Use of Ampliﬁed Fragment Length Polymorphism To Identify 42 Cladophialophora Strains Related to Cerebral Phaeohyphomycosis with In Vitro Antifungal Susceptibility (cid:1)

The ampliﬁed fragment length polymorphism technique has been applied to identify neurotropic chaeto-thyrialean black yeasts and relatives from clinical sources. Cladophialophora bantiana , C. emmonsii , C. arxii , C. devriesii , and C. modesta , previously identiﬁed on the basis of sequencing and phenotypic and physiological criteria, were conﬁrmed by cluster analysis, demonstrating the clear separation of C. bantiana as a rather homogeneous group from the other species. C. bantiana is a neurotropic fungus causing cerebral abscesses with a mortality of up to 70%. Successful therapy consists of neurosurgical intervention and optimal antifungal therapy. Since the latter is not clearly deﬁned in a large series, we tested the in vitro activities of eight antifungal drugs against clinical isolates of C. bantiana ( n (cid:1) 37), C. modesta ( n (cid:1)
Supervised Object Localization

We propose a geometry constrained network, termed GC-Net, for weakly supervised object localization (WSOL). GC-Net consists of three modules: a detector, a generator and a classiﬁer. The detector predicts the object location deﬁned by a set of coeﬃcients describing a geometric shape (i.e. ellipse or rectangle), which is geometrically constrained by the mask produced by the generator. The classiﬁer takes the resulting masked images as input and performs two complementary clas-siﬁcation tasks for the object and background. To make the mask more compact and more complete, we propose a novel multi-task loss function that takes into account area of the geometric shape, the categorical cross-entropy and the negative entropy. In contrast to previous approaches, GC-Net is trained end-to-end and predict object location without any post-processing (e.g. thresholding) that may require additional tuning. Extensive experiments on the CUB-200-2011 and ILSVRC2012 datasets show that GC-Net outperforms state-of-the-art methods by a large margin. Our source code is available at https://github.com/lwzeng/GC-Net.
J ul 2 00 1 Spectral Indices of Stars at Super-solar Regime ∗

We derived Lick narrow-band indices for 139 candidate super metal-rich stars of different luminosity class for a sample of which fundamental atmosphere parameters have been obtained from a grid of synthetic reference spectra by Malagnini et al. (2000). Indices include Iron Fe50, Fe52, Fe53, and Magnesium Mgb and Mg2 features. By comparing models and observations, no evidence is found for nonstandard Mg vs. Fe relative abundance (i.e. [Mg/Fe] = 0, on the average, for our sample). Both the Worthey et al. (1994) and Buzzoni et al. (1992, 1994) fitting functions are found to suitably match the data, and can therefore confidently be extended for population synthesis applications also to super-solar metallicity regimes.
over-Associations of sex, breed, and age with cervical vertebral compressive myelopathy in horses: 811 cases (1974–2007)

Objective —To determine sex, breed, and age distributions in a population of horses with cervical vertebral compressive myelopathy (CVCM), compared with contemporaneous con-trol horses. Design —Retrospective case-control study. Animals —811 horses with CVCM and 805 control horses. Procedures —The Veterinary Medical Database was searched to identify horses with CVCM and contemporaneous control horses registered between July 1974 and August 2007. Ad-mission date, admitting institution, sex, breed, age at the time of registration in the data-base, weight, and discharge status (alive, died, or euthanized) were recorded for each case and control horse. Results —On the basis of results of multivariable logistic regression analysis, geldings and sexually intact males had a significantly higher likelihood of having CVCM than females (odds ratio [OR], 2.0 [95% confidence interval, 1.5 to 2.6]; and OR, 2.
A Comparison of hp-adaptive Strategies for Elliptic Partial Differential Equations (long version)

The hp version of the finite element method (hp-FEM) combined with adaptive mesh refinement is a particularly efficient method for solving partial differential equations because it can achieve a convergence rate that is exponential in the number of degrees of freedom. hp-FEM allows for refinement in both the element size, h, and the polynomial degree, p. Like adaptive refinement for the h version of the finite element method, a posteriori error estimates can be used to determine where the mesh needs to be refined, but a single error estimate can not simultaneously determine whether it is better to do the refinement by h or by p. Several strategies for making this determination have been proposed over the years. In this paper we summarize these strategies and present the results of a numerical experiment to study the convergence properties of these strategies.
Language-Speciﬁc Constraints on Conversation: Evidence from Danish and Norwegian

Establishing and maintaining mutual understanding in everyday conversations is crucial. To do so, people employ a variety of conversational devices, such as backchannels, repair, and linguistic entrainment. Here, we explore whether the use of conversational devices might be inﬂuenced by cross-linguistic differences in the speakers’ native language, comparing two matched languages—Danish and Norwegian—differing primarily in their sound structure, with Danish being more opaque, that is, less acoustically distinguished. Across systematically manipulated conversational contexts, we ﬁnd that processes supporting mutual understanding in conversations vary with external constraints: across different contexts and, crucially, across languages. In accord with our predictions, linguistic entrainment was overall higher in Danish than in Norwegian, while backchannels and repairs presented a more nuanced pattern. These ﬁndings are compatible with the hypothesis that native speakers of Danish may compensate for its opaque sound structure by adopting a top-down strategy of building more conversational redundancy through entrainment, which also might reduce the need for repairs. These results suggest that linguistic differences might be met by systematic changes in language processing and use. This paves the way for further cross-linguistic investigations and critical assessment of the
Master Computer Science Rumour Detection for Dutch Twitter

The internet has become an intricate and indispensable part of modern life, and along with that comes a potent medium for spreading rumours. This paper focuses on ﬁnding rumours in the Dutch language under the constraint of having limited amounts of labelled materials. First, I have gathered a dataset of Dutch tweets from Twitter. These tweets are related to a selection of trending topics in the Netherlands and have been annotated by volunteers. Next, I have employed self-training on XGBoost, support vector machines and naive Bayes models. In addition, I have also examined the importance of features and the generalizability of the results across hashtags. Lastly, I perform a permutation test in combination with upsampling, on these models, a multilayer perceptron, a gradient based classiﬁer and a random forest. The models showed imbalanced predictions, often leaning heavily towards one of the classes. Content features generally provided similar information as context features for all models. The models were not able to reliably generalize across diﬀerent domains. In other conditions, XGBoost performed the best, achieving AUC scores of around 0.9. The permutation tests with upsampling result in AUC scores between 0.7 and 0.9 for most models. Models that use only one feature generally perform best, although no one feature that was consistently more prominent. Though limited annotation and data availability held back the model somewhat, this paper could provide a starting point for future research.
Performance of the Principal Components Estimation Method on Factor Analysis Quality without and with Varimax Rotation

The objective of this work was to evaluate the performance of the principal components estimation method on the quality of estimates of some parameters of exploratory factor analysis (EFA), without and with varimax rotation. For this purpose, 18 parametric correlation matrices (  ) were imposed. These matrices were obtained from combinations of six different values of parametric commonalities of four normally distributed random variables with three different proportions of distances between the parametric factor loadings of the first two orthogonal factors. For each matrix  , the following parameters were defined: the first two eigenvalues (  1 and  2 ), the matrix of factor loadings (  ), the four commonalities ( h 12 , h 22 , h 32 and h 42 ) the matrix of the specific factors (  ). After the 36 factor analyses, the respective estimates of these parameters were obtained, and their respective absolute deviations between the estimates obtained a posteriori and the parameters are known a priori were evaluated. With the results of the Student's t-test at 5% significance applied to the response surface analysis, it could have been inferred that the principal components estimation method for estimating orthogonal factors was not adequate and the varimax rotation improved relatively little to the quality of the AFE estimates.
A Conceptual Model for Folding

Modern tools for viewing source code typically include a feature that enables readers to fold or unfold selected program segments in support of abstraction. Existing implementations support folding structures that conform to the abstract syntax of the programming language; that is folding by collapsing a structured construct, such as a method, into a single abstract statement. To support other forms of abstraction requires the ability to define folding structures that crosscut the syntactic structure of the language. This paper contributes a conceptual model that generalizes folding to describe both the current state of the practice and also folds involving non-contiguous segments of code. The model characterizes the technical obstacles inherent to supporting non-contiguous folds and describes a variety of policies that can be applied to resolve ambiguity. We also describe a tool called TAJ that supports this capability.
Using Knowledge Representation to Understand Interactive Systems

System migration presents a myriad of challenges in software maintenance. The user interfaces of interactive systems can undergo significant change during migration. Program understanding techniques can be used to create abstract models of the user interface that can be used to generate a new user interface on the target platform. Using a knowledge representation to model the abstractions has the advantage of providing support for transformation to the new user interface environment. This paper details the knowledge base and representation incorporated into the Model Oriented Reengineering Process for HCI (MORPH) 1 toolkit, which supports program understanding for interactive systems. It illustrates the process with an example transforming MORPH abstractions to the Java Abstract Windowing Toolkit (AWT).
Synthesisa Behavioural Programming and Multi-Process Model with High-Level Hardware-Software-Co-Design of Parallel and Distributed Systems Using

A new design methodology for parallel and distributed embedded systems is presented using the behavioural hardware compiler ConPro providing an imperative programming model based on concurrently communicating sequential processes (CSP) with an extensive set of interprocess-communication primitives and guarded atomic actions. The programming language and the compiler-based synthesis process enables the design of constrained power-and resource-aware embedded systems with pure Register-Transfer-Logic (RTL) efficiently mapped to FPGA and ASIC technologies. Concurrency is modelled explicitly on control-and datapath level. Ad-ditionally, concurrency on data-path level can be automatically explored and optimized by different schedulers. The CSP programming model can be synthesized to hardware (SoC) and software (C,ML) models and targets. A common source for both hardware and software implementation with identical functional behaviour is used. Processes and objects of the entire design can be distributed on different hardware and software platforms, for example, several FPGA components and software executed on several microprocessors, providing a parallel and distributed system. Inter- system, interprocess-, and object communication is automatically implemented with serial links, not visible on programming level. The presented design methodology has the benefit of high modularity, freedom of choice of target technologies, and system architecture. Algorithms can be well matched to and distributed on different suitable execution platforms and implementation technologies, using a unique programming model, providing a balance of concurrency and resource complexity. An extended case study of a communication protocol used in high-density sensor-actuator networks should demonstrate and compare the design of a hardware and software target. The communication protocol is suited for high-density intra-and in-terchip networks.
Preclinical quality, safety, and efﬁcacy of a human embryonic stem cell-derived product for the treatment of Parkinson’s disease, STEM-PD

SUMMARY Cell replacement therapies for Parkinson’s disease (PD) based on transplantation of pluripotent stem cell-derived dopaminergic neurons are now entering clinical trials. Here, we present quality, safety, and efﬁcacy data supporting the ﬁrst-in-human STEM-PD phase I/IIa clinical trial along with the trial design. The STEM-PD product was manufactured under GMP and quality tested in vitro and in vivo to meet regulatory requirements. Importantly, no adverse effects were observed upon testing of the product in a 39-week rat GLP safety study for toxicity, tumorigenicity, and biodistribution, and a non-GLP efﬁcacy study conﬁrmed that the transplanted cells mediated full functional recovery in a pre-clinical rat model of PD. We further observed highly comparable efﬁcacy results between two different GMP batches, verifying that the product can be serially manufactured. A fully in vivo-tested batch of STEM-PD is now being used in a clinical trial of 8 patients with moderate PD, initiated in 2022.
A Model for Matching Semantic Maps between Languages ( French / English , English / French )

This article describes a spatial model for matching semantic values between two languages, French and English. Based on semantic similarity links, the model constructs a map that represents a word in the source language. Then the algorithm projects the map values onto a space in the target language. The new space abides by the semantic similarity links specific to the second language. Then the two maps are projected onto the same plane in order to detect overlapping values. For instructional purposes, the different steps are presented here using a few examples. The entire set of results is available at the following address: http://dico.isc. cnrs.fr.
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes

Abstract. In geoscientific models, simulating the properties associated with particles in a continuum can serve many scientific purposes, and this has commonly been addressed using Lagrangian models. As an alternative approach, we present an Eulerian method here: diffusion–advection–reaction type partial differential equations are derived for centralized moments, which can describe the distribution of properties associated with chemicals in reaction–transport models. When the property is age, the equations for centralized moments (unlike non-central moments) do not require terms to account for aging, making this method suitable for modeling age tracers. The properties described by the distributions may also represent kinetic variables affecting reaction rates. In practical applications, continuous distributions of ages and reactivities are resolved to simulate organic matter mineralization in surficial sediments, where macrofaunal and physical mixing processes typically dominate transport. In test simulations, mixing emerged as the predominant factor shaping reactivity and age distributions. Furthermore, the applications showcase the method's aptitude for modeling continua in mixed environments while also highlighting practical considerations and challenges.
Digital Commons @ New Haven Digital Commons @ New Haven

Summary. The recent Mirai botnet attack demonstrated the danger of using default passwords and showed it is still a major problem. In this study we investigated several common applications and their password policies. Speciﬁcally, we analyzed if these applications: (1) have default passwords or (2) allow the user to set a weak password (i
Digital Commons @ New Haven Digital Commons @ New Haven

The purpose of this study is to develop an analytical assessment approach to identify the main factors that affect graduate students’ happiness level. Two methods, Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN), were employed for analytical modeling. A sample of 118 students at a small non-profit private university constituted the survey pool. Various factors including education, school facilities, health, social activities, and family were taken into consideration as a result of literature review in happiness assessment. A total of 32 inputs and 1 output variables were identified during survey design phase. Following survey conduction, data collection, cleaning, and preparation; MLR and ANNs were built. ANN models provided better classification performance with over 0.7 R-square and a smaller standard error of estimate compared to MLR. Major policy areas to improve student happiness levels were identified as career services, financial aid, parking and dining services.
Comparative Study on Architecture of Deep Neural Networks for Segmentation of Brain Tumor using Magnetic Resonance Images

The state-of-the-art works for the segmentation of brain tumor using the images acquired by Magnetic Resonance Imaging (MRI) with their performances are analyzed in this comparative study. First, the architectures of convolutional neural networks (CNN) and the variants of U-shaped Network (U-Net), a kind of Deep Neural Network (DNN) are compared and their differences are highlighted. The publicly available datasets of MRI images specifically Brain Tumor Segmentation (BraTS) are also discussed. Next, the performances of tumor segmentation of various methods in the literature are compared using the parameters such as Dice score and Hausdroff distance (95). This study concludes that the U-Net based architectures using the BraTS-2019 dataset outperform well compared with other CNN based architectures.
Immobilization of Cellulases Produced by Penicillium brevicompactum AUMC 10987, using Cross-Linkage, Chitosan-Coating and Encapsulation

This study was designed to optimize different conditions for improving enzyme production by Penicillium brevicompactum AUMC 10987, and to precipitate and immobilize cellulases by cross-linking method using glutaraldehyde, magnetic nanocarriers and encapsulation using Ca-alginate. Maximum activity of cellulase was achieved in medium containing date palm leaves, sodium nitrate, after 9 days incubation at 30°C and pH 6. Solid state fermentation was more convenient method in cellulase production. After ammonium sulphate precipitation, enzyme activities exceeded two-folded, constructing more stability for the enzyme structure and giving maximum activities at 50℃ and pH 4.8. Hence, precipitated enzyme could work in higher temperature and acidity conditions. The immobilization of cellulases by encapsulation was the most valuable technique retaining the activity of enzyme. Moreover, the immobilized enzyme remained active up to 80°C, giving its maximum activity at 50°C and pH 5.5. Enzyme encapsulated within alginate beads is preferred due to easy for formulation, mild gelation conditions, non-toxic, biocompatibility, low cost and resistance to microbial attack. Magnetic nannocariers immobilized enzyme had opportunity to be reused after 4 cycles/16 hours. The current study could provide a robust and highly valuable immobilized enzyme for different industrial and biotechnological applications.
Butyrate suppresses experimental necrotizing enterocolitis–induced brain injury in mice

Background Necrotizing enterocolitis (NEC) is a devastating disease in premature infants, and 50% of infants with surgical NEC develop neurodevelopmental defects. The mechanisms by which NEC-induced cytokine release and activation of inflammatory cells in the brain mediate neuronal injury, and whether enteral immunotherapy attenuates NEC-associated brain injury remain understudied. Based on our prior work, which demonstrated that experimental NEC-like intestinal injury is attenuated by the short-chain fatty acid, butyrate, in this study, we hypothesize that NEC-induced brain injury would be suppressed by enteral butyrate supplementation. Methods A standardized NEC mouse model [enteral formula feeding, lipopolysaccharide (LPS), and hypoxia] was used. Mice were randomized into the following groups: control, NEC, butyrate pretreated NEC, and butyrate control. NEC scoring (1–4 with 4 representing severe injury) was performed on ileal sections using a validated scoring system. Intestinal and brain lysates were used to assess inflammation, proinflammatory signaling, and apoptosis. Results NEC-induced intestinal injury was attenuated by butyrate supplementation. NEC-induced microglial activation in the cerebral cortex and hippocampus was suppressed with butyrate. NEC increased the number of activated microglial cells but decreased the number of oligodendrocytes. Butyrate pretreatment attenuated these changes. Increased activation of proinflammatory Toll-like receptor signaling, cytokine expression, and induction of GFAP and IBA1 in the cerebral cortex observed with NEC was suppressed with butyrate. Conclusion Experimental NEC induced inflammation and activation of microglia in several regions of the brain, most prominently in the cortex. NEC-induced neuroinflammation was suppressed with butyrate pretreatment. The addition of short-chain fatty acids to diet may be used to attenuate NEC-induced intestinal injury and neuroinflammation in preterm infants.