Miracle-dz/UniFAR-FTUs huggingface dataset:
N-Acylhomoserine Lactones Undergo Lactonolysis in a pH-, Temperature-, and Acyl Chain Length-Dependent Manner during Growth of Yersinia pseudotuberculosis and Pseudomonas aeruginosa

ABSTRACT In gram-negative bacterial pathogens, such as Pseudomonas aeruginosa and Yersinia pseudotuberculosis, cell-to-cell communication via the N-acylhomoserine lactone (AHL) signal molecules is involved in the cell population density-dependent control of genes associated with virulence. This phenomenon, termed quorum sensing, relies upon the accumulation of AHLs to a threshold concentration at which target structural genes are activated. By using biosensors capable of detecting a range of AHLs we observed that, in cultures of Y. pseudotuberculosis and P. aeruginosa, AHLs accumulate during the exponential phase but largely disappear during the stationary phase. When added to late-stationary-phase, cell-free culture supernatants of the respective pathogen, the major P. aeruginosa [N-butanoylhomoserine lactone (C4-HSL) and N-(3-oxododecanoyl)homoserine lactone (3-oxo-C12-HSL)] and Y. pseudotuberculosis [N-(3-oxohexanoyl)homoserine lactone (3-oxo-C6-HSL) and N-hexanoylhomoserine lactone (C6-HSL)] AHLs were inactivated. Short-acyl-chain compounds (e.g., C4-HSL) were turned over more extensively than long-chain molecules (e.g., 3-oxo-C12-HSL). Little AHL inactivation occurred with cell extracts, and no evidence for inactivation by specific enzymes was apparent. This AHL turnover was discovered to be due to pH-dependent lactonolysis. By acidifying the growth media to pH 2.0, lactonolysis could be reversed. By using carbon-13 nuclear magnetic resonance spectroscopy, we found that the ring opening of homoserine lactone (HSL), N-propionyl HSL (C3-HSL), and C4-HSL increased as pH increased but diminished as the N-acyl chain was lengthened. At low pH levels, the lactone rings closed but not via a simple reversal of the ring opening reaction mechanism. Ring opening of C4-HSL, C6-HSL, 3-oxo-C6-HSL, and N-octanoylhomoserine lactone (C8-HSL), as determined by the reduction of pH in aqueous solutions with time, was also less rapid for AHLs with more electron-donating longer side chains. Raising the temperature from 22 to 37°C increased the rate of ring opening. Taken together, these data show that (i) to be functional under physiological conditions in mammalian tissue fluids, AHLs require an N-acyl side chain of at least four carbons in length and (ii) that the longer the acyl side chain the more stable the AHL signal molecule.
Can seqlocks get along with programming language memory models?

Seqlocks are an important synchronization mechanism and represent a significant improvement over conventional reader-writer locks in some contexts. They avoid the need to update a synchronization variable during a reader critical section, and hence improve performance by avoiding cache coherence misses on the lock object itself. Unfortunately, they rely on speculative racing loads inside the critical section. This makes them an interesting problem case for programming-language-level memory models that emphasize data-race-free programming. We analyze a variety of implementation alternatives within the C++11 memory model, and briefly address the corresponding issue in Java. In the process, we observe that there may be a use for "read-dont-modify-write" operations, i. e. read-modify-write operations that atomically write back the original value, without modifying it, solely for the memory model consequences, and that it may be useful for compilers to optimize such operations.
A Memory-Efficient Deterministic Finite Automaton-Based Bit-Split String Matching Scheme Using Pattern Uniqueness in Deep Packet Inspection

This paper proposes a memory-efficient bit-split string matching scheme for deep packet inspection (DPI). When the number of target patterns becomes large, the memory requirements of the string matching engine become a critical issue. The proposed string matching scheme reduces the memory requirements using the uniqueness of the target patterns in the deterministic finite automaton (DFA)-based bit-split string matching. The pattern grouping extracts a set of unique patterns from the target patterns. In the set of unique patterns, a pattern is not the suffix of any other patterns. Therefore, in the DFA constructed with the set of unique patterns, when only one pattern can be matched in an output state. In the bit-split string matching, multiple finite-state machine (FSM) tiles with several input bit groups are adopted in order to reduce the number of stored state transitions. However, the memory requirements for storing the matching vectors can be large because each bit in the matching vector is used to identify whether its own pattern is matched or not. In our research, the proposed pattern grouping is applied to the multiple FSM tiles in the bit-split string matching. For the set of unique patterns, the memory-based bit-split string matching engine stores only the pattern match index for each state to indicate the match with its own unique pattern. Therefore, the memory requirements are significantly decreased by not storing the matching vectors in the string matchers for the set of unique patterns. The experimental results show that the proposed string matching scheme can reduce the storage cost significantly compared to the previous bit-split string matching methods.
"Isms" in information science: constructivism, collectivism and constructionism

Purpose – Describes the basic premises of three metatheories that represent important or emerging perspectives on information seeking, retrieval and knowledge formation in information science: constructivism, collectivism, and constructionism.Design/methodology/approach – Presents a literature‐based conceptual analysis. Pinpoints the differences between the positions in their conceptions of language and the nature and origin of knowledge.Findings – Each of the three metatheories addresses and solves specific types of research questions and design problems. The metatheories thus complement one another. Each of the three metatheories encourages and constitutes a distinctive type of research and learning.Originality/value – Outlines each metatheory's specific fields of application.
Robust Direct Adaptive Fuzzy Control of Flexible Joints Robots with Time-Varying Stiffness/Damping Parameters

In this article, we address the problem of controlling unknown flexible-joint robots with unknown time-varying stiffness and damping parameters. We propose a Robust Direct Adaptive Fuzzy Control (RDAFC) strategy that accommodates the dynamics anonymity and joints stiffness/damping variations. The RDAFC strategy relies on the synergy of the concepts of fuzzy logic approximation and the Sliding Mode Control (SMC). The fuzzy logic approximation relaxes the need for knowing the robot dynamics and the SMC accommodates the parameters variations. We also modify the RDAFC strategy to be suited to the KUKA Lightweight Robot (LWR) and propose a control strategy that can accommodates dynamics anonymity, uncertainty and joints elasticity variations. Experimental results are performed on a KUKA LWR moving in free space with its joints stiffness and damping vary with time in sine and cosine waveforms respectively. From the experiments, we can see that excellent tracking performance is obtained when using the RDAFC strategy despite the joints elasticity parameters time-variance and the robot dynamics unavailability.
Coded Emulation of Shared Atomic Memory for Message Passing Architectures

This paper considers the communication and storage costs of emulating atomic (linearizable) read/write shared memory in distributed messagepassing systems. We analyze the costs of previously-proposed algorithms by Attiya, Bar-Noy, and Dolev (the ABD algorithm) and by Fan and Lynch (the LDR algorithm), and develop new coding-based algorithms that significantly reduce these costs. The paper contains three main contributions: (1) We present a new shared-memory algorithm that we call CAS, for Coded Atomic Storage. This algorithm uses erasure coding methods. (2) In a storage system withN servers that is resilient to f server failures, we show that the communication costs for the ABD and LDR algorithms, measured in terms of number of object values, are both at least f + 1, whereas the communication cost for CAS is N N−2f . (3) We also explicitly quantify the storage costs of the ABD, LDR, and CAS algorithms. The storage cost of the ABD algorithm, measured in terms of number of object values, is N, whereas the storage costs of the LDR and CAS algorithms are both unbounded. We present a modification of the CAS algorithm based on the idea of garbage collection. The modified version of CAS has a storage cost of (δ + 1) N N−2f , where δ in an upper bound on the number of operations that are concurrent with a read operation. Thus, if δ is sufficiently small, the storage cost of CAS is lower than those of both the ABD and LDR algorithms.
Using exponentially weighted moving average algorithm to defend against DDoS attacks

This paper seeks to investigate the performance of the Exponentially Weighted Moving Average (EWMA) for mining big data and detection of DDoS attacks in Internet of Things (IoT) infrastructure. The paper will investigate the trade­off between the algorithm's detection rate, false alarm and detection delay. The paper seeks to further investigate how the performance of the algorithm is affected by the tuning parameters and how various network attack intensity affect its performance. The performance results are analyzed and discussed and further suggestion is also discussed.
Increasing Classifier Ensemble Efficiency using KSBC Algorithm

most challenging issue in constructing a classification system based on ensemble is how to construct an appropriate ensemble of basic classifiers. In this paper, a new approach of constructing ensemble namely, KSBC, K-means Based Classifier Selection is introduced. This approach utilizes Bagging algorithm as the producer of basic classifiers. Type of all basic classifiers, decision tree or multi-layer nervous networks are considered and remained unchanged during construction of ensemble. After constructing a large number of basic classifiers, KSBC partitions them with the help of k- means clustering. Afterward, by choosing one classifier from each partition, final ensemble is constructed. Weight voting method is the assembling function of the ensemble. In addition the approaches for selection of a classifier from each partition were analyzed. The effectiveness of sampling rate on the efficiency of combining classification based on clustering of classifiers was also evaluated. Finally, several tests were carried out on a large number of standard datasets in machine learning database. Experimental results illustrate the effectiveness of the proposed method compared to other approaches.
Design Pattern Recognition

The role of design patterns in forward engineering is well known, also if it’s not easy to use them, since large experience is needed. Different approaches and tools have been proposed in the literature to enhance and support the design process respect to design patterns exploitation. Also the role of design patterns in reverse engineering has been largely studied. In this paper, we describe a tool for design pattern recognition to be used in forward engineering as a kind of reuse advisor. As finding the right solution, or better finding the right pattern involves modeling some kind of similarity, we explore and propose some possible similarity-based techniques that could be used for design pattern recognition.
S1P1 Receptor Modulation with Cyclical Recovery from Lymphopenia Ameliorates Mouse Model of Multiple Sclerosis

Multiple sclerosis (MS) therapies modulate T-cell autoimmunity in the central nervous system (CNS) but may exacerbate latent infections. Fingolimod, a nonselective sphingosine-1-phosphate (S1P) receptor agonist that induces sustained lymphopenia and accumulates in the CNS, represents a new treatment modality for MS. We hypothesized that sustained lymphopenia would not be required for efficacy and that a selective, CNS-penetrant, peripherally short-acting, S1P1 agonist would show full efficacy in a mouse MS model. Using daily treatment with 10 mg/kg 2-(4-(5-(3,4-diethoxyphenyl)-1,2,4-oxadiazol-3-yl)-2,3-dihydro-1H-inden-1-yl amino)ethanol (CYM-5442) at the onset of clinical signs in myelin oligodendrocyte glycoprotein MOG35–55- induced experimental allergic encephalomyelitis (EAE), we assessed clinical scores, CNS cellular infiltration, demyelination, and gliosis for 12 days with CYM-5442, vehicle, or fingolimod. CYM-5442 levels in CNS and plasma were determined at experiment termination, and blood lymphopenia was measured 3 and 24 h after the last injection. Plasma levels of cytokines were assayed at the end of the protocol. Changes in S1P1-enhanced green fluorescent protein expression on neurons and astrocytes during active EAE and upon CYM-5442 treatment were quantified with flow cytometry and Western blotting by using native-locus enhanced green fluorescent protein-tagged S1P1 mice. S1P1 agonism alone reduced pathological features as did fingolimod (maximally lymphopenic throughout), despite full reversal of lymphopenia within each dosing interval. CYM-5442 levels in CNS but not in plasma were sustained. Neuronal and astrocytic S1P1 expression in EAE was suppressed by CYM-5442 treatment, relative to vehicle, and levels of key cytokines, such as interleukin 17A, were also significantly reduced in drug-treated mice. S1P1-selective agonists that induce reversible lymphopenia while persisting in the CNS may be effective MS treatments.
Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package

As the use of RNA-seq has popularized, there is an increasing consciousness of the importance of experimental design, bias removal, accurate quantification and control of false positives for proper data analysis. We introduce the NOISeq R-package for quality control and analysis of count data. We show how the available diagnostic tools can be used to monitor quality issues, make pre-processing decisions and improve analysis. We demonstrate that the non-parametric NOISeqBIO efficiently controls false discoveries in experiments with biological replication and outperforms state-of-the-art methods. NOISeq is a comprehensive resource that meets current needs for robust data-aware analysis of RNA-seq differential expression.
Participatory Simulation of Land-Use Changes in the Northern Mountains of Vietnam: the Combined Use of an Agent-Based Model, a Role-Playing Game, and a Geographic Information System

In Vietnam, the remarkable economic growth that resulted from the doi moi (renovation) reforms was based largely on the rural households that had become the new basic unit of agricultural production in the early 1990s. The technical, economic, and social changes that accompanied the decollectivization process transformed agricultural production, resource management, land use, and the institutions that defined access to resources and their distribution. Combined with the extreme biophysical, technical, and social heterogeneity encountered in the northern mountains, these rapid changes led to the extreme complexity of the agrarian dynamics that today challenges traditional diagnostic approaches. Since 1999, a participatory simulation method has been developed to disentangle the cause-and-effect relationships between the different driving forces and changes in land use observed at different scales. Several tools were combined to understand the interactions between human and natural systems, including a narrative conceptual model, an agent-based spatial computational model (ABM), a role-playing game, and a multiscale geographic information system (GIS). We synthesized into an ABM named SAMBA-GIS the knowledge generated from the above tools applied to a representative sample of research sites. The model takes explicitly into account the dynamic interactions among: (1) farmers' strategies, i.e., the individual decision-making process as a function of the farm's resource profile; (2) the institutions that define resource access and usage; and (3) changes in the biophysical and socioeconomic environment. The next step consisted of coupling the ABM with the GIS to extrapolate the application of local management rules to a whole landscape. Simulations are initialized using the layers of the GIS, e.g., land use in 1990, accessibility, soil characteristics, etc., and statistics available at the village level, e.g., population, ethnicity, livestock, etc. At each annual time step, the agrarian landscape changes according to the decisions made by agent-farmers about how to allocate resources such as labor force, capital, and land to different productive activities, e.g., crops, livestock, gathering of forest products, off-farm activities. The participatory simulations based on SAMBA-GIS helped identify villages with similar land-use change trajectories to which the same types of technical and/or institutional innovations could be applied. Scenarios of land-use changes were developed with local stakeholders to assess the potential impact of these changes on the natural resource base and on agricultural development. This adaptive approach was gradually refined through interactions between researchers and the local population.
Vectorial versus configural encoding of Body Space A neural basis for a distinction between Body schema and Body image

A neural basis for a distinction between Body schema and Body image. The way in which space relationships are represented in the brain and intervene to organize our vision of a stable world in which we move our private body space has been the topic of lasting philosophical and scientific debates. In interdisciplinary workshop like this, each of us, depending on his own background and experiences, is necessarily coming with his biased point of view. Let me first briefly outline how my own itinerary, as an early trained neurobiologist (having to teach psychobiology in the faculty of sciences) lead me, as early as 1972, to confidently consider a functional segregation between body schema and body image as biologically and evolutionary founded. One of the most impressive features of our brain is its ability to process a continuous flow of multimodal information from internal and external sources thus producing an integrated and coherent central representation of our perceptible outside world and of both our perceived and unconsciously registered own body space. Motor action is assumed to play a crucial role in accounting for the astonishing capacity of the nervous system to extract regularity and covariant features from changing surroundings and body state, storing them in some central representation of both a predictable outside word and the private domestic body space which we inhabit. Additionally, inherited sensori-motor mechanisms intervene both for regulating the large spectrum of autonomic functions underlying body metabolic functions and for automatically framing the basic postural mechanisms underlying body's orientation in the field of gravity, and those anchoring oriented sense organs to targets located in a coherent, stable, and unified perceived world. ('Paillard, 1999b)
Reduction of quantum systems on Riemannian manifolds with symmetry and application to molecular mechanics

This paper deals with a general method for the reduction of quantum systems with symmetry. For a Riemannian manifold M admitting a compact Lie group G as an isometry group, the quotient space Q=M/G is not a smooth manifold in general but stratified into a collection of smooth manifolds of various dimensions. If the action of the compact group G is free, M is made into a principal fiber bundle with structure group G. In this case, reduced quantum systems are set up as quantum systems on the associated vector bundles over Q=M/G. This idea of reduction fails, if the action of G on M is not free. However, the Peter–Weyl theorem works well for reducing quantum systems on M. When applied to the space of wave functions on M, the Peter–Weyl theorem provides the decomposition of the space of wave functions into spaces of equivariant functions on M, which are interpreted as Hilbert spaces for reduced quantum systems on Q. The concept of connection on a principal fiber bundle is generalized to be defined well on the.
The multiplier approach to the money supply process: a precautionary note

HE MULTIPLIER MODEL of the money supply, originally developed by Brunner (1961) and Brunner and Meltzer (1964), has become the standard paradigm in macroeconomics and money and banking textbooks to explain how the policy actions of the Federal Reserve influence the money stock. It also has been used in empirical analyses of money stock control and the impact of monetary policy actions on other economic variables.
Anisotropic Centroidal Voronoi Tessellations and Their Applications

In this paper, we introduce a novel definition of the anisotropic centroidal Voronoi tessellation (ACVT) corresponding to a given Riemann metric tensor. A directional distance function is used in the definition to simplify the computation. We provide algorithms to approximate the ACVT using the Lloyd iteration and the construction of anisotropic Delaunay triangulation under the given Riemannian metric. The ACVT is applied to the optimization of two-dimensional anisotropic Delaunay triangulation, to the generation of surface CVT, and high-quality triangular mesh on general surfaces. Various numerical examples demonstrating the effectiveness of the proposed method are presented.
Deformable models for volume feature tracking

Conventional three dimensional medical imaging devices have made possible the routine visualization of biological tissue acquired as a sequence of image volumes over time. Because biological tissue is rarely static, the accurate registration of features in two volumes from an image sequence is a common requirement for analysis of these data. This registration task can be difficult, since tissue can bend and stretch over time, and a motion description capturing the non-rigid deformation can be quite complex. One way to characterize the non-rigid deformation is by means of a vector field called a motion field, which describes the relative displacement of each voxel, and thus establishes a correspondence between any set of features in the two volumes. A field such as this can adequately describe any non-rigid deformation seen in biological tissue; however, algorithms designed to estimate it are often confounded by the large dimensionality of the problem. Given the size of conventional medical imaging data sets, the total degrees of freedom represented by the number of independent vectors in the motion field is tremendously large. This dissertation focuses on incorporating elastic material models into a motion estimation algorithm so that the deformation of tissue in a medical imaging data set can be more accurately described. The research has been motivated by a problem seen in the acquisition of cardiac Positron Emission Tomography (PET). Because the heart moves during a PET acquisition, data are often distributed into different time frames, each capturing a specific phase of the cardiac cycle. This reduces motion-induced blur; however, the individual time frames are quite noisy, and need to be recombined in some manner to improve image quality. Since the shape of the heart is different in each time frame, the data 2 may not be simply added together, but first must be warped to match a common reference shape. Warping is achieved by using an optical flow-based motion algorithm to estimate the mapping between corresponding voxels in a source and a reference volume. The material model serves to reduce the large domain of possible motion fields, constraining the image data to deform as if it were a physical piece of elastic media undergoing stress from an external force. The main result of this dissertation is that by better modeling the material properties of tissue within the field of view in a dynamic cardiac PET acquisition, a better estimation of the motion field describing the …