Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-equilibrium gelation transition in a kinetic lattice gas model

We consider a lattice gas model which in addition to the canonical nearest neighbor pair interatomic interaction accounts for a many-body interaction inside atomic trios. Interactions of this kind arise in the coherent strained epitaxy and were recently used by us to describe some surface phenomena. With the use of the Monte Carlo simulation we show that in two dimensions the model at low temperature exhibits glassy behaviour, in particular, undergoes a gelation transition. We argue that this model may belong to the universality class of non-equilibrium critical phenomena which may comprise also some off-lattice structural glass transitions, provided such a class exists.
Formal verification of control-flow graph flattening

Code obfuscation is emerging as a key asset in security by obscurity. It aims at hiding sensitive information in programs so that they become more difficult to understand and reverse engineer. Since the results on the impossibility of perfect and universal obfuscation, many obfuscation techniques have been proposed in the literature, ranging from simple variable encoding to hiding the control-flow of a program. In this paper, we formally verify in Coq an advanced code obfuscation called control-flow graph flattening, that is used in state-of-the-art program obfuscators. Our control-flow graph flattening is a program transformation operating over C programs, that is integrated into the CompCert formally verified compiler. The semantics preservation proof of our program obfuscator relies on a simulation proof performed on a realistic language, the Clight language of CompCert. The automatic extraction of our program obfuscator into OCaml yields a program with competitive results.
A unified approach for inverse and direct dynamics of constrained multibody systems based on linear projection operator: applications to control and simulation

This paper presents a unified approach for inverse and direct dynamics of constrained multibody systems that can serve as a basis for analysis, simulation, and control. The main advantage of the dynamics formulation is that it does not require the constraint equations to be linearly independent. Thus, a simulation may proceed even in the presence of redundant constraints or singular configurations, and a controller does not need to change its structure whenever the mechanical system changes its topology or number of degrees of freedom. A motion-control scheme is proposed based on a projected inverse-dynamics scheme which proves to be stable and minimizes the weighted Euclidean norm of the actuation force. The projection-based control scheme is further developed for constrained systems, e.g., parallel manipulators, which have some joints with no actuators (passive joints). This is complemented by the development of constraint force control. A condition on the inertia matrix resulting in a decoupled mechanical system is analytically derived that simplifies the implementation of the force control. Finally, numerical and experimental results obtained from dynamic simulation and control of constrained mechanical systems, based on the proposed inverse and direct dynamics formulations, are documented.
Transportation modeling: an artificial life approach

Artificial life (ALife) uses biological knowledge and techniques to help solve different engineering, management, control and computational problems. Natural systems teach us that very simple individual organisms can form systems capable of performing highly complex tasks by dynamically interacting with each other. The main goal of this paper is to show how we can use ALife concepts (inspired by some principles of natural swarm intelligence) when solving complex problems in traffic and transportation. The bee system that represents the new approach in the field of swarm intelligence is described. It is also shown in the paper that ALife approach can be successful to "attack" transportation problems characterized by uncertainty. The fuzzy ant system (FAS) described in the paper represents an attempt to handle the uncertainty that sometimes exists in some complex transportation problems. The potential applications of the bee system and the fuzzy ant system in the field of traffic and transportation engineering are discussed.
CAD file conversion to GIS layers: Issues and solutions

CAD data created for drawings and Geographic Information System (GIS) data are created for different purposes. As a result the software's data models are inherently different, and the files differ in their structure and attributes. CAD data contain information to draw it with features organized by mixed layers. While GIS data has an additional functionality, its feature can hold huge amounts of data describing the features. Moreover, GIS data is “spatially informed” regarding adjacency and other spatial relationships. Thus, the conversion of CAD files to GIS shape file may face problems and data may get corrupted. Furthermore, in order to keep the geometric properties integrity and accuracy, we should be able to keep a correct topological database. Accurate topological data leads to correct and reliable spatial analysis, in addition to cost reduction. The aim of the topological knowledge in GIS is to increase spatial analysis opportunities. Hence, we should be able to evaluate a topological database, in addition to the geometric properties. Different issues will be addressed in this work; a step-by-step methodology will be presented using a case study to demonstrate the problems, and provided solutions using different software and programs. Examples of problems and solutions when transferring CAD data into GIS data layers are provided to allow correct and full functionality of the GIS.
Using Quantitative Usability Goals in the Design of a User Interface for A Cellular Phone

1531294 Battery testing COMPAGNIE EUROPEENNE D'ACCUMULATEURS SA 30 June 1976 [30 July 1975] 27178/76 Heading G1U The state of health of a battery (as opposed to its state of charge) is determined by fully charging the battery and by observing how rapidly its open circuit voltage drops to a stable value. A typical lead-acid cell in good condition will have an open circuit voltage of about 2.3V when just charged. This voltage MA, Fig. 1, will drop to a stable value of a little over 2.1V after about 10 hours. However, for a defective cell A such as one having an internal short passing about 100mA, the stable voltage is reached more quickly. This phenomenon is exploited in the present invention to test new, just charged, multicell batteries. In the preferred embodiment Figs. 3 and 4 (not shown) the open circuit voltage of each cell of a just-charged multicell battery is compared with the average cell voltage, and if the difference exceeds a pre-set amount, for example after 1 hour, the cell in question is judged to be defective.
Automatic Construction and Global Optimization of a Multisentiment Lexicon

Manual annotation of sentiment lexicons costs too much labor and time, and it is also difficult to get accurate quantification of emotional intensity. Besides, the excessive emphasis on one specific field has greatly limited the applicability of domain sentiment lexicons (Wang et al., 2010). This paper implements statistical training for large-scale Chinese corpus through neural network language model and proposes an automatic method of constructing a multidimensional sentiment lexicon based on constraints of coordinate offset. In order to distinguish the sentiment polarities of those words which may express either positive or negative meanings in different contexts, we further present a sentiment disambiguation algorithm to increase the flexibility of our lexicon. Lastly, we present a global optimization framework that provides a unified way to combine several human-annotated resources for learning our 10-dimensional sentiment lexicon SentiRuc. Experiments show the superior performance of SentiRuc lexicon in category labeling test, intensity labeling test, and sentiment classification tasks. It is worth mentioning that, in intensity label test, SentiRuc outperforms the second place by 21 percent.
Modular system-level architecture for concurrent cell balancing

This paper proposes a novel modular architecture for Electrical Energy Storages (EESs), consisting of multiple series-connected cells. In contrast to state-of-the-art architectures, the presented approach significantly improves the energy utilization, safety, and availability of EESs. For this purpose, each cell is equipped with a circuit that enables an individual control within a homogeneous architecture. One major advantage of our approach is a direct and concurrent charge transfer between each cell of the EES using inductors. To enable a system-level modeling and performance analysis of the architecture, a detailed investigation of the components and their interaction with the Pulse Width Modulation (PWM) control was performed at transistor-level. At system-level, we propose a control algorithm for the charge transfer that aims at minimizing the energy loss and balancing time. The results give evidence of the significant advantages of our architecture over existing passive and active balancing methods in terms of energy efficiency and charge equalization time.
Enhancing File System Integrity Through Checksums

Providing a way to check the integrity of information stored in an unreliable medium is a prime necessity in the field of secure storage systems. Also in operating systems like Unix that allow a user to bypass the file system to access the raw disk, integrity checks not only detect data corruption, but also track malicious attacks. Checksumming is a common way of ensuring data integrity. Checksums that are generated using cryptographic hash functions prevent unauthorized users from generating custom checksums to match the malicious data modification that they have made. This report discusses the various design choices in file system checksumming and describes an implementation using an in-kernel database in a stackable encryption file system.
Robust Subspace Clustering via Thresholding Ridge Regression

Given a data set from a union of multiple linear subspaces, a robust subspace clustering algorithm fits each group of data points with a low-dimensional subspace and then clusters these data even though they are grossly corrupted or sampled from the union of dependent subspaces. Under the framework of spectral clustering, recent works using sparse representation, low rank representation and their extensions achieve robust clustering results by formulating the errors (e.g., corruptions) into their objective functions so that the errors can be removed from the inputs. However, these approaches have suffered from the limitation that the structure of the errors should be known as the prior knowledge. In this paper, we present a new method of robust subspace clustering by eliminating the effect of the errors from the projection space (representation) rather than from the input space. We firstly prove that ell_1-, ell_2-, and ell_infty-norm-based linear projection spaces share the property of intra-subspace projection dominance, i.e., the coefficients over intra-subspace data points are larger than those over inter-subspace data points. Based on this property, we propose a robust and efficient subspace clustering algorithm, called Thresholding Ridge Regression (TRR). TRR calculates the ell2-norm-based coefficients of a given data set and performs a hard thresholding operator; and then the coefficients are used to build a similarity graph for clustering. Experimental studies show that TRR outperforms the state-of-the-art methods with respect to clustering quality, robustness, and time-saving.
Using Quantum Mechanical Approaches to Study Biological Systems

Conspectus Quantum mechanics (QM) has revolutionized our understanding of the structure and reactivity of small molecular systems. Given the tremendous impact of QM in this research area, it is attractive to believe that this could also be brought into the biological realm where systems of a few thousand atoms and beyond are routine. Applying QM methods to biological problems brings an improved representation to these systems by the direct inclusion of inherently QM effects such as polarization and charge transfer. Because of the improved representation, novel insights can be gleaned from the application of QM tools to biomacromolecules in aqueous solution. To achieve this goal, the computational bottlenecks of QM methods had to be addressed. In semiempirical theory, matrix diagonalization is rate limiting, while in density functional theory or Hartree–Fock theory electron repulsion integral computation is rate-limiting. In this Account, we primarily focus on semiempirical models where the divide and conquer (D&C) approach linearizes the matrix diagonalization step with respect to the system size. Through the D&C approach, a number of applications to biological problems became tractable. Herein, we provide examples of QM studies on biological systems that focus on protein solvation as viewed by QM, QM enabled structure-based drug design, and NMR and X-ray biological structure refinement using QM derived restraints. Through the examples chosen, we show the power of QM to provide novel insights into biological systems, while also impacting practical applications such as structure refinement. While these methods can be more expensive than classical approaches, they make up for this deficiency by the more realistic modeling of the electronic nature of biological systems and in their ability to be broadly applied. Of the tools and applications discussed in this Account, X-ray structure refinement using QM models is now generally available to the community in the refinement package Phenix. While the power of this approach is manifest, challenges still remain. In particular, QM models are generally applied to static structures, so ways in which to include sampling is an ongoing challenge. Car–Parrinello or Born–Oppenheimer molecular dynamics approaches address the short time scale sampling issue, but how to effectively use QM to study phenomenon covering longer time scales will be the focus of future research. Finally, how to accurately and efficiently include electron correlation effects to facilitate the modeling of, for example, dispersive interactions, is also a major hurdle that a broad range of groups are addressing The use of QM models in biology is in its infancy, leading to the expectation that the most significant use of these tools to address biological problems will be seen in the coming years. It is hoped that while this Account summarizes where we have been, it will also help set the stage for future research directions at the interface of quantum mechanics and biology.
“8A” framework for value stream selection – an empirical case study

Purpose Before initiating the implementation of change for transforming and improving an organization through lean thinking (LT), it has to first select a right value stream. Several implementation studies have been documented in literature, but not many studies have addressed this issue of value stream selection. The purpose of this paper is to propose and empirically validate a framework for selecting a value stream to implement LT. Design/methodology/approach 8A framework is proposed by reviewing the literature on LT implementation case studies. Single case study methodology has been adopted to validate the application of 8A framework for selecting a value stream in an Indian educational institute. Since multiple qualifiers are considered simultaneously, a multi-criteria decision-making approach has been employed for choosing the value stream. Findings Utility of the proposed 8A framework for value stream selection was confirmed through its successful application in an educational institute. Out of three alternatives in the case organization, the teaching alternative was chosen for further LT implementation based on the application of 8A framework. Qualitative cross-validation and sensitivity analysis also confirmed the robustness of the value stream selection made using the 8A framework. Research limitations/implications Framework proposed in this study comprehensively captures the important qualifiers that were overlooked by the widely adopted first tenet of LT. Future research can attempt to generalize the applicability of 8A framework in different contexts including manufacturing, healthcare, software development, etc. A further study can be carried out in two similar case organizations or in two value streams of the same case organization (say in two different plants) to compare the differences in the outcome of lean implementation when one chooses its value stream for LT implementation without the application of the proposed framework, while another chooses it by applying the 8A framework. Practical implications Through structured evaluation of the comprehensive set of qualifiers in 8A framework using a multi-criteria decision making model, an informed decision can be taken by the practitioners in selecting a value stream from the available alternatives before proceeding with the implementation of LT. Originality/value After questioning the existing procedure of value stream selection for LT implementation, this study is the first to propose and validate an 8A framework that overcomes the limitations of the existing procedure. Study is also unique in the choice of the case organization as not many research papers have documented implementation of LT from the context of educational institutes.
HST/STIS observations of the RW Aurigae bipolar jet: mapping the physical parameters close to the source

We present the results of new spectral diagnostic investigations applied to high-resolution long-slit spectra of the RW Aur bipolar jet obtained with HST/STIS. The spectra include the forbidden doublets [O I] 6300,6363 \AA, [S II] 6716,6731 \AA, and [N II] 6548, 6583 \AA that we utilized to determine electron density, electron temperature, hydrogen ionisation fraction, total hydrogen density, radial velocity and the mass outflow rate. We were able to extract the parameters as far as 3". 9 in the red- and 2". 1 in the blueshifted beam. The RW Aur jet appears to be the second densest outflow from a T Tauri star studied so far, but its other properties are quite similar to those found in other jets from young stars. The overall trend of the physical parameters along the first few arcseconds of the RW Aur jet is similar to that of HH 30 and DG Tau and this can reflect analogies in the mechanisms operating in that region, suggesting the same engine is accelerating the jets in the T Tauri stars with outflows. Our study of the RW Aur jet indicates for the first time that, despite the detected marked asymmetries in physical and kinematic properties between the two lobes, the mass outflow rates in the two lobes are similar. This appears to indicate that the central engine has constraining symmetries on both sides of the system, and that the observed asymmetries are probably due to different environmental conditions.
The anatomy of the NGC 5044 group ― II. Stellar populations and star formation histories

The distribution of galaxy properties in groups and clusters holds important information on galaxy evolution and growth of structure in the Universe. While clusters have received appreciable attention in this regard, the role of groups as fundamental to formation of the present-day galaxy population has remained relatively unaddressed. Here, we present stellar ages, metallicities and α-element abundances derived using Lick indices for 67 spectroscopically confirmed members of the NGC 5044 galaxy group with the aim of shedding light on galaxy evolution in the context of the group environment. We find that galaxies in the NGC 5044 group show evidence for a strong relationship between stellar mass and metallicity, consistent with their counterparts in both higher and lower mass groups and clusters. Galaxies show no clear trend of age or α-element abundance with mass, but these data form a tight sequence when fitted simultaneously in age, metallicity and stellar mass. In the context of the group environment, our data support the tidal disruption of lowmass galaxies at small group-centric radii, as evident from an apparent lack of galaxies below
Glutamate Controls tPA Recycling by Astrocytes, Which in Turn Influences Glutamatergic Signals

Tissue-type plasminogen activator (tPA) regulates physiological processes in the brain, such as learning and memory, and plays a critical role in neuronal survival and neuroinflammation in pathological conditions. Here we demonstrate, by combining mouse in vitro and in vivo data, that tPA is an important element of the cross talk between neurons and astrocytes. The data show that tPA released by neurons is constitutively endocytosed by astrocytes via the low-density lipoprotein-related protein receptor, and is then exocytosed in a regulated manner. The exocytotic recycling of tPA by astrocytes is inhibited in the presence of extracellular glutamate. Kainate receptors of astrocytes act as sensors of extracellular glutamate and, via a signaling pathway involving protein kinase C, modulate the exocytosis of tPA. Further, by thus capturing extracellular tPA, astrocytes serve to reduce NMDA-mediated responses potentiated by tPA. Overall, this work provides the first demonstration that the neuromodulator, tPA, may also be considered as a gliotransmitter.
Dynamic itemset counting and implication rules for market basket data

We consider the problem of analyzing market-basket data and present several important contributions. First, we present a new algorithm for finding large itemsets which uses fewer passes over the data than classic algorithms, and yet uses fewer candidate itemsets than methods based on sampling. We investigate the idea of item reordering, which can improve the low-level efficiency of the algorithm. Second, we present a new way of generating “implication rules,” which are normalized based on both the antecedent and the consequent and are truly implications (not simply a measure of co-occurrence), and we show how they produce more intuitive results than other methods. Finally, we show how different characteristics of real data, as opposed by synthetic data, can dramatically affect the performance of the system and the form of the results.
InterMine: extensive web services for modern biology

InterMine (www.intermine.org) is a biological data warehousing system providing extensive automatically generated and configurable RESTful web services that underpin the web interface and can be re-used in many other applications: to find and filter data; export it in a flexible and structured way; to upload, use, manipulate and analyze lists; to provide services for flexible retrieval of sequence segments, and for other statistical and analysis tools. Here we describe these features and discuss how they can be used separately or in combinations to support integrative and comparative analysis.
Issues in the design of a no-reference metric for perceived blur

Developing an objective metric, which automatically quantifies perceived image quality degradation induced by blur, is highly beneficial for current digital imaging systems. In many applications, these objective metrics need to be of the noreference (NR) type, which implies that quality prediction is based on the distorted image only. Recent progress in the development of a NR blur metric is evident from many promising methods reported in the literature. However, there is still room for improvement in the design of a NR metric that reliably predicts the extent to which humans perceive blur. In this paper, we address some important issues relevant to the design as well as the application of a NR blur metric. Its purpose is not to describe a particular metric, but rather to explain current concerns and difficulties in this field, and to outline how these issues may be accounted for in the design of future metrics.