Miracle-dz/UniFAR-FTUs huggingface dataset:
Fault-Preserving Simplifying Transformations for Security Protocols or Not Just the Needham Schroede

Recent techniques for analyzing security protocols have tended to concentrate upon the small protocols that are typically found in the academic literature. However, there is a huge gulf between these and most large commercial protocols: the latter typically have many more fields, and much higher levels of nested encryption. As a result, existing techniques are difficult to apply directly to these large protocols. In this paper we develop the notion of fault-preserving simplifying transformations : transformations that have the property of preserving insecurities; the effect of such transformations is that if we can verify the transformed protocol, then we will have verified the original protocol. We identify a number of such fault-preserving simplifying transformations, and use them in the analysis of a commercial protocol.
Adaptive Online Sequential ELM for Concept Drift Tackling

A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method as an enhancement of Online Sequential Extreme Learning Machine (OS-ELM) and Constructive Enhancement OS-ELM (CEOS-ELM) by adding adaptive capability for classification and regression problem. The scheme is named as adaptive OS-ELM (AOS-ELM). It is a single classifier scheme that works well to handle real drift, virtual drift, and hybrid drift. The AOS-ELM also works well for sudden drift and recurrent context change type. The scheme is a simple unified method implemented in simple lines of code. We evaluated AOS-ELM on regression and classification problem by using concept drift public data set (SEA and STAGGER) and other public data sets such as MNIST, USPS, and IDS. Experiments show that our method gives higher kappa value compared to the multiclassifier ELM ensemble. Even though AOS-ELM in practice does not need hidden nodes increase, we address some issues related to the increasing of the hidden nodes such as error condition and rank values. We propose taking the rank of the pseudoinverse matrix as an indicator parameter to detect “underfitting” condition.
Titanium: A High-performance Java Dialect

Titanium is a language and system for high-performance parallel scientific computing. Titanium uses Java as its base, thereby leveraging the advantages of that language and allowing us to focus attention on parallel computing issues. The main additions to Java are immutable classes, multidimensional arrays, an explicitly parallel SPMD model of computation with a global address space, and zone-based memory management. We discuss these features and our design approach, and report progress on the development of Titanium, including our current driving application: a three-dimensional adaptive mesh refinement parallel Poisson solver. © 1998 John Wiley & Sons, Ltd.
Application of Machine Learning Techniques for Soil Type Classification of Karanataka

Soil science and its integration with machine learning has been into practice since the past few decades. Within the agriculture domain soil classification is an essential work that has to be conducted so as to provide good classificaction systmes for the soil types. Karnataka state has registerd the highest suicides in India. With the data about soil health of Karnataka state the different types of soils was analyzed and classified using different machine learning techniques. This research study for classification of soil types was conducted using tree-based model Decision Tree (C5.0), Random Forest (RF). Support Vector Machines (SVM) and eXtreme Gradient Boosting (XGBOOST). Accuracy and Kappa values suggested XGBOOST performed the best whereas the time of execution for these models differed and Random Forest had the most effient compution time with relatively comparable accuracy.
100 years after Smoluchowski: stochastic processes in cell biology

100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation.
Temperature responses of microbial soil organic matter decomposition and associated respiration at various scales, ranging from exo-enzymes to populations and communities

iii ACKNOWLEDGEMENTS . v TABLES OF CONTENTS . vii GENERAL INTRODUCTION . 1 CHAPTER 1: Differential effects of pH on temperature sensitivity of organic carbon and nitrogen decay . 4 CHAPTER 2: Carbon availability modifies temperature responses of heterotrophic microbial respiration, carbon uptake affinity, and stable carbon isotope discrimination . 37 CHAPTER 3: Temperature sensitivity of microbial exo-enzyme activities and respiration across diverse timescales . 72 GENERAL CONCLUSIONS . 125
Indoor localization system using visible light communication

Visible light communication (VLC) has recently become popular due to its benefit of VLC. VLC can provide not only the data communication via light, but also illumination. Indoor localization using VLC is a solution to locate objects or people inside a building using visible light wave by reading the identification data from visible light tubes. However, the identification data cannot be read in the light overlapping area. Time division multiplexing (TDM) is used to deal with this issue. In this work, the proximity technique is used for localization. The LED spotlights at fixed locations are used as transmitters that transmit their unique IDs, while the photodiode is used as a target receiver. By using the proximity technique, the location of the target is identified using one received ID or more.
Axisymmetric Interchange Calculations with NIMROD January 9 , 2007

Axisymmetric interchange instabilities in ideal magnetohydrodynamics are considered for a code verification exercise. Linearized equations are solved for cylindrical equilibria with uniform axial current density and uniform axial magnetic field. Analytical results are obtained from eigenmode analysis, and different NIMROD computations are performed with the plane of finite elements representing either the r-z plane or the r-θ plane of the periodic cylinder. Accuracy is confirmed for interchange without axial magnetic field with both representations and with the r-z mesh for the large-axial-field case. No-slip conditions, which reduce the growth rate by 5.5%, are required with large-axial field and the r-θ mesh to avoid a numerical error. Possible improvements to the NIMROD representation are discussed. 1. Introduction At nearly eleven years into the NIMROD project (http://nimrodteam.org), the code has been well exercised on many applications and test problems, only some of which have been documented. When the code converges, we have confidence that it provides accurate results for the specified parameters. Nonetheless, there are computations where we have to modify parameters, usually increasing diffusivities, in order to achieve convergence. The difficulties typically appear as high-wavenumber modes that grow rapidly. However, in linear computations of edge-localized modes (ELMs) with low values of electrical resistivity, we observe slow convergence properties and an unphysical dependence on the diffusivity for controlling magnetic divergence error. Convergence on ELMs is achieved at increased values of resistivity, but the value is not realistic for large tokamaks, and high-order polynomials (degree 5 and larger) are still required. It is also worth noting where the code works extremely well. At low pressure, even very slow magnetic reconnection processes are reproduced accurately. Tearing modes tend to be low wavenumber, but very localized features exist near the reconnection region. In addition, the project changed the standard for resolving anisotropy in MHD computations without mesh alignment. The challenges associated with interchange behavior have received significant attention in the numerical literature. The book by Gruber and Rappaz [1] provides an extensive treatment of ideal MHD eigenvalue computations with finite elements. It emphasizes the 'non-standard' or singular nature of ideal MHD computations—when viewed as Sturm-Liouville problems—that results from resonant surfaces. In addition, stiffness in the time-dependent MHD system manifests itself as spectral sensitivity to point-wise numerical errors associated with compression in some finite element representations, leading to spectral pollution where a new unresolved mode appears as each new element is added. Degtyarev and Medvedev review …
Comparative study of image registration techniques for bladder video-endoscopy

Bladder cancer is widely spread in the world. Many adequate diagnosis techniques exist. Video-endoscopy remains the standard clinical procedure for visual exploration of the bladder internal surface. However, video-endoscopy presents the limit that the imaged area for each image is about nearly 1 cm2. And, lesions are, typically, spread over several images. The aim of this contribution is to assess the performance of two mosaicing algorithms leading to the construction of panoramic maps (one unique image) of bladder walls. The quantitative comparison study is performed on a set of real endoscopic exam data and on simulated data relative to bladder phantom.
Turkish keyphrase extraction using multi-criterion ranking

Keyphrases have been extensively used for indexing and searching in databases and information retrieval systems. In addition, they provide useful information about semantic content of a document. In this paper, we propose an algorithm for automating Turkish keyphrase extraction. Several features of candidate phrases are exploited and form the extraction task as a problem of finding optimal set of candidate phrases. We use multi-criterion ranking to tackle this problem.
Towards a Characterization of Approximation Resistance for Symmetric CSPs

A Boolean constraint satisfaction problem (CSP) is called approximation resistant if independently setting variables to 1 with some probability achieves the best possible approximation ratio for the fraction of constraints satisfied. We study approximation resistance of a natural subclass of CSPs that we call Symmetric Constraint Satisfaction Problems (SCSPs), where satisfaction of each constraint only depends on the number of true literals in its scope. Thus a SCSP of arity k can be described by a subset of allowed number of true literals. For SCSPs without negation, we conjecture that a simple sufficient condition to be approximation resistant by Austrin and Hastad is indeed necessary. We show that this condition has a compact analytic representation in the case of symmetric CSPs (depending only on the gap between the largest and smallest numbers in S), and provide the rationale behind our conjecture. We prove two interesting special cases of the conjecture, (i) when S is an interval and (ii) when S is even. For SCSPs with negation, we prove that the analogous sufficient condition by Austrin and Mossel is necessary for the same two cases, though we do not pose an analogous conjecture in general.
Evolutionary Protein Structure Comparison

Comparing homologous objects are central to biology and the last decade have been dominated by this in the field of comparative genomics. However, many other objects than sequences in biology are homologous and can be subject to evolutionary study. Examples could be networks and structures. Protein structures have been compared for decades in a non-statistical and non-evolutionary way. There are many principles, principles and domains of applications in this field. Are the amino acids of the structures prepaired [ie aligned] or not. If they are the comparison is much easier. Can the structures be morphed or are the rigid? The latter makes the problem easier, but less realistic. Are we comparing the complete structures or search for similar sub-structures? In sequence alignment, if i is aligned to i’ and j>i, then j cannot be aligned to j’<i’ because we only allow insertion-deletions as position changing evolutionary events. But on billion year time scale, this limitation might not be warranted. Do we have more than 2 structures to be compared? Successful comparison has many applications, but given the very large evolutionary distances, it is also very hard and often unsuccessfull.
Inversion of Surface Deformation Data for Rapid Estimates of Source Parameters and Uncertainties: A Bayesian Approach

New satellite missions (e.g., the European Space Agency's Sentinel‐1 constellation), advances in data downlinking, and rapid product generation now provide us with the ability to access space‐geodetic data within hours of their acquisition. To truly take advantage of this opportunity, we need to be able to interpret geodetic data in a prompt and robust manner. Here we present a Bayesian approach for the inversion of multiple geodetic data sets that allows a rapid characterization of posterior probability density functions (PDFs) of source model parameters. The inversion algorithm efficiently samples posterior PDFs through a Markov chain Monte Carlo method, incorporating the Metropolis‐Hastings algorithm, with automatic step size selection. We apply our approach to synthetic geodetic data simulating deformation of magmatic origin and demonstrate its ability to retrieve known source parameters. We also apply the inversion algorithm to interferometric synthetic aperture radar data measuring co‐seismic displacements for a thrust‐faulting earthquake (2015 Mw 6.4 Pishan earthquake, China) and retrieve optimal source parameters and associated uncertainties. Given its robustness and rapidity in estimating deformation source parameters and uncertainties, our Bayesian framework is capable of taking advantage of real‐time geodetic measurements. Thus, our approach can be applied to geodetic data to study magmatic, tectonic, and other geophysical processes, especially in rapid‐response operational settings (e.g., volcano observatories). Our algorithm is fully implemented in a MATLAB®‐based software package (Geodetic Bayesian Inversion Software) that we make freely available to the scientific community.
Shape and Texture Indexes Application to Cell nuclei Classification

This paper describes the sequence of construction of a cell nuclei classification model by the analysis, the characterization and the classification of shape and texture. We describe first the elaboration of dedicated shape indexes and second the construction of the associated classification submodel. Then we present a new method of texture characterization, based on the construction and the analysis of statistical matrices encoding the texture. The various characterization techniques developed in this paper are systematically compared to previous approaches. In particular, we paid special attention to the results obtained by a versatile classification method using a large range of descriptors dedicated to the characterization of shapes and textures. Finally, the last classifier built with our methods achieved 88% of classification out of the 94% possible.
Sum Rate Maximization of MIMO Broadcast Channels with Coordination of Base Stations

We consider cooperative downlink transmission in multiuser, multi-cell and multiple-antenna cellular networks. It has been shown that multi-base coordinated transmission has significant spectral efficiency gains over that without coordination. The capacity limits can be achieved using a non-linear preceding technique known as dirty paper coding, which is still infeasible to implement in practice. This motivates investigation of a simpler linear preceding technique based on generalized zero-forcing known as block diagonalization (BD). In this paper, an enhanced form of BD is proposed for multiple-input multiple-output (MIMO) multi-base coordinated network. It involves optimizing the precoding over the entire null space of other users' transmissions. The performance limits of the multiple-antenna downlink with multi-base coordination are studied using duality of MIMO broadcast channels (BC) and MIMO multiple-access channels (MAC) under per-antenna power constraint, which has been established recently.
New marine Thinophilus species (Diptera: Dolichopodidae: Hydrophorinae) from the Thai Andaman Sea coast and new records from peninsular Thailand

Three new species of Thinophilus Wahlberg, 1844 are described from marine sites on the Andaman Sea coasts in peninsular Thailand: T. inaequalis Samoh & Grootaert sp. nov. belonging to the ‘Thinophilus simplex-group’ sensu Grootaert, 2018, T. plektron Samoh & Grootaert sp. nov., an unplaced species characterised by a long flattened apical spur on the hind tibia, and T. subapicalis Samoh & Grootaert sp. nov. belonging to the ‘Thinophilus spinatus-group’ sensu Grootaert, 2018. New records are given for following species occurring in peninsular Thailand: T. apicatus Grootaert, 2018, T. chaetulosus Grootaert, 2018, T. clavatus Zhu, Yang & Masunaga, 2006, T. evenhuisi Grootaert, 2018, T. lenachanae Grootaert, 2018, T. longicilia Evenhuis & Grootaert, 2002, T. nigrilineatus Grootaert, 2018, T. simplex Grootaert, 2018, T. superbus Grootaert, 2018, and T. yeoi Grootaert, 2018.
Speech segregation based on sound localization

We study the cocktail-party effect, which refers to the ability of a listener to attend to a single talker in the presence of adverse acoustical conditions. It has been observed that this ability improves in the presence of binaural cues. In this paper, we explore a technique for speech segregation based on sound localization cues. The auditory masking phenomenon motivates an "ideal" binary mask in which time-frequency regions that correspond to the weak signal are cancelled. In our model we estimate this binary mask by observing that systematic changes of the interaural time differences and intensity differences occur as the energy ratio of the original signals is modified. The performance of our model is comparable with results obtained using the ideal binary mask and it shows a large improvement over existing pitch-based algorithms.
Cooperation and Storage Tradeoffs in Power Grids With Renewable Energy Resources

One of the most important challenges in smart grid systems is the integration of renewable energy resources into its design. In this paper, two different techniques to mitigate the time-varying and intermittent nature of renewable energy generation are considered. The first one is the use of storage, which smooths out the fluctuations in the renewable energy generation across time. The second technique is the concept of distributed generation combined with cooperation by exchanging energy among the distributed sources. This technique averages out the variation in energy production across space. This paper analyzes the tradeoff between these two techniques. The problem is formulated as a stochastic optimization problem with the objective of minimizing the time average cost of energy exchange within the grid. First, an analytical model of the optimal cost is provided by investigating the steady state of the system for some specific scenarios. Then, an algorithm to solve the cost minimization problem using the technique of Lyapunov optimization is developed, and results for the performance of the algorithm are provided. These results show that in the presence of limited storage devices, the grid can benefit greatly from cooperation, whereas in the presence of large storage capacity, cooperation does not yield much benefit. Further, it is observed that most of the gains from cooperation can be obtained by exchanging energy only among a few energy-harvesting sources.
A test of ecological and ethnolinguistic determinants of maize diversity in southern Mexico

While prevailing theories of crop evolution suggest that crop diversity and cultural diversity should be linked, empirical evidence for such a link remains inconclusive. In particular, few studies have investigated such patterns on a local scale. Here, we address this issue by examining the determinants of maize diversity in a local region of high cultural and biological richness in Southern Mexico. We collected maize samples from Mixtec and Chatino villages at low and mid elevations. Although morphological traits show few patterns of population structure, we see clear genetic differentiation among villages, with ethnicity explaining a larger proportion of the differentiation than altitude. Consistent with an important role of ethnicity in patterning seed exchange, metapopulation model-based estimates of differentiation match the genetic data within village and ethnic group, but dramatically underestimate differentiation when all four villages are taken together. Our research provides insights about the importance of social origin in structuring maize diversity at the local scale.
A taxonomy of musical genres

The recent progress of Electronic Music Distribution creates a natural pressure for fine-grained musical metadata. This metadata is needed to provide music distribution services which are able to cope with the mere size of music catalogues, and the desire of users to access music titles by similarity. In this context, we describe a project of a global music title metadatabase, and focus in the particular "genre" descriptor. We analyze existing taxonomies of musical genre as found in the music industry and on the Internet, and stress on their inconsistencies. We describe a novel music genre taxonomy based on a few guiding principles, and report on the process of building this taxonomy.
Effects of moniliformin and selenium on human articular cartilage metabolism and their potential relationships to the pathogenesis of Kashin-Beck disease

ObjectiveTo investigate the effects of mycotoxin moniliformin (MON) on the metabolism of aggrecan and type II collagen in human chondrocytes in vitro and the relationship between MON and Kashin-Beck disease (KBD). MethodsHuman chondrocytes were isolated and cultured on bone matrix gelatin to form an artificial cartilage model in vitro with or without MON toxin. Cell viability was determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The expression of aggrecan and type II collagen in the cartilage was determined using immunocytochemical staining.ResultsMON toxin inhibited chondrocyte viability in dose-dependent and time-dependent manners. MON reduced aggrecan and type II collagen syntheses in the tissue-engineered cartilage. MON also increased the expression of matrix metalloproteinase-1 (MMP-1), MMP-13, BC4 epitopes, and CD44 in cartilages. However, the expression of 3B3(−) epitopes in cartilages was inhibited by MON. Selenium partially alleviated the damage of aggrecan induced by MON toxin.ConclusionMON toxin promoted the catabolism of aggrecan and type II collagen in human chondrocytes.