Miracle-dz/UniFAR-FTUs huggingface dataset:
The use of amplified fragment length polymorphism in determining species trees at fine taxonomic levels: analysis of a medically important snake, Trimeresurus albolabris

There are a huge number of phylogenetic studies based on mitochondrial DNA (mtDNA); however, these may represent gene trees that may not be congruent with the species tree. A solution to this problem is to include additional, independent, loci from the nuclear genome. At fine taxonomic levels, i.e. between populations and closely related species, previously suggested nuclear markers such as intron sequence data may not be appropriate. In this study we investigate the use of amplified fragment length polymorphisms (AFLP) to aid determination of the species tree for 24 specimens of a medically important snake, Trimeresurus albolabris. This is of particular importance for many venomous snakes as venom often varies intraspecifically. Five different primer combinations produced 434 bands and were analysed by constructing a phylogenetic tree using neighbour joining and principal component analysis. Results were similar across all methods and found distinct groupings. The results were compared with mtDNA data and a reconciled tree was constructed in order to determine the species tree for T. albolabris. We found that T. albolabris (sensu lato) is not monophyletic. Specimens from the Indonesian islands (except West Java) form a distinct clade and we propose elevation to species level. A specimen from Nepal is also distinct and suggests that this population also deserves specific status. We suggest that AFLPs may prove a valuable aid in determining species trees as opposed to gene trees at fine taxonomic levels and this should facilitate the incorporation of molecular data into such activities as antivenom production and conservation management.
Gender Identification on Twitter Using the Modified Balanced Winnow

With the rapid growth of web-based social networking technologies in recent years, author identification and analysis have proven increasingly useful. Authorship analysis provides information about a document’s author, often including the author’s gender. Men and women are known to write in distinctly different ways, and these differences can be successfully used to make a gender prediction. Making use of these distinctions between male and female authors, this study demonstrates the use of a simple stream-based neural network to automatically discriminate gender on manually labeled tweets from the Twitter social network. This neural network, the Modified Balanced Winnow, was employed in two ways; the effectiveness of data stream mining was initially examined with an extensive list of n-gram features. Feature selection techniques were then evaluated by drastically reducing the feature list using WEKA’s attribute selection algorithms. This study demonstrates the effectiveness of the stream mining approach, achieving an accuracy of 82.48%, a 20.81% increase above the baseline prediction. Using feature selection methods improved the results by an additional 16.03%, to an accuracy of 98.51%.
Application of Multi Objective Evolutionary Programming to Combined Economic Emission Dispatch Problem

This paper describes a new multi-objective evolutionary programming (MOEP) method to solve the combined economic emission dispatch (CEED) problem. CEED is a multi-objective optimization problem by considering the fuel cost and emission as the objectives. It is converted into single objective optimization problem using weighted sum method. Hence the MOEP is proposed by employing the non-dominated solution ranking as selection mechanism for the bi-objective CEED problem. The developed algorithm is tested for a three-unit and a six-unit system. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto optimal solutions of the multi-objective CEED problem in a single run.
Principal Type Schemes for Gradual Programs

Gradual typing is a discipline for integrating dynamic checking into a static type system. Since its introduction in functional languages, it has been adapted to a variety of type systems, including object-oriented, security, and substructural. This work studies its application to implicitly typed languages based on type inference. Siek and Vachharajani designed a gradual type inference system and algorithm that infers gradual types but still rejects ill-typed static programs. However, the type system requires local reasoning about type substitutions, an imperative inference algorithm, and a subtle correctness statement. This paper introduces a new approach to gradual type inference, driven by the principle that gradual inference should only produce static types. We present a static implicitly typed language, its gradual counterpart, and a type inference procedure. The gradual system types the same programs as Siek and Vachharajani, but has a modular structure amenable to extension. The language admits let-polymorphism, and its dynamics are defined by translation to the Polymorphic Blame Calculus. The principal types produced by our initial type system mask the distinction between static parametric polymorphism and polymorphism that can be attributed to gradual typing. To expose this difference, we distinguish static type parameters from gradual type parameters and reinterpret gradual type consistency accordingly. The resulting extension enables programs to be interpreted using either the polymorphic or monomorphic Blame Calculi.
Location Type Classification Using Tweet Content

Location context in social media plays an important role in many applications. In addition to explicit location sharing via popular "check in" service, user-posted content could also implicitly reveals users' location context. Identifying such a location context based on content is an interesting problem because it is not only important in inferring social ties between people, but also vital for applications such as user profiling and targeted advertising. In this paper, we study the problem of location type classification using tweet content. We extend probabilistic text classification models to incorporate temporal features and user history information in terms of probabilistic priors. Experimental results show that our extensions can boost classification accuracy effectively.
The European Union Decides: List of tables

European legislation affects countless aspects of daily life in modern Europe but just how does the European Union make such significant legislative decisions? How important are the formal decision-making procedures in defining decision outcomes and how important is the bargaining that takes place among the actors involved? Using a combination of detailed evidence and theoretical rigour, this 2006 volume addresses these questions and others that are central to understanding how the EU works in practice. It focuses on the practice of day-to-day decision-making in Brussels and the interactions that take place among the Member States in the Council and among the Commission, the Council and the European Parliament. A unique data set of actual Commission proposals are examined against which the authors develop, apply and test a range of explanatory models of decision-making, exemplifying how to study decision-making in other political systems using advanced theoretical tools and appropriate research design.
E-Books in Higher Education: Technology, E-Marketing Prospects, and Pricing Strategy

This article describes an ongoing project on the use of electronic books (e-books) in a higher institution and starts with a discussion on the diversity of e-book definitions to address misconception of its concept. Then, the advantages and associated technology such as hardware, software, formats, and standards are detailed. Comparisons between formats, a discussion on where e-books can be acquired and purchased, the electronic publishing process, e-book compilers, and personalized e-books are also explained. The final part of this article highlights the idea of marketing e-books electronically to improve accessibility and also assist lecturers to market their publications. In addition, the results of investigating buyersâ€™ views are discussed briefly where a formula for pricing e-books based on student attitudes is also proposed.
S PEECH T RANS : An Experimental Real-Time Speech-to-Speech Translation System

This paper reports the current progress in the SPEECHTRANS project at the Center for Machine Translation which is a speech-to-speech translation project for real-time processing of speaker-independent noisy continuous speech input. SPEECHTRANS uses a custom speech recognition hardware and a phoneme-based generalized LR parser that uses a unification-based grammar formalism and a natural language generator that is connected to a voice synthesis module. SPEECHTRANS was originally presented at the MT Conference held at eMU in June 1988 as a public demonstration of a realtime speaker-independent speech-to-speech translation system.
Approaches for prioritizing feature improvements extracted from app reviews

App reviews contain valuable feedback about what features should be fixed and improved. This feedback could be 'mined' to facilitate app maintenance and evolution. While requirements are routinely extracted from post-release users' feedback in traditional projects, app reviews are often generated by a much larger client-base with competing needs and priorities and ad hoc structure. Although there has been interest aimed at exploring the nature of issues reported in app reviews (e.g., bugs and enhancement requests), prioritizing these outcomes for improving and evolving apps hasn't received much attention. In this preliminary study we aim to bridge this gap by proposing three prioritization approaches. Driven by literature in other domains, we identify four attributes (frequency, rating, negative emotions and deontics) that serve as the base constructs for prioritization. Thereafter, using these four constructs, we develop three approaches (individual attribute-based approach, weighted approach and regression-based approach) that may help developers to prioritize features for improvements. We evaluate our approaches in constructing multiple prioritized lists of features using reviews from the MyTracks app. It is anticipated that these prioritized lists could allow developers to better focus their efforts in deciding which aspects of their apps to improve.
Bilateral interpolation filters for image size conversion

This paper presents an image size conversion method based on bilateral filtering. We formulate interpolation with bilateral filters by an optimization problem, with which we can enforce the interpolation constraint as well as smoothness constraint. The designed bilateral filter can be used in image size conversion, providing better pass-band characteristics and less artifacts from aliasing.
Evidence theory for image segmentation using information from stochastic Watershed and Hessian filtering

In this paper; a new segmentation method is presented. It combines the probability density function of the stochastic Watershed and the Frobenius norm of the Hessian operator under the evidence theory framework. The first step of this method is a classification of the values provided by these two sources of information into five classes. Then, a predefined belief scheme is used to assign masses to pixels in each class. The segmentation result is obtained after beliefs fusion using the Dempster's rule of combination. The method is designed for two-label segmentation, contour and non-contour. Experimental results on a set of images from the Berkeley dataset, shows the ability of this method to yield a good segmentation compared to the given ground truths.
RetrogeneDB—A Database of Animal Retrogenes

Retrocopies of protein-coding genes, reverse transcribed and inserted into the genome copies of mature RNA, have commonly been categorized as pseudogenes with no biological importance. However, recent studies showed that they play important role in the genomes evolution and shaping interspecies differences. Here, we present RetrogeneDB, a database of retrocopies in 62 animal genomes. RetrogeneDB contains information about retrocopies, their genomic localization, parental genes, ORF conservation, and expression. To our best knowledge, this is the most complete retrocopies database providing information for dozens of species previously never analyzed in the context of protein-coding genes retroposition. The database is available at http://retrogenedb.amu. edu.pl.
A neural network based approach to support the Market Making strategies in High-Frequency Trading

Artificial Neural Networks (ANN) have been frequently applied to reduce risks and maximize the net returns in different types of algorithm trading. Using a real dataset, and aiming to support the Market Making process in High-Frequency Trading, this work investigates the use of a multilayer perceptron (MLP) to predict positive oscillations in short time periods (5, 10 or 15 minutes). The statistical analysis of our results showed that a neural network is more effective in short-term oscillations (5 minutes) when compared with the results obtained in longer periods (10 or 15 minutes). The result is important because it allows to insert a higher quantity of limit orders once they will be placed more frequently, which increases the market liquidity. It contextualizes a new contribution in the High-Frequency Trading field, where this work proposes a new trigger to start a market making process.
A Problem Space Approach to Expert System Specification

One view of expert system development separates the endeavor into two parts. First, a domain expert, with the aid of a knowledge engineer, articulates a procedure for performing the desired task in some external form. Next, the knowledge engineer operationalizes the external description within some computer language. This paper examines the nature of the processes that operationalize natural task descriptions. We exhibit a language based on a computational model of problem spaces for which these processes are quite simple. We describe the processes in detail, and discuss which aspects of our computational model determine the simplicity of these processes.
Likelihood of External Causation in the Structure of Events

This article addresses the causal structure of events described by verbs: whether an event happens spontaneously or it is caused by an external causer. We automatically estimate the likelihood of external causation of events based on the distribution of causative and anticausative uses of verbs in the causative alternation. We train a Bayesian model and test it on a monolingual and on a bilingual input. The performance is evaluated against an independent scale of likelihood of external causation based on typological data. The accuracy of a two-way classification is 85% in both monolingual and bilingual setting. On the task of a three-way classification, the score is 61% in the monolingual setting and 69% in the bilingual setting.
The microstructure of petroleum vacuum residue films for bituminous concrete: a microscopy approach

Selected carbon‐rich refinery residues (‘binders’) mixed with mineral particles can form composite materials (‘bituminous concrete’) with bulk mechanical properties comparable to those of cement concrete. The microstructural mechanism underlying the remarkable composite properties has been related to the appearance of a rigid percolating network consisting of asphaltenes and mineral particles [ Wilbrink M. et al. (2005) Rigidity percolation in dispersions with a structured visco‐elastic matrix. Phys. Rev. E71, 031402]. In this paper, we explore the microstructure of thin binder films of varying thickness with a number of microscopic characterization techniques, and attempt to relate the observed microstructure to the distinctive mechanical behaviour. Two binders, only one of which has been proven to be suitable for bituminous concrete were investigated, and their microstructure compared. Both binders show the formation of asphaltene aggregates. The binder suitable for bituminous concrete is distinguished by the fact that the asphaltenes show a stronger tendency towards such aggregation, due to a higher concentration and less stabilization in the maltene phase. They also show a clear affinity to other species (such as waxes) and may act as nucleation sites for crystals and aggregates of those species.
The Event Heap : An Enabling Infrastructure for Interactive Workspaces

As computers and large displays become cheaper, additional modes of human computer interaction are becoming possible. One can now set up an interactive workspace in which multiple computer displays and input devices are simultaneously visible and usable by one or more users. Unfortunately, the well-known event queue metaphor, which works well for a single user sitting in front of a single computer using a GUI, breaks down in such an interactive workspace. We propose the Event Heap as a novel mechanism by which multiple users, machines and applications can all simultaneously interact as consumers and generators of system events. The Event Heap is flexible, robust to failure of individual interactors, and sufficiently lightweight to be integrated easily with “legacy” single-user-GUI applications.
The Pursuit of Accountability: Promise, Problems, and Prospects

This paper examines the status of the accountability research and practice in Public Administration. It focuses on issues related to the widespread and growing use of the concept in PA and related sectors, highlighting the various promises of accountability that make it so attractive to those seeking reform and improvement in governance and administration. It reviews some of the major problems encountered by those studying accountability and concludes with a discussion of some prospects for enhancing our understanding of the subject.
NUMERICAL STUDY OF BUOYANCY EFFECTS ON TRIPLE FLAMES

The structure and propagation properties of triple flames subject to buoyancy effects are studied numerically using a high accuracy scheme. A wide range of gravity conditions, heat release, and mixing widths for a scalar mixing layer are computed for ’upright’ and ’inverted’ triple flames (i.e, gravity pointed in parallel and in opposite directions of flame propagation). These results are used to identify non-dimensional quantities, which parameterize the triple flame response. Computed results show that buoyancy effects act primarily to modify the overall size of the triple flame in response to gas acceleration through the two premixed branches. The impact of buoyancy on the structure of triple flame is found less pronounced than the general physical shape of the branches. The trailing diffusion branch is affected by buoyancy primarily due to the changes in the overall flame shape. The overall size of triple flame is determined by the two premixed branches. Buoyancy affects the locations of these premixed flames and consequently modifies the rates of diffusion of excess fuel and oxidizer from the premixed branches to the diffusion branch. A simple analytical model for the triple flame, which accounts for both buoyancy and heat release is developed. Comparisons of the proposed model for the triple flame speed with the numerical results for a wide range of gravity, heat release and mixing width conditions, yield good agreement.
Multi-Agent Architectures for E-Business Information Systems : An Organizational Perspective

A Multi-Agent System (MAS) is an organization of coordinated autonomous agents that interact in order to achieve particular, possible common goals. Considering real world organizations as an analogy, this paper proposes MAS architectural patterns for information systems which adopt concepts from organizational theories. The patterns are modeled using the i* framework which offers the notions of actor, goal and actor dependency and specified in Formal Tropos and evaluated with respect to a set of software quality attributes, such as predictability or adaptability. We conduct a comparison of organizational and conventional software architectures using an e-business information system case study. Theme: Architecture, Systems and Infrastructure
Backoff Window Based on Congestion Prediction Algorithm in Wireless Networks

We propose an algorithm to choose a reasonable backoff window based on prediction of the congestion of downstream and upstream nodes. The algorithm listens to the number of consecutive idle slots of the wireless network, then calculates the congestion and feeds it back to the downstream node and upstream node. When sending packets, a reasonable backoff window is chosen, depending on downstream and upstream node congestion. Simulation results show that the proposed approach can provide good performance, high throughput, low collision overhead, and low delay.
Patent image retrieval: a survey

Drawings are an important component of patents, and many search tasks in the intellectual property domain rely on the comparison of patent drawings. In this paper, we begin with a review of algorithms developed for the automated retrieval of similar images in the patent domain. There is however a larger body of research dedicated to analysis and retrieval of images found in technical documents that is also applicable to the images found in patents. We present an overview of this research for technical drawings, diagrams, charts, plots and chemical structures. Finally, we discuss the evaluation of image retrieval for patents, including short descriptions of the new patent image evaluation tasks in the CLEF-IP and TREC-CHEM evaluation campaigns in 2011.
The in vitro toxicology of Swedish snus

Three commercial brands of Swedish snus (SWS), an experimental SWS, and the 2S3 reference moist snuff were each tested in four in vitro toxicology assays. These assays were: Salmonella reverse mutation, mouse lymphoma, in vitro micronucleus, and cytotoxicity. Water extractions of each of the 5 products were tested using several different concentrations; the experimental SWS was also extracted using dimethyl sulfoxide (DMSO). Extraction procedures were verified by nicotine determinations. Results for SWS in the mutagenicity assays were broadly negative: there were occasional positive responses, but these were effectively at the highest concentration only (concentrations well above those suggested by regulatory guidelines), and were often associated with cytotoxicity. The 2S3 reference was unequivocally positive in one of the three conditions of the micronucleus assay (MNA), at the highest concentration only. Positive controls produced the expected responses in each assay. The SWS data are contrasted with data reported for combusted tobacco in the form of cigarettes, where strongly positive responses have been routinely reported for mutagenicity and cytotoxicity. These negative findings in a laboratory setting concur with the large amount of epidemiological data from Sweden, data showing that SWS are associated with considerably lower carcinogenic potential when compared with cigarettes.
Functional-analytic and numerical issues in splitting methods for total variation-based image reconstruction

Variable splitting schemes for the function space version of the image reconstruction problem with total variation regularization (TV-problem) in its primal and pre-dual formulations are considered. For the primal splitting formulation, while existence of a solution cannot be guaranteed, it is shown that quasi-minimizers of the penalized problem are asymptotically related to the solution of the original TV-problem. On the other hand, for the pre-dual formulation, a family of parametrized problems is introduced and a parameter dependent contraction of an associated fixed point iteration is established. Moreover, the theory is validated by numerical tests. Additionally, the augmented Lagrangian approach is studied, details on an implementation on a staggered grid are provided and numerical tests are shown.