Miracle-dz/UniFAR-FTUs huggingface dataset:
On Some Stability Properties of the LRAAM Model

In this report we discuss some mathematical properties of the LRAAM model. The LRAAM model is an extension of the RAAM model by Pollack. It allows one to obtain distributed reduced representations of labeled graphs. In particular, we give suucient conditions on the asymptotical stability of the decoding process along a cycle of the encoded structure. Data encoded in an LRAAM can also be accessed by content by transforming the LRAAM in an analog Hoppeld network with hidden units and asymmetric connection matrix (CA network.) Diierent access procedures can be deened according to the access key. Each access procedure corresponds to a particular constrained version of the CA network. We give suucient conditions under which the property of asymptotical stability of a xed point in one particular constrained version of the CA network can be extended to related xed points of diierent constrained versions of the CA network. An example of encoding of a labeled graph on which the theoretical results are applied is given as well.
Opinion leaders as intermediaries in audience building for independent films in the Internet age

How are contemporary film-makers building audiences independently from distributors or sales agents? This article uses two case studies, Tenner Films and The Hunt for Gollum, to argue that opinion leaders are intermediaries who play a vital role in do-it-yourself audience building for independent films in today’s Internet age. The article concludes that (1) the Internet has increased the number of potential and accessible opinion leaders, (2) online opinion leaders have potentially bigger audiences than their offline counterparts, (3) new opinion leaders have emerged, (4) opinion leaders act as multipliers and (5) non-experts can be opinion leaders too. (6) The Internet allows cultural producers to reach different opinion leaders through a single medium and while (7) different opinion leaders come with different audience sizes, (8) they all continue to function as taste guides. Finally, (9) the Internet makes it easier for independent film-makers to nurture personal audiences and therefore, partially replace opinion leaders by becoming opinion leaders themselves.
Recurrent Domestication by Lepidoptera of Genes from Their Parasites Mediated by Bracoviruses

Bracoviruses are symbiotic viruses associated with tens of thousands of species of parasitic wasps that develop within the body of lepidopteran hosts and that collectively parasitize caterpillars of virtually every lepidopteran species. Viral particles are produced in the wasp ovaries and injected into host larvae with the wasp eggs. Once in the host body, the viral DNA circles enclosed in the particles integrate into lepidopteran host cell DNA. Here we show that bracovirus DNA sequences have been inserted repeatedly into lepidopteran genomes, indicating this viral DNA can also enter germline cells. The original mode of Horizontal Gene Transfer (HGT) unveiled here is based on the integrative properties of an endogenous virus that has evolved as a gene transfer agent within parasitic wasp genomes for ≈100 million years. Among the bracovirus genes thus transferred, a phylogenetic analysis indicated that those encoding C-type-lectins most likely originated from the wasp gene set, showing that a bracovirus-mediated gene flux exists between the 2 insect orders Hymenoptera and Lepidoptera. Furthermore, the acquisition of bracovirus sequences that can be expressed by Lepidoptera has resulted in the domestication of several genes that could result in adaptive advantages for the host. Indeed, functional analyses suggest that two of the acquired genes could have a protective role against a common pathogen in the field, baculovirus. From these results, we hypothesize that bracovirus-mediated HGT has played an important role in the evolutionary arms race between Lepidoptera and their pathogens.
Topological Construction and Visualization of Higher Order 3D Vector Fields

We present the first algorithm for constructing 3D vector fields based on their topological skeleton. The skeleton itself is modeled by interactively moving a number of control polygons. Then a piecewise linear vector field is automatically constructed which has the same topological skeleton as modeled before. This approach is based on a complete segmentation of the areas around critical points into sectors of different flow behavior. Based on this, we present the first approach to visualizing higher order critical points of 3D vector fields.
Multi-Agent UAV Path Planning

This paper introduces a simulation designed to test real-time path planning done by single and multiple agents. The components of the simulation include a road network, several Uninhabited Aerial Vehicles (UAVs) with electro-optic sensors, a target and an Uninhabited Ground Vehicle (UGV). The target and UGV are located on the road network. Random blockages are placed on the road network, possibly preventing UGV traversal to the target. These blockages can be detected by the UAVs. Figure (i) outlines the components in the simulation.
Reasoning about Photo Collections using Models of Outdoor Illumination

Natural illumination from the sun and sky plays a signiﬁcant role in the appearance of outdoor scenes. We propose the use of sophisticated outdoor illumination models, developed in the computer graphics community, for estimating appearance and timestamps from a large set of uncalibrated images of an outdoor scene. We ﬁrst present an analysis of the relationship between these illumination models and the geolocation, time, surface orientation
Harnessing Type I and Type III CRISPR-Cas systems for genome editing

CRISPR-Cas (clustered regularly interspaced short palindromic repeats-CRISPR-associated) systems are widespread in archaea and bacteria, and research on their molecular mechanisms has led to the development of genome-editing techniques based on a few Type II systems. However, there has not been any report on harnessing a Type I or Type III system for genome editing. Here, a method was developed to repurpose both CRISPR-Cas systems for genetic manipulation in Sulfolobus islandicus, a thermophilic archaeon. A novel type of genome-editing plasmid (pGE) was constructed, carrying an artificial mini-CRISPR array and a donor DNA containing a non-target sequence. Transformation of a pGE plasmid would yield two alternative fates to transformed cells: wild-type cells are to be targeted for chromosomal DNA degradation, leading to cell death, whereas those carrying the mutant gene would survive the cell killing and selectively retained as transformants. Using this strategy, different types of mutation were generated, including deletion, insertion and point mutations. We envision this method is readily applicable to different bacteria and archaea that carry an active CRISPR-Cas system of DNA interference provided the protospacer adjacent motif (PAM) of an uncharacterized PAM-dependent CRISPR-Cas system can be predicted by bioinformatic analysis.
A Note on the Interpretation of Weighted Kappa and its Relations to Other Rater Agreement Statistics for Metric Scales

This article presents a formula for weighted kappa in terms of rater means, rater variances, and the rater covariance that is particularly helpful in emphasizing that weighted kappa is an absolute agreement measure in the sense that it is sensitive to differences in rater’s marginal distributions. Specifically, rater mean differences will decrease the value of weighted kappa relative to the value of the intraclass correlation that ignores mean differences. In addition, if rater variances also differ, then the value of weighted kappa will be decreased relative to the value of the product-moment correlation. Equality constraints on the rater means and variances are given to illustrate the relationships between weighted kappa, the intraclass correlation, and the product-moment correlation. In addition, the expression for weighted kappa shows that weighted kappa belongs to the Zegers-ten Berge family of chance-corrected association coefficients. More specifically, weighted kappa is equivalent to the chance-corrected identity coefficient.
Parallel Secondo: Boosting Database Engines with Hadoop

Hadoop is an efficient and simple parallel framework following the Map Reduce paradigm, and making the parallel processing recently become a hot issue in data-intensive applications. Since Hadoop can be easily deployed on large-scale clusters including up to thousands of computers, various studies intend to process common relational database operations also on this new platform and expect to achieve a remarkable performance. However, these works have to prepare customized programs according to different input format, making the communication between co-workers difficult. Additionally, all intermediate data have to be transformed to key-value pairs and then transferred through the underlying HDFS, making the data processable by Map and Reduce tasks and keeping a balanced workload on the cluster. During this period, unnecessary overhead decreases both the speed-up and scale-up of these systems. Therefore, this paper attempts to propose a light and efficient coupling structure thus to combine Hadoop with single-computer databases on the engine level. On one hand, it uses a well-designed parallel data model to make end-users represent parallel queries like common queries. All current and future data types and algorithms can be used directly, having no need to be specifically changed for the parallel platform. On the other hand, it provides a simple and independent distributed file system to transfer data among database engines directly, without passing through HDFS, hence to remove as much as possible unnecessary transform and transfer overhead. For purpose of demonstration, a prototype Parallel Secondo is introduced in this paper. It has been fully evaluated in both small and large scale clusters, achieving satisfactory performances for different database operations.
Academic Mission Statements: An Exercise in Negotiation

English educational legislation in the 1980s and early 1990s occasioned major reforms in the funding and management of post-compulsory educational institutions. Out went largely autonomous Universities, Polytechnics answerable for their actions to local government, and independent Colleges of Higher Education; in came Higher Education Funding Councils and Higher Educational Institutions (HEIs). After legislation in 1992, all were able to call themselves universities. Driving this redefinition of educational realities was a view that higher education had been too long `provider centred' rather than `customer centred', that it had to expand and change to take fully into account the new needs of industry, business and the professions. It had to become a more responsible user of public funds, to demonstrate it was capable of managing them effectively and efficiently, and provide value for money. Higher education had to become `business like'. This article examines one facet of the transformation through which English higher education is still passing. It analyses the Mission Statements which all HEIs have had to produce, to determine in what ways they position the HEIs, represent what they do, and relate them to other participants `in the wider community'.
Joint Effects of Gender Differences in Central Tendency and Gender Differences in Variability

My article (Feingold, 1992a) focused on the examination of gender differences in variability on scales of well-known standardized cognitive ability batteries. However, I recognized that gender differences in variability per se are meaningful only in the absence of corresponding gender differences in central tendency and that previous analyses of the same scales (Feingold, 1988, 1992a) found that such differences often existed. In order to communicate the joint effects of the two kinds of gender differences, I subjectively integrated ds (standardized mean differences; Cohen, 1977) and VRs (variance ratios; Snedecor & Cochran, 1967) to determine the ratios of males to females at both tails of each distribution
Limitations of Current Grammar Induction Algorithms

I review a number of grammar induction algorithms (ABL, Emile, Adios), and test them on the Eindhoven corpus, resulting in disappointing results, compared to the usually tested corpora (ATIS, OVIS). Also, I show that using neither POS-tags induced from Biemann's unsupervised POS-tagging algorithm nor hand-corrected POS-tags as input improves this situation. Last, I argue for the development of entirely incremental grammar induction algorithms instead of the approaches of the systems discussed before.
Modelling Hydrology and Sediment Transport in a Semi-Arid and Anthropized Catchment Using the SWAT Model: The Case of the Tafna River (Northwest Algeria)

Sediment deposits in North African catchments contribute to around 2%–5% of the yearly loss in the water storage capacity of dams. Despite its semi-arid climate, the Tafna River plays an important role in Algeria’s water self-sufficiency. There is continuous pressure on the Tafna’s dams to respond to the demand for water. The Soil and Water Assessment Tool (SWAT) was used to evaluate the contribution of different compartments in the basin to surface water and the dams’ impact on water and sediment storage and its flux to the sea in order to develop reservoir management. The hydrological modelling fitted well with the observed data (Nash varying between 0.42 and 0.75 and R2 varying between 0.25 and 0.84). A large proportion of the surface water came from surface runoff (59%) and lateral flow (40%), while the contribution of groundwater was insignificant (1%). SWAT was used to predict sediments in all the gauging stations. Tafna River carries an average annual quantity of 2942 t·yr−1 to the Mediterranean Sea. A large amount of water was stored in reservoirs (49%), which affected the irrigated agricultural zone downstream of the basin. As the dams contain a large amount of sediment, in excess of 27,000 t·yr−1 (90% of the sediment transported by Tafna), storage of sediment reduces the lifetime of reservoirs.
Advanced grazing-incidence techniques for modern soft-matter materials analysis

Advanced grazing-incidence techniques have developed significantly during recent years. With the ongoing progress in instrumentation, novel methods have emerged which allow for an in-depth morphology characterization of modern soft-matter materials. Examples are in situ and in operando grazing-incidence small-angle X-ray scattering (GISAXS), micro- and nanofocused GISAXS, time-of-flight (TOF) grazing-incidence small-angle neutron scattering (GISANS) and surface-sensitive resonant soft X-ray scattering techniques, including the potential to investigate polarization. Progress in software for data analysis is another important aspect.
A Thermistor-Based Temperature Sensor for a Real-Time Clock With $\pm$ 2 ppm Frequency Stability

This paper describes the design of a temperature sensor based on integrated poly-silicon thermistors. The thermistors are incorporated in a Wien-bridge RC filter, which, in turn, is embedded in a frequency-locked loop. The loop's output frequency is then determined by the filter's temperature-dependent phase shift, thus realizing an energy-efficient and high resolution temperature sensor. After a 3-point calibration, the sensor achieves an inaccuracy of less than ±0.12<sup>°</sup>C (min-max) from -40<sup>°</sup>C to 85<sup>°</sup>C. This translates into a frequency stability of better than ±2 ppm from -40<sup>°</sup>C to 85<sup>°</sup>C when the sensor is used to temperature compensate the quartz-crystal oscillator of a 32 kHz real-time clock. The 0.09 mm<sup>2</sup> sensor also achieves 2.8 mK (rms) resolution in a 32 ms conversion time while dissipating only 31 μW.
Metabolic Syndrome: The Danger Signal in Atherosclerosis

Atherosclerosis is a chronic inflammatory disease characterized by infiltration of blood vessels by lipids and leukocytes. There is a growing body of evidence that among risk factors that promote atherosclerosis, the metabolic syndrome is a powerful and prevalent predictor of cardiovascular events. The systemic inflammatory process associated with the metabolic syndrome has numerous deleterious effects that promote plaque activation, which is responsible for clinical events. Interactions between the innate immune system with lipid-derived products seem to play a major role in the pathophysiology of atherosclerosis in relation with the metabolic syndrome. The multiple links among adipose tissue, the vascular wall, and the immune system are the topics of this review, which examines the roles of oxidized low-density lipoprotein, inflammatory cytokines, and adipokines in triggering and perpetuating a danger signal response that promotes the development of atherosclerosis. Furthermore, therapeutic options that specifically target the metabolic syndrome components are reviewed in light of recent developments.
Limit distribution of degrees in random family trees

In a one-parameter model for evolution of random trees, which also includes the Barabasi-Albert random tree [1], almost sure behavior and the limiting distribution of the degree of a vertex in a fixed position are examined. A functional central limit theorem is also given. Results about Polya urn models are applied in the proofs.
Fusion based Multi Scale RETINEX with Color Restoration for image enhancement

Image fusion is a technique of combining two or more images so that the combined image is better enhanced than all these images. We propose that a fusion based approach on Multi Scale Retinex with Color Restoration(MSRCR) would give better image enhancement. Lower dynamic range of a camera as compared to human visual system causes images taken to be extremely dependent on illuminant conditions. MSRCR algorithm enhances images taken under a wide range of nonlinear illumination conditions to the level that a user would have perceived it in real time.
Accent classification with phonetic vowel representation

Previous accent classification research focused mainly on detecting accents with pure acoustic information without recognizing accented speech. This work combines phonetic knowledge such as vowels with acoustic information to build Guassian Mixture Model (GMM) classifier with Perceptual Linear Predictive (PLP) features, optimized by Hetroscedastic Linear Discriminant Analysis (HLDA). With input about 20-second accented speech, this system achieves classification rate of 51% on a 7-way classification system focusing on the major types of accents in English, which is competitive to the state-of-the-art results in this field.
Enabling Practical Software-defined Networking Security Applications with OFX

Software Defined Networks (SDNs) are an appealing platform for network security applications. However, existing approaches to building security applications on SDNs are not practical because of performance and deployment challenges. Network security applications often need to analyze and process traffic in more advanced ways than SDN data plane implementations, such as OpenFlow, allow. Much of an application ends up running on the centralized controller, which forms an inherent bottleneck. Researchers have proposed application specific modifications to the underlying data plane to gain performance, but this results in a solution that is not deployable as it requires new switches and does not support all network security applications. In this paper, we introduce OFX (the OpenFlow Extension Framework) which harnesses the processing power of network switches to enable practical SDN security applications within an existing OpenFlow infrastructure. OFX allows applications to dynamically load software modules directly onto unmodified network switches where application-dependent processing/monitoring can execute closer to the data plane at a rate much closer to line speed. We implemented OFX modules for security applications including Silverline (ACSAC’13), BotMiner (Sec’08), and several others motivated by the custom OpenFlow extensions in Avant-Guard (CCS’13). We evaluated OFX on a Pica 8 3290 switch and found that processing traffic in an OFX module running on the switch had orders of magnitude less overhead than processing traffic at the controller. OFX increased the performance of the evaluated security application by 20-40x as compared to standard OpenFlow implementations and up to 1.25x when compared to middlebox implementations running on dedicated servers. This is all achieved without the need for additional or modified hardware.
Motion velocity estimation from electroencephalography signals with extreme learning machine

Decoding motion velocity from electroencephalography (EEG) signals is important for brain-computer interface (BCI) research. However, no studies explore how to decode the velocity of complex motion. In this paper, we apply extreme learning machine (ELM) to explore how to decode the velocity of complex motion from EEG signals. We design a new experimental paradigm and analyze the effects of the number of hidden neuron nodes and frequency band on the decoding performance. This work lays a foundation of building accurate motion decoders from EEG signals to develop the BCI-based prostheses and rehabilitation systems.
An enhanced dominant sets clustering method

As a graph-based clustering approach, dominant sets clustering determines the number of clusters automatically and possesses some other nice properties. By applying histogram equalization transformation to the similarity matrix before clustering, we are able to accomplish the dominant sets clustering process without any user-specified parameters. However, this transformation usually leads to over-segmented clustering results. In this paper, we analyze the correlation between histogram equalization transformation and the over-segmentation tendency, and attribute the over-segmentation to the over-strict global density constraint imposed by the dominant set definition. Therefore we propose to relax the global density constraint to a local one, which is then used in dominant set extension. We test our algorithm in experiments of data clustering and image segmentation, and validate its effectiveness in comparison with the original dominant sets algorithm and other algorithms.
Migratory connectivity and population-specific migration routes in a long-distance migratory bird

Knowledge about migratory connectivity, the degree to which individuals from the same breeding site migrate to the same wintering site, is essential to understand processes affecting populations of migrants throughout the annual cycle. Here, we study the migration system of a long-distance migratory bird, the Montagu's harrier Circus pygargus, by tracking individuals from different breeding populations throughout northern Europe. We identified three main migration routes towards wintering areas in sub-Saharan Africa. Wintering areas and migration routes of different breeding populations overlapped, a pattern best described by ‘weak (diffuse) connectivity’. Migratory performance, i.e. timing, duration, distance and speed of migration, was surprisingly similar for the three routes despite differences in habitat characteristics. This study provides, to our knowledge, a first comprehensive overview of the migration system of a Palaearctic-African long-distance migrant. We emphasize the importance of spatial scale (e.g. distances between breeding populations) in defining patterns of connectivity and suggest that knowledge about fundamental aspects determining distribution patterns, such as the among-individual variation in mean migration directions, is required to ultimately understand migratory connectivity. Furthermore, we stress that for conservation purposes it is pivotal to consider wintering areas as well as migration routes and in particular stopover sites.