Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed garbage collection by timeouts and backward inquiry

We present a practical and efficient garbage collection mechanism for large scale distributed systems. The mechanism collects all garbage including distributed cyclic garbage without global synchronization or backward links. The primary method used for local and remote garbage collection is timeouts: each object has a time-to-live, and clients which have a link to an object must refresh the target object within the time-to-live to guarantee that the link will remain valid. For cyclic garbage collection: objects suspected to be garbage are detected by last referenceable timestamp propagation; and cyclic garbage is reclaimed by backward inquiry (back-tracing). Since, without additional overhead, the information about backward references can be obtained during the refreshing process, and since messages necessary for cyclic garbage collection are bundled with the messages used for the refreshing, communication, computation and storage overhead is minimized. This mechanism has been implemented and evaluated on Prospero directory service, and the performance results show that it works well for large scale distributed systems.
Landscape metrics and change analysis of a national wildlife refuge at different spatial resolutions

For the past three decades, ecologists and biogeographers have increasingly incorporated remote sensing and geographical information systems (GISs) to inventory and analyse spatially organized data. Although there are many studies exploring the effects of fine resolution on remote sensing and GIS mapping, there is still a gap on how to identify the most appropriate spatial resolutions for studying landscapes and their structures and dynamics. This study investigated the effects of landscape changes over a 64-year study period at different spatial resolutions using four resampling schemes. The study was conducted on a national wildlife refuge of five land-use and land-cover (LULC) categories using aerial photos recorded in three distant years (1938, 1971, and 2001). This refuge has undergone major landscape changes in the last 64 years. Among the five LULC categories studied, the one that lost the most surface is agriculture; the most gain was made in forest and water. In terms of net change and swapping, agriculture and forest were the most dynamic categories in the National Wildlife Refuge. Our findings showed considerable spatial variability in landscape dynamics at different scales. We specifically observed that hard-classified maps with spatial resolutions of 30 m or finer provided better analysis of landscape dynamics, whereas with soft-classified maps it could go up to 90 m or finer. This implies that there is a range of optimum resolution that could allow for the use of medium-resolution data, such as Landsat, for reliable land change analysis. These findings offer further insight on landscape change analysis at different spatial resolutions and advance our understanding and knowledge on the effect of scale on landscape ecology.
Vector Perturbation Precoding Under Quantized CSI

This paper focuses on the design of vector perturbation (VP) precoding for multiuser multiple-input-single-output (MU-MISO) downlink transmission under quantized channel side information (CSI). In particular, each receiver decomposes its downlink channel vector in forms of channel direction information (CDI) and channel magnitude information (CMI) for feedback to the transmitter. The CMI contribution is studied in two scenarios: i) perfect CMI available to the transmitter and ii) only CMI statistics known at the transmitter. Under these two scenarios, using the quantized CDI and quantization error statistics, we propose a unified approach to design the VP precoders that minimize the mean square error (MSE) between channel input and output. Closed-form expressions to the precoders are then derived. Bit-error-rate (BER) results indicate that the proposed VP precoder designs are less sensitive to quantization errors, and CMI availability offers significant performance improvements.
An Analysis of the Behaviour of Simplified Evolutionary Algorithms on Trap Functions

Methods are developed to numerically analyse an evolutionary algorithm that applies mutation and selection on a bit-string representation to find the optimum for a bimodal unitation function called a trap function. This research bridges part of the gap between the existing convergence velocity analysis of strictly unimodal functions and global convergence results assuming the limit of infinite time. As a main result of this analysis, a new so-called (1: )evolutionary algorithm is proposed, which generates offspring using individual mutation rates . While a more traditional evolutionary algorithm using only one mutation rate is not able to find the global optimum of the trap function within an acceptable (non-exponential) time, our numerical investigations provide evidence that the new algorithm overcomes these limitations. The analysis tools used for the analysis, based on absorbing Markov chains and the calculation of transition probabilities, are demonstrated to provide an intuitive and useful method for investigating the capabilities of evolutionary algorithms to bridge the gap between a local and a global optimum in bimodal search spaces.
Association between prenatal treatment and clinical manifestations of congenital toxoplasmosis in infancy: A cohort study in 13 European centres

Aim: To determine the effectiveness of prenatal treatment for clinical manifestations of congenital toxoplasmosis. Methods: We prospectively identified 255 live‐born infants with congenital toxoplasmosis using prenatal or neonatal screening. We determined the effect of prenatal treatment on the risks of intracranial or ocular lesions in infancy, accounting for gestational age at maternal seroconversion. Results: Prenatal treatment within 4 wk of seroconversion reduced the risk of intracranial lesions compared with no treatment (odds ratio, OR 0.28; 95% CI: 0.08–0.75), but there was no significant effect when initiated after 4 wk (OR 0.76; 95% CI: 0.35–1.59; overall p‐value 0.19). Compared to spiramycin alone, no treatment doubled the risk of intracranial lesions (OR 2.33; 95% CI: 1.04–5.50), but the risk did not differ with pyrimethamine‐sulphonamide treatment (overall p‐value 0.52). There was no consistent relationship between the type or timing of treatment and the risk of ocular lesions. Gestational age at maternal seroconversion was inversely associated with the risk of intracranial but not ocular lesions.
Edit Categories and Editor Role Identification in Wikipedia

In this work, we introduced a corpus for categorizing edit types in Wikipedia. This fine-grained taxonomy of edit types enables us to differentiate editing actions and find editor roles in Wikipedia based on their low-level edit types. To do this, we first created an annotated corpus based on 1,996 edits obtained from 953 article revisions and built machine-learning models to automatically identify the edit categories associated with edits. Building on this automated measurement of edit types, we then applied a graphical model analogous to Latent Dirichlet Allocation to uncover the latent roles in editors’ edit histories. Applying this technique revealed eight different roles editors play, such as Social Networker, Substantive Expert, etc.
Web-based educational tools for speech technology

This paper describes the efforts at KTH in creating educational tools for speech technology. The demand for such tools is increasing with the advent of speech as a medium for man– machine communication. The world wide web was chosen as our platform in order to increase the usability and accessibility of our computer exercises. The aim was to provide dedicated educational software instead of exercises based on complex research tools. Currently, the set of exercises comprises basic speech analysis, multi-modal speech synthesis and spoken dialogue systems. Students access web pages in which the exercises have been embedded as applets. This makes it possible to use them in a classroom setting, as well as from the students’ home computers.
Identifying Earmarks in Congressional Bills

Earmarks are legislative provisions that direct federal funds to specific projects, circumventing the competitive grant-making process of federal agencies. Identifying and cataloging earmarks is a tedious, time-consuming process carried out by experts from public interest groups. In this paper, we present a machine learning system for automatically extracting earmarks from congressional bills and reports. We first describe a table-parsing algorithm for extracting budget allocations from appropriations tables in congressional bills. We then use machine learning classifiers to identify budget allocations as earmarked objects with an out of sample ROC AUC score of 0.89. Using this system, we construct the first publicly available database of earmarks dating back to 1995. Our machine learning approach adds transparency, accuracy, and speed to the congressional appropriations process.
Nonoptimal DNA Topoisomerases Allow Maintenance of Supercoiling Levels and Improve Fitness of Streptococcus pneumoniae

ABSTRACT Fluoroquinolones, which target gyrase and topoisomerase IV, are used for treating Streptococcus pneumoniae infections. Fluoroquinolone resistance in this bacterium can arise via point mutation or interspecific recombination with genetically related streptococci. Our previous study on the fitness cost of resistance mutations and recombinant topoisomerases identified GyrAE85K as a high-cost change. However, this cost was compensated for by the presence of a recombinant topoisomerase IV (parC and parE recombinant genes) in strain T14. In this study, we purified wild-type and mutant topoisomerases and compared their enzymatic activities. In strain T14, both gyrase carrying GyrAE85K and recombinant topoisomerase IV showed lower activities (from 2.0- to 3.7-fold) than the wild-type enzymes. These variations of in vitro activity corresponded to changes of in vivo supercoiling levels that were analyzed by two-dimensional electrophoresis of an internal plasmid. Strains carrying GyrAE85K and nonrecombinant topoisomerases had lower (11.1% to 14.3%) supercoiling density (σ) values than the wild type. Those carrying GyrAE85K and recombinant topoisomerases showed either partial or total supercoiling level restoration, with σ values being 7.9% (recombinant ParC) and 1.6% (recombinant ParC and recombinant ParE) lower than those for the wild type. These data suggested that changes acquired by interspecific recombination might be selected because they reduce the fitness cost associated with fluoroquinolone resistance mutations. An increase in the incidence of fluoroquinolone resistance, even in the absence of further antibiotic exposure, is envisaged.
Multimodal event streams for virtual reality

Applications in the fields of virtual and augmented reality as well as image-guided medical applications make use of a wide variety of hardware devices. Existing frameworks for interconnecting low-level devices and high-level application programs do not exploit the full potential for processing events coming from arbitrary sources and are not easily generalizable. In this paper, we will introduce a new multi-modal event processing methodology using dynamically-typed event attributes for event passing between multiple devices and systems. The existing OpenTracker framework was modified to incorporate a highly flexible and extensible event model, which can store data that is dynamically created and arbitrarily typed at runtime. The main factors impacting the library's throughput were determined and the performance was shown to be sufficient for most typical applications. Several sample applications were developed to take advantage of the new dynamic event model provided by the library, thereby demonstrating its flexibility and expressive power.
Hahoe KAIST Robot Theatre: learning rules of interactive robot behavior as a multiple-valued logic synthesis problem

The paper presents a new application of decomposition of multiple-valued relations. We developed a theatre of interactive humanoid robots, Hahoe KAIST Robot Theatre. Version 2 includes three full body robots, equipped with vision, speech recognition, speech synthesis and natural language dialog based on machine learning abilities. The needs for this kind of project result from several research questions, especially in emotional computing and gesture generation, but the project has also educational, artistic, and entertainment values. It is a testbed to verify and integrate several algorithms in the domain of computational intelligence. Machine learning methods based on multiple-valued logic are used for representation of knowledge and machine learning from examples.
Drug Trafficking into Macrophages via the Endocytotic Receptor CD163

In inflammatory diseases, macrophages are a main producer of a range of cytokines regulating the inflammatory state. This also includes inflammation induced by tumor growth, which recruits so-called tumor-associated macrophages supporting tumor growth. Macrophages are therefore relevant targets for cytotoxic or phenotype-modulating drugs in the treatment of inflammatory and cancerous diseases. Such targeting of macrophages has been tried using the natural propensity of macrophages to non-specifically phagocytose circulating foreign particulate material. In addition, the specific targeting of macrophage-expressed receptors has been used in order to obtain a selective uptake in macrophages and reduce adverse effects of off-target delivery of drugs. CD163 is a highly expressed macrophage-specific endocytic receptor that has been studied for intracellular delivery of small molecule drugs to macrophages using targeted liposomes or antibody drug conjugates. This review will focus on the biology of CD163 and its potential role as a target for selective macrophage targeting compared with other macrophage targeting approaches.
Descriptor transition tables for object retrieval using unconstrained cluttered video acquired using a consumer level handheld mobile device

Visual recognition and vision based retrieval of objects from large databases are tasks with a wide spectrum of potential applications. In this paper we propose a novel recognition method from video sequences suitable for retrieval from databases acquired in highly unconstrained conditions e.g. using a mobile consumer-level device such as a phone. On the lowest level, we represent each sequence as a 3D mesh of densely packed local appearance descriptors. While image plane geometry is captured implicitly by a large overlap of neighbouring regions from which the descriptors are extracted, 3D information is extracted by means of a descriptor transition table, learnt from a single sequence for each known gallery object. These allow us to connect local descriptors along the 3rd dimension (which corresponds to viewpoint changes), thus resulting in a set of variable length Markov chains for each video. The matching of two sets of such chains is formulated as a statistical hypothesis test, whereby a subset of each is chosen to maximize the likelihood that the corresponding video sequences show the same object. The effectiveness of the proposed algorithm is empirically evaluated on the Amsterdam Library of Object Images and a new highly challenging video data set acquired using a mobile phone. On both data sets our method is shown to be successful in recognition in the presence of background clutter and large viewpoint changes.
Spectrum Sensing Approach Based on Optimal Stochastic Resonance Technique under Color Noise Background in Cognitive Radio Networks

An optimal-stochastic-resonance-based spectrum sensing approach under color noise environment is proposed in this paper. It can improve the detection performance of energy detector in color noise background especially under low signal-to-noise radio (SNR). The suitable stochastic resonance (SR) noise and corresponding driving parameter can be introduced to maximize the output SNR of the SR system and the received signal. Computer simulation results show the efficiency of the proposed spectrum sensing approach under different kinds of color noises and its advantages over traditional energy detectors.
Making the small oblique parameters large.

We compute the oblique parameters, including the three new parameters V , W and X introduced recently by the Montreal group, for the case of one scalar multiplet of arbitrary weak isospin J and weak hypercharge Y . We show that, when the masses of the heaviest and lightest components of the multiplet remain constant, but J increases, the oblique parameter U and the three new oblique parameters increase like J 3 , while T only increases like J. For large multiplets with masses not much higher than mZ, the oblique parameters U and V may become much larger than T and S. The oblique parameters characterize the influence of physics beyond the standard model on the experimentally measurable quantities in terms of their contributions to the usual gaugeboson propagators. The first oblique parameter considered by the theorists [1] was T, which in many cases is larger than the other oblique parameters, because of its quadratic, instead of logarithmic, dependence on the masses of the new particles. Later [2], the parameter S was introduced, and it was shown that, because S receives a significant mass-independent contribution from each chiral fermion doublet, the experimentally allowed range for that parameter severely constrains technicolor theories. A more general parametrization of the effects of new physics, under the assumption that the mass scale of that physics is much higher than the Z mass, which implies that the vacuum-polarization functions are approximately linear in p 2 up to p 2 = m 2 , requires one more oblique parameter, U [3]. Recently [4], the above assumption has been relaxed, and it has been shown that, whatever the mass scale of the new physics may be, the fact that all precision electroweak measurements are made at either p 2 = 0 or p 2 = m 2 (or, in the case of mW and W, at p 2 = m 2 ), requires the use of a total of six oblique parameters, thereby introducing three new parameters, which were named V , W and X. The definitions of the six oblique parameters given in reference [4] are S ≡ 16�c 2 w s 2 w e 2 " AZZ(MZ) − AZZ(0) MZ
Immunological tolerance: the liver effect

The developing immune system in the embryo is programmed to accept all its own tissues as self-products and not react against them. It has been the aim of transplantation research for the past 40 years to try and manipulate the developed immune system temporarily to a similar status to that in the embryo at the time of an organ graft, so that the organ graft is accepted but immunity generally is not interfered with. Such a state is known as immunological tolerance and can be produced in the laboratory by a number of special techniques, none of which is appropriate for clinical use in organ grafting. In pigs and rats, an allografted liver can sometimes survive permanently without any immunosuppressive treatment in immunologically mature animals.
Intelligence and Substance Use

Why do some individuals choose to drink alcohol, smoke cigarettes, and use illegal drugs while others do not? The origin of individual preferences and values is one of the remaining theoretical questions in social and behavioral sciences. The Savanna-IQ Interaction Hypothesis suggests that more intelligent individuals may be more likely to acquire and espouse evolutionarily novel values than less intelligent individuals. Consumption of alcohol, tobacco, and drugs is evolutionarily novel, so the Savanna-IQ Interaction Hypothesis would predict that more intelligent individuals are more likely to consume these substances. Analyses of two large, nationally representative, and prospectively longitudinal data from the United Kingdom and the United States partly support the prediction. More intelligent children, both in the United Kingdom and the United States, are more likely to grow up to consume more alcohol. More intelligent American children are more likely to grow up to consume more tobacco, while more intelligent British children are more likely to grow up to consume more illegal drugs.
Characterization of RNase R-digested cellular RNA source that consists of lariat and circular RNAs from pre-mRNA splicing

Besides linear RNAs, pre-mRNA splicing generates three forms of RNAs: lariat introns, Y-structure introns from trans-splicing, and circular exons through exon skipping. To study the persistence of excised introns in total cellular RNA, we used three Escherichia coli 3′ to 5′ exoribonucleases. Ribonuclease R (RNase R) thoroughly degrades the abundant linear RNAs and the Y-structure RNA, while preserving the loop portion of a lariat RNA. Ribonuclease II (RNase II) and polynucleotide phosphorylase (PNPase) also preserve the lariat loop, but are less efficient in degrading linear RNAs. RNase R digestion of the total RNA from human skeletal muscle generates an RNA pool consisting of lariat and circular RNAs. RT–PCR across the branch sites confirmed lariat RNAs and circular RNAs in the pool generated by constitutive and alternative splicing of the dystrophin pre-mRNA. Our results indicate that RNase R treatment can be used to construct an intronic cDNA library, in which majority of the intron lariats are represented. The highly specific activity of RNase R implies its ability to screen for rare intragenic trans-splicing in any target gene with a large background of cis-splicing. Further analysis of the intronic RNA pool from a specific tissue or cell will provide insights into the global profile of alternative splicing.
DiffServ aware link adaptation for CDMA radio systems

A link adaptation schemes is proposed to improve the efficiency to support DiffServ traffic over CDMA air interface. To differentiate the resource allocation between DiffServ PHBs and between the in/out profile packets within each AF class, two-level differentiation is done in the proposed scheme: inter-class differentiation and infra-class differentiation. Through this interaction between the two levels, a better QoS balance between classes is achieved and therefore a higher capacity is gained as shown by our numerical evaluation
A Theory of Synchronous Relational Interfaces

Compositional theories are crucial when designing large and complex systems from smaller components. In this work we propose such a theory for synchronous concurrent systems. Our approach follows so-called interface theories, which use game-theoretic interpretations of composition and refinement. These are appropriate for systems with distinct inputs and outputs, and explicit conditions on inputs that must be enforced during composition. Our interfaces model systems that execute in an infinite sequence of synchronous rounds. At each round, a contract must be satisfied. The contract is simply a relation specifying the set of valid input/output pairs. Interfaces can be composed by parallel, serial or feedback composition. A refinement relation between interfaces is defined, and shown to have two main properties: (1) it is preserved by composition, and (2) it is equivalent to substitutability, namely, the ability to replace an interface by another one in any context. Shared refinement and abstraction operators, corresponding to greatest lower and least upper bounds with respect to refinement, are also defined. Input-complete interfaces, that impose no restrictions on inputs, and deterministic interfaces, that produce a unique output for any legal input, are discussed as special cases, and an interesting duality between the two classes is exposed. A number of illustrative examples are provided, as well as algorithms to compute compositions, check refinement, and so on, for finite-state interfaces.