Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabonomics Reveals Drastic Changes in Anti-Inflammatory/Pro-Resolving Polyunsaturated Fatty Acids-Derived Lipid Mediators in Leprosy Disease

Despite considerable efforts over the last decades, our understanding of leprosy pathogenesis remains limited. The complex interplay between pathogens and hosts has profound effects on host metabolism. To explore the metabolic perturbations associated with leprosy, we analyzed the serum metabolome of leprosy patients. Samples collected from lepromatous and tuberculoid patients before and immediately after the conclusion of multidrug therapy (MDT) were subjected to high-throughput metabolic profiling. Our results show marked metabolic alterations during leprosy that subside at the conclusion of MDT. Pathways showing the highest modulation were related to polyunsaturated fatty acid (PUFA) metabolism, with emphasis on anti-inflammatory, pro-resolving omega-3 fatty acids. These results were confirmed by eicosanoid measurements through enzyme-linked immunoassays. Corroborating the repertoire of metabolites altered in sera, metabonomic analysis of skin specimens revealed alterations in the levels of lipids derived from lipase activity, including PUFAs, suggesting a high lipid turnover in highly-infected lesions. Our data suggest that omega-6 and omega-3, PUFA-derived, pro-resolving lipid mediators contribute to reduced tissue damage irrespectively of pathogen burden during leprosy disease. Our results demonstrate the utility of a comprehensive metabonomic approach for identifying potential contributors to disease pathology that may facilitate the development of more targeted treatments for leprosy and other inflammatory diseases.
On the Design of Global Refunding and Climate Change

We design a global refunding scheme as a new international approach to address climate change. A global refunding system allows each country to set its carbon emission tax, while aggregate tax revenues are partially refunded to member countries in proportion to the relative emission reductions they achieve within a given period, compared to some given baseline emissions. In a simple model we show that a suitably designed global refunding scheme is self-enforcing and achieves the social global optimum.
Validating Heuristics for Virtual Machines Consolidation

This paper examines two fundamental issues pertaining to virtual machines (VM) consolidation. Current virtualization management tools, both commercial and academic, enable multiple virtual machines to be consolidated into few servers so that other servers can be turned off, saving power. These tools determine effective strategies for VM placement with the help of clever optimization algorithms, relying on two inputs: a model of resource utilization vs performance tradeoff when multiple VMs are hosted together and estimates of resource requirements for each VM in terms of CPU, network and storage. This paper investigates the following key questions: What factors govern the performance model that drives VM placement, and how do competing resource demands in multiple dimensions affect VM consolidation? It establishes a few basic insights about these questions through a combination of experiments and empirical analysis. This experimental study points out potential pitfalls in the use of current VM management tools and identifies promising opportunities for more effective performance consolidation algorithms. In addition to providing valuable guidance to practitioners, we believe this paper will serve as a starting point for research into next-generation virtualization platforms and tools.
Learning TSK Fuzzy Model by GA-BP Method

It is difficult to learn TSK fuzzy model because the problem is multiconstraint and multitarget optimization. GA-BP hybrid learning method for the model is proposed. Some problems related to a species coding means for the model structure, evolution and fitness evaluation strategy are discussed. The error back propagation algorithm (BP) for training the antecedent and consequent parameters during the process of evolution is inferred. The characteristic of the method requests a little of previous information about objects, and avoids slow convergence, and has better adaptive capability, and is able to obtain compact and accurate fuzzy model from samples, the validity of the method has been demonstrated by an example of function approximation.
Travel preferences of Asian gay men

ABSTRACT Lesbian, gay, bisexual and transgender (LGBT) travel is an emerging theme within tourism academia. However, most research to date has focused on the Western context. The reviewed literature appears to assume gay market to be homogenous. The present study contributes to understanding of Asian gay men travel preferences. Qualitative analysis of interviews with Asian gay men is undertaken. Findings suggest that the following categories impact travel decisions among Asian gay men: centrality of being gay to self-identity, degree of disclosure of personal sexuality to others, level of disposable income, purpose of travel, safety and conservativeness of the destination. Moreover, the findings provide a classification for gay tourist attractions. The classification of gay attractions includes the following categories: site/event, exclusivity, popularity, commercialisation, type of benefits provided and political activism. The results point to high diversity of travel preferences among Asian gay men. Treatment of LGBT travellers as a single market is critiqued.
A Rate-distortion Optimized Motion Compensated Wavelet Video Coder

This paper presents a rate-distortion optimized wavelet video coder using variable block size motion estimation and region-based embedded wavelet coding. The optimization is achieved by the joint selection of all the control parameters in the motion estimation and residual coding. The Shannon Lower Bound is used for the rate and distortion estimation in the pixel domain. Experiments are performed at a range of bit rates and compared to MPEG-2 TM5 and H.263 TMN5. The resulting video demonstrates 0.2-1.3 dB PSNR gain as well as signiicantly improved visual quality.
PERCEPTION OF ENGLISH LEXICAL STRESS WITH A MARKED PITCH ACCENT BY NATIVE SPEAKERS OF MANDARIN

Three perceptual experiments were conducted to investigate the perception of English lexical stress with a marked nuclear pitch accent by native speakers of Taiwan Mandarin at the phonological and phonetic levels of processing. The stimuli were English disyllabic word pairs differing only in the position of the stress and in the morphosyntactic categories (e.g., PERmit (n.) vs. perMIT (v.)), presented for identification or discrimination. The general finding is that Mandarin-speaking learners of English performed in a native-like manner in the unmarked pitch accent context but not in the marked one. Further examination of their performance in the latter context revealed that while experienced learners failed to match the stress patterns with their morphosyntactic categories in the identification task, they could categorize them in the ABX task, which suggests that they were not phonologically deaf to stress. In contrast, inexperienced learners could not do the same, presumably deaf to stress at the phonological level. Yet, their sensitivity to both within- and across-category stress differences in the AX task indicates that they did not experience stress deafness at the phonetic level.
Defending the European political order

This article theorizes the European-level political response to the radical right by suggesting a focus on the conceptions of politics, society and of the European Union itself that inform this response. Analyses of the ways in which the political mainstream relates to such movements remain under-theorized and often fall back on understandings of political action in narrow instrumental terms. Instead, this article proposes an approach to this response which emphasizes the process through which shared understanding of the European political project surface. It engages with these issues by turning to ideas that emerged in relation to the rise of European fascism in the 1930s on how to mount an effective defence of democracy. The underlying social analysis that fed into such strategies, the article argues, serves as a useful framework for analysis of the contemporary European response to the radical right.
Investigating Test Teams' Defect Detection in Function test

In a case study, the defect detection for functional test teams is investigated. In the study it is shown that the test teams not only discover defects in the features under test that they are responsible for, but also defects in interacting components, belonging to other test teams' features. The paper presents the metrics collected and the results as such from the study, which gives insights into a complex development environment and highlights the need for coordination between test teams in function test.
Traffic loading impacts on throughput and energy performance related to MIMO scheduling techniques and dynamic carrier band switching

The ever-increasing focus on the environment has led to energy considerations throughout industry. The Mobile Phone industry is no exception. Researchers and Commercial organisations are examining system design and associated technologies which will minimize energy consumption whilst retaining current system performance. Techniques across the mobile industry are being considered from Energy Efficient air interface design to equipment "switch-off" (during periods of low usage). This paper considers the impact of, dual, co-located, system traffic loading in relation to Multiple Input Multiple Output (MIMO) scheduling techniques and Dynamic Carrier Band Switching for the 3GPP WCDMA Downlink in order to maximize throughput whilst ensuring Energy Efficiency.
Constructing tilting modules

We investigate the structure of (infinite dimensional) tilting modules over hereditary artin algebras. For connected algebras of infinite representation type with Grothendieck group of rank n, we prove that for each 0 < i < n - 1, there is an infinite dimensional tilting module T i with exactly i pairwise non-isomorphic indecomposable finite dimensional direct summands. We also show that any stone is a direct summand in a tilting module. In the final section, we give explicit constructions of infinite dimensional tilting modules over iterated one-point extensions.
Document summarization based on semantic representations

We present a novel extractive summarization method based on semantic vector representation. The new representation extends the word embedding, and represents words, phrases, sentences, paragraphs and documents in same vector space, which is used to measure the semantic similarity between sentences and document. Then we use greedy search algorithm to extract the summary sentences. The proposed method is evaluated on DUC01 dataset and employ F1-measure and ROUGE-N as metrics. The results show the proposed method outperforms comparison methods. The ROUGE-N is much higher than others.
Detection and recognition of sports(wo)men from multiple views

The methods presented in this paper aim at detecting and recognizing players on a sport-field, based on a distributed set of loosely synchronized cameras. Detection assumes player verticality, and sums the cumulative projection of the multiple views' foreground activity masks on a set of planes that are parallel to the ground plane. After summation, large projection values indicate the position of the player on the ground plane. This position is used as an anchor for the player bounding box projected in each one of the views. Within this bounding box, the regions provided by mean-shift segmentation are sorted out based on contextual features, e.g. relative size and position, to select the ones that are likely to correspond to a digit. Normalization and classification of the selected regions then provides the number and identity of the player. Since the player number can only be read when it faces towards the camera, graph-based tracking is considered to propagate the identity of a player along its trajectory.
Immediate Nonfunctional Loading of Two Single-Maxillary Postextractive Implants: 6-Year Postloading Results of Two Case Reports

Objectives. The aim of the study was to evaluate and compare crestal bone loss of single-maxillary immediate postextractive implants and immediate nonfunctional loading (INFL) during 72 months of follow-up. Material and Methods. Two single titanium implants (Certain Prevail, Biomet 3I, USA) were placed in two patients using INFL technique. Implant stability and crestal bone level were measured on periapical radiographs at 1, 3, and 6 months after surgery. Results. All osseointegrated implants were clinically successful after 6 years of functional loading. Conclusion. Within the limit of the present case report, the paper supports the concept that INFL of single dental implant can be a successful treatment procedure.
TraxBot - Assembling and Programming of a Mobile Robotic Platform

This work presents the TraxBot mobile robot design, a ground platform recently developed for applications in the mobile robotics field. The assembling of the robotic system, with description of its components as well as information about the microcontroller programming, development and testing are presented. The TraxBot is a multidisciplinary platform and is ideal for education, since it is easily programmed with opensource tools requiring basic knowledge of other areas beyond robotics, like mechanics, control or energy management. Although being released in a stable version, the robot is continually in development, with the ability to incorporate extensions to its design and new features.
The Design and Implementation of Time Synchronization for CNC Systems Based on Switched Ethernet

The method of reconstructing acceleration field was studied based on inversion of frequency response function matrix. In the method, the frequency response function (FRF) matrix was obtained. The vibration test was carried out and the test object was an underwater vehicle power-cabin. The results of theory study and test showed that the calculated precision by this method can satisfy the needs of the engineering application.
Feasibility of Structurally Synthesized BDD Models for Test Generation

An ATPG algorithm based on a special class of BDD models, called Structurally Synthesized BDDs (SSBDD), is presented. Experimental results show that the novel test generation approach provides a remarkable speed-up in comparison with classical gate-oriented methods. In addition, SSBDDs offer a more generalized view to the test generation problem.
Active , semi-supervised learning to utilize human oracles

We present an approach to interactive machine learning, in which unlabeled data is employed in conjunction with active learning to better utilize the valuable resources that the human oracles provide. We empirically evaluate the approach in two very different applications, smartphone interruptibility prediction and semantic parsing. In both applications, we show that the use of active, semi-supervised training results in an improvement compared to a traditionally trained classifier relying only on full-supervision with random sampling.
Multiresolution parameterization of meshes for improved surface-based registration

Common problems in medical image analysis involve surface-based registration. The applications range from atlas matching to tracking an object's boundary in an image sequence, or segmenting anatomical structures out of images. Most proposed solutions are based on deformable surface algorithms. The main problem of such methods is that the local accuracy of the matching must often be traded off against global smoothness of the surface in order to reach global convergence of the deformation process. Our contribution is to first build a Multi-Resolution (M-R) surface from a reference segmented image, and then match this surface onto the target image in an M-R fashion using a deformable surface-like algorithm. As we proceed from lower to higher resolution, the smoothing effect of the deformable surface is more and more localized, and the surface gets closer and closer to the target boundary. We present initial results of our algorithm for atlas registration onto brain MRI showing improved convergence and accuracy over classical deformable surface methods.
Exploring 3-D Reconstruction Techniques: A Benchmarking Tool for Underwater Robotics

When the results of research in the field of robotics are presented to the scientific community, the same question is asked repeatedly: Are the results really reproducible? Regarding benchmarking issues, some technological areas where complex mechatronic devices, such as robots, have a central role are very far from other research areas like physics or chemistry, to name but a few, where reproducibility is always mandatory. Aside from mechatronic complexities, the comparison between two different algorithms in the same conditions is influenced by the experimental validation scenario. In underwater environments, the difficulties for benchmarking characterization increase substantially. This is especially true when the test bed is the sea where uncertainty is high. It is the aim of this article to present a software tool which enables a comparison between two different algorithms when the algorithms are being used to solve the same problem in water tank conditions. This is a preliminary stage before the final validation on the seabed. The evaluated algorithms fall into the three-dimensional (3-D) image reconstruction context, as a prior step to their autonomous manipulation. Performance results are presented for both simulation and real water tank conditions.
Approximate Inverse Preconditioners via Sparse-Sparse Iterations

The standard incomplete LU (ILU) preconditioners often fail for general sparse indefinite matrices because they give rise to "unstable" factors L and U. In such cases, it may be attractive to approximate the inverse of the matrix directly. This paper focuses on approximate inverse preconditioners based on minimizing ||I-AM||F, where AM is the preconditioned matrix. An iterative descent-type method is used to approximate each column of the inverse. For this approach to be efficient, the iteration must be done in sparse mode, i.e., with "sparse-matrix by sparse-vector" operations. Numerical dropping is applied to maintain sparsity; compared to previous methods, this is a natural way to determine the sparsity pattern of the approximate inverse. This paper describes Newton, "global," and column-oriented algorithms, and discusses options for initial guesses, self-preconditioning, and dropping strategies. Some limited theoretical results on the properties and convergence of approximate inverses are derived. Numerical tests on problems from the Harwell--Boeing collection and the FIDAP fluid dynamics analysis package show the strengths and limitations of approximate inverses. Finally, some ideas and experiments with practical variations and applications are presented.
Visualization and Concept Drift Detection Using Explanations of Incremental Models

The temporal dimension that is ever more prevalent in data makes data stream mining (incremental learning) an important field of machine learning. In addition to accurate predictions, explanations of the models and examples are a crucial component as they provide insight into model's decision and lessen its black box nature, thus increasing the user's trust. Proper visual representation of data is also very relevant to user's understanding – visualization is often utilised in machine learning since it shifts the balance between perception and cognition to take fuller advantage of the brain's abilities. In this paper we review visualisation in incremental setting and devise an improved version of an existing visualisation of explanations of incremental models. Additionally, we discuss the detection of concept drift in data streams and experiment with a novel detection method that uses the stream of model's explanations to determine the places of change in the data domain.
SDN enabled SPIN routing protocol for wireless sensor networks

The wireless sensor networks are highly dynamic in nature and their storage, processing and energy resources are limited. For these conditions routing protocols are required to maintain the network with reliable and secure communication. Lot of protocols are designed for routing but none of the protocol is proposed security as a main task. We advocate that Software Defined Network (SDN) enabled SPIN routing protocol through novel design for security and energy efficient wireless sensor network. The feature of SDN such as programmability, abstraction, and openness can enhance security in wireless sensor networks. The hardware independent SDN with TinyOS is designed and implemented, the results concerning memory footprint, energy consumption, PDR and transmission delay latency presented.
Adaptive tracking control of underactuated surface vessels

We design a continuous, time-varying tracking controller for an underactuated surface vessel in the presence of uncertainty associated with the hydrodynamic damping coefficients. A Lyapunov-based approach is used to ensure that the position/orientation tracking error is ultimately confined to a ball that can be made arbitrarily small. The result is achieved via the judicious design of a dynamic oscillator in conjunction with two state transformations. We also illustrate how the proposed tracking controller yields the same stability result for the stabilization problem.
Adaptive Scheduling for QoS Virtual Machines under Different Resource Availability — First Experiences

The current trend in CPU design is toward many-core CPUs which will create SMP servers with large numbers of cores and require jobs to be parallel. To provide performance guarantees (QoS) and support functional separation, virtual machines are an important approach in such environments. Very promising for job scheduling in such environments is adaptive scheduling which can adjust sizes of parallel jobs to consider different load situations and different resource availability. If applied to virtual machines and resource partitioning on many-coreCPU / multiple CPU servers, the resource allocation can be determined at virtual-machine level and propagated down to the job sizes. The paper investigates job re-shaping and virtual-machine resizing, the effects which the efficiency curve of the jobs has on performance, and the potential for predictability of performance under different resource allocation.
Type classes with existential types

Abstract We argue that the novel combination of type classes and existential types in a single language yields significant expressive power. We explore this combination in the context of higher-order functional languages with static typing, parametric polymorphism, algebraic data types and Hindley–Milner type inference. Adding existential types to an existing functional language that already features type classes requires only a minor syntactic extension. We first demonstrate how to provide existential quantification over type classes by extending the syntax of algebraic data type definitions, and give examples of possible uses. We then develop a type system and a type inference algorithm for the resulting language. Finally, we present a formal semantics by translation to an implicitly-typed second-order λ-calculus and show that the type system is semantically sound. Our extension has been implemented in the Chalmers Haskell B. system, and all examples from this paper have been developed using this system.