Miracle-dz/UniFAR-FTUs huggingface dataset:
The So-called “Bar” in the Large Magellanic Cloud

We propose that the off-centered "bar" in the Large Magellanic Cloud (LMC) is an unvirialized structure slightly misaligned with, and offset from, the plane of the LMC disk. The small displacement and misalignment are consequences of recent tidal interactions with the Small Magellanic Cloud and the Galaxy. This proposal, although radical, is consistent with the kinematics of the LMC and the near-infrared star count maps from the Deep Near-Infrared Survey and the 2 Micron All-Sky Survey and, in particular, with the reported 25°-50° inclination range of the LMC and the east-west gradient of distance moduli of standard candles. Contributions to LMC microlensing come mainly from the mutual lensing of stars in the disk and the "bar. " The predicted microlensing optical depth is at levels comparable to observation, even without including contributions from MACHOs. Observational tests are suggested to discriminate between our misaligned offset "bar" model and the conventional picture of an off-centered planar bar.
Correction: In Vivo Expression Technology Identifies a Novel Virulence Factor Critical for Borrelia burgdorferi Persistence in Mice

Analysis of the transcriptome of Borrelia burgdorferi, the causative agent of Lyme disease, during infection has proven difficult due to the low spirochete loads in the mammalian tissues. To overcome this challenge, we have developed an In Vivo Expression Technology (IVET) system for identification of B. burgdorferi genes expressed during an active murine infection. Spirochetes lacking linear plasmid (lp) 25 are non-infectious yet highly transformable. Mouse infection can be restored to these spirochetes by expression of the essential lp25-encoded pncA gene alone. Therefore, this IVET-based approach selects for in vivo-expressed promoters that drive expression of pncA resulting in the recovery of infectious spirochetes lacking lp25 following a three week infection in mice. Screening of approximately 15,000 clones in mice identified 289 unique in vivo-expressed DNA fragments from across all 22 replicons of the B. burgdorferi B31 genome. The in vivo-expressed candidate genes putatively encode proteins in various functional categories including antigenicity, metabolism, motility, nutrient transport and unknown functions. Candidate gene bbk46 on essential virulence plasmid lp36 was found to be highly induced in vivo and to be RpoS-independent. Immunocompetent mice inoculated with spirochetes lacking bbk46 seroconverted but no spirochetes were recovered from mouse tissues three weeks post inoculation. However, the bbk46 gene was not required for B. burgdorferi infection of immunodeficient mice. Therefore, through an initial IVET screen in B. burgdorferi we have identified a novel in vivo-induced virulence factor critical for the ability of the spirochete to evade the humoral immune response and persistently infect mice.
Cognitive Questions in Software Visualisation

Software visualisation is nifty stuff; but is it the powerful cognitive tool it is often assumed to be? This chapter attempts to moderate the understandable enthusiasm for software visualisation and to raise some of the questions for which the discipline doesn’t yet have answers. The chapter is structured as a list of questions with discussion. The questions are not a comprehensive analysis of cognitive challenges in software visualisation. Rather, the chapter attempts to provide a list sufficiently provocative to give designers pause, in order:
Enhancement for Accurate Stream Prefetching

One fundamental approach to improve memory hierarchy performance is to prefetch the needed instructions and data before their usage when cache capacity is limited. A stream prefetcher captures a sequence of nearby misses when their addresses follow the same positive or negative direction in a small memory region [17]. Once a stream of cache misses is identified, the prefetcher prefetches consecutive blocks in the same direction. In this paper, we describe several enhancement techniques to improve weakness of existing stream-based prefetchers. First, the existing stream prefetcher does not take streams with constant stride into consideration. For long-stride accesses across more than one block, prefetching consecutive blocks is wasteful and pollutes the cache. Second, in accessing a data structure through pointers such as trees and graphs, each node in the data structure may occupy more than one block. Hence, accesses within a node may have different addressing direction than the traversal direction through the nodes. Due to this noise, the stream may not be identified and the prefetch opportunity is wasted. Third, regular streams for array accesses are often repeated. Penalty occurs for reestablishing a repeated stream. Fourth, an established stream may be ended before being removed from the prefetch table. A hit to a dead stream causes inaccurate prefetches. Performance evaluations based on SPEC applications show that the enhanced stream prefetcher improves 37.6%, 41.6%, and 54.5% of CPI for the three cache configurations with respect to the base design without prefetching. In comparison with the original stream prefetcher, the improvements are 1.8%, 17.6%, and 18.7% respectively.
On the Benefits and the Limits of ` p-norm Multiple Kernel Learning In Image Classification

Many modern applications from the domain of image classification, such as natural photo categorization, come with highly variable concepts; to this end, state-of-theart solutions employ a large number of heterogeneous image features, leaving a demand for combining information across many descriptors. In the paradigm of kernel-based learning, the multiple kernel learning (MKL) framework offers a principled way for learning linear combinations of feature groups / kernels — but the classical formulation is known to have limits in practice. We compare regular MKL with the recent `p-norm multiple kernel learning methodology and the SVM using uniform kernel combination on VOC2009 and ImageCLEF2010 datasets using Bagof-Words and simpler features. In our experiments we find advantages and shortcomings.
Loose Commitment in Medium-Scale Macroeconomic Models: Theory and an Application

This paper proposes a method and a toolkit for solving optimal policy with imperfect commitment in linear quadratic models. As opposed to the existing literature, our method can be employed in medium- and large-scale models typically used in monetary policy. We apply our method to the Smets and Wouters (2007) model, where we show that imperfect commitment has relevant implications for the interest rate setting, the sources of business cycle fluctuations, and welfare.
Path planning and obstacle avoidance for vision guided quadrotor UAV navigation

In this paper, we implement a path planning algorithm and combine with an obstacle avoidance system for a small commercial quadrotor vehicle. To keep the flight safe, the quadrotor navigates with the vision information for obstacle detection. A sequence of images are captured from the onboard camera and used for visual guidance. The optical flow is computed from the images and the derived depth cues are used to detect incoming obstacles. We implement the algorithm on an embedded system and use a single-board computer as the control platform. The experiments carried out in the outdoor environment show the feasibility of our technique for path planning and autonomous navigation.
Algorithm 2 The MWEU algorithm 1 : Initialization : ( The same with Algorithm 1 )

Two utility based dynamic subcarrier allocation (DSA) algorithms: the max exponential utility (MEU) algorithm and the max weighted exponential utility (MWEU) algorithm are proposed for quality of service (QoS) guarantees in single carrier frequency division multiple access (SC-FDMA) system. With the objective of maximizing the system total utility, the two proposed DSA algorithms are designed based on a cross-layer manner so as to guarantee the diverse QoS requirements of real-time traffic. The proposed MEU algorithm exploits the property of the exponential utility function to provide higher allocation priority for the user in heavy traffic load. Furthermore, the MWEU algorithm is proposed as a kind of priority adjustable DSA scheduling by introducing the grading theory and the weight factor into the utility function. Simulation results indicate that the MEU algorithm is able to achieve outstanding average delay and system rate-sum capacity performance. And the MWEU algorithm can further improve the delay variance and delay violation probability performance by setting appropriate allocation weights. It is also concluded that the adaptive weight factor value of the MWEU algorithm can be derived according to the practical QoS requirements and average packets arrival rate.
The multi-mode inertial tracking system for unconstrained indoor positioning

In the following work the multi-mode inertial tracking system is proposed. The system tries to bypass the constraints regarding the device placement and typical usage scenario. The system consists of four principal modules. The first one is the data pre-processing and calibration module: it automatically calibrates the accelerometer, gyroscope and magnetometer sensors. The simple calibration is employed for the accelerometer and the gyroscope, while the magnetometer is being calibrated in realtime using Stochastic Gradient Descent approach. The second module recovers the trajectory of the pedestrian and is able to separate the forward and backward steps of the user. The third module is an orientation estimation filter with magnetometer disturbance detector. For orientation estimation a well-known complementary filter is employed. To adaptively tune the magnetometer filter gain the residuals between the virtual gyroscope and the real one are continuously handled. The fourth module is responsible for the power management of the whole system. The key features of the proposed system is that it does not restrict typical user behaviour, automatically adapts to the used sensors and could be easily fused with any existing localization technology. The first section of the paper is devoted to the practical aspects of implementation of such system for embedded devices.
Providing Arguments in Discussions on the Basis of the Prediction of Human Argumentative Behavior

Argumentative discussion is a highly demanding task. In order to help people in such discussions, this article provides an innovative methodology for developing agents that can support people in argumentative discussions by proposing possible arguments. By gathering and analyzing human argumentative behavior from more than 1000 human study participants, we show that the prediction of human argumentative behavior using Machine Learning (ML) is possible and useful in designing argument provision agents. This paper first demonstrates that ML techniques can achieve up to 76% accuracy when predicting people’s top three argument choices given a partial discussion. We further show that well-established Argumentation Theory is not a good predictor of people’s choice of arguments. Then, we present 9 argument provision agents, which we empirically evaluate using hundreds of human study participants. We show that the Predictive and Relevance-Based Heuristic agent (PRH), which uses ML prediction with a heuristic that estimates the relevance of possible arguments to the current state of the discussion, results in significantly higher levels of satisfaction among study participants compared with the other evaluated agents. These other agents propose arguments based on Argumentation Theory; propose predicted arguments without the heuristics or with only the heuristics; or use Transfer Learning methods. Our findings also show that people use the PRH agents proposed arguments significantly more often than those proposed by the other agents.
Fast Computation of Exponential B-splines

This paper proposes a fast method for the calculation of exponential B-splines sampled at regular intervals. This algorithm is based on a combination of FIR and IIR filters which enables a fast decomposition and reconstruction of a signal. When complex values are selected for the parameters of the exponentials, complex trigonometric functions are obtained. Only the real part of these functions are used for the interpolation of real signals, leading less bandlimited signals when they are compared with the polynomial B-spline counterparts. These characteristics were verified with 1-D and 2-D examples.
INTERPOLATION-BASED FUZZY REASONING IN BEHAVIOUR-BASED CONTROL STRUCTURES

Some difficulties emerging during the construction of fuzzy behaviour-based control structures are inherited from the type of the applied fuzzy reasoning. Classical fuzzy reasoning methods need a complete fuzzy rule base. In case of fetching fuzzy rules directly from expert knowledge e.g. for the behaviour coordination module, the way of building a complete rule base is not always straightforward. One simple solution for overcoming the necessity of the complete rule base is the application of interpolation-based fuzzy reasoning methods, since interpolation-based fuzzy reasoning methods can serve usable (interpolated) conclusion even if none of the existing rules is hit by the observation. These methods can save the expert from dealing with derivable rules and help to concentrate on cardinal actions only. For demonstrating the applicability of the interpolation-based fuzzy reasoning methods in behaviourbased control structures a simple interpolation-based fuzzy reasoning method and its adaptation for behaviour-based control will be discussed briefly in this paper.
Community Detection and Analysis in the Bitcoin Network CS 224 W Final Report April

Bitcoin is a decentralized payment system and electronic cryptocurrency first published in 2009, which has steadily grown to a market cap of around $4 trillion USD and over 150k transactions a day. Through the use of ingenious cryptographic techniques to sign transactions and determine control of funds, Bitcoin is a peer-to-peer system where users transact directly, without need for an intermediary, and in which transactions are recorded, for posterior verification by all nodes, in a public, distributed ledger called a Blockchain. Given the public nature of the Blockchain, in which every transaction is recorded, it provides an excellent source of data from which to infer and analyze flows of funds and connections between users.
What should autism research focus upon? Community views and priorities from the United Kingdom

The rise in the measured prevalence of autism has been accompanied by much new research and research investment internationally. This study sought to establish whether the pattern of current UK autism research funding maps on to the concerns of the autism community. Interviews and focus groups were conducted with autistic adults, family members, practitioners and researchers to identify their priorities for research. We also captured the views of a large number of stakeholders via an online survey. There was a clear disparity between the United Kingdom’s pattern of funding for autism research and the priorities articulated by the majority of participants. There was general consensus that future priorities for autism research should lie in those areas that make a difference to people’s day-to-day lives. There needs to be greater involvement of the autism community both in priority setting and in research more broadly to ensure that resources reach where they are most needed and can make the most impact.
Towards predicting feature defects in software product lines

Defect-prediction techniques can enhance the quality assurance activities for software systems. For instance, they can be used to predict bugs in source files or functions. In the context of a software product line, such techniques could ideally be used for predicting defects in features or combinations of features, which would allow developers to focus quality assurance on the error-prone ones. In this preliminary case study, we investigate how defect prediction models can be used to identify defective features using machine-learning techniques. We adapt process metrics and evaluate and compare three classifiers using an open-source product line. Our results show that the technique can be effective. Our best scenario achieves an accuracy of 73 % for accurately predicting features as defective or clean using a Naive Bayes classifier. Based on the results we discuss directions for future work.
An ASIC Implementation and Evaluation of a Profiled Variable Length Instruction Set Architecture Master of Science Thesis

This thesis presents implementation of an extension to an existing instruction set architecture, which gains considerable reduction in power consumption. The reduction in power consumption is achieved through coding of the most frequently executed instructions in a short format done by the compiler based on a profile of previous executions. This leads to fewer accesses to the instruction cache and that more instructions can fit in the cache. Another major advantage is the reduction in the number of instruction fetch cycles which will also contribute significantly towards reduction in power consumption. The work involves implementing the new processor front-end architecture in ASIC and estimation of power-consumption compared to the normal architecture. Power was estimated using both RTL and gate level estimation methods. As an extension to the thesis the possible architectures which could be implemented in the case of superscalar processors are also discussed. 4 5 Acknowledgments This Master thesis has been the most rewarding experiences in my years of study. I was very much involved in this project which made me learn and enjoy doing. I was able to experience the different stages of developing the hardware from ideas to complete implementation in hardware. I am thankful to all who have supported me and discussed every new idea that encountered during my thesis period. I was also able to experience writing a research paper which is the most valuable thing I have gained as a part of my thesis. Most of all I would like to thank my advisor Mikael Collin who had guided me in all the stages where I needed support which helped me to make my design in the right direction. It was a very nice experience especially when we worked together for the submission of Research paper related to my thesis. I would like to thank Jimson Mathew, Erland Nilsson and Miegen Shen who had helped me with the tools and guided me in the proper way. Finally I would like to thank my Examiner Mats Brorsson who had given me all the support and ideas in dealing with my thesis even in his busy schedule. Also I am very grateful for his guidance in writing the Research paper and for the encouragement he had given me in developing new ideas related to my thesis work.
Design of a virtual mechanism for trajectory tracking of convoys of mobile robots

This paper proposes a control law to emulate the behavior of a standard n-trailer using a multi-agent robot system conformed by a group of unicycle-type robots. A sliding kingpin technique is used in order to reduce or completely eliminate the off-tracking (oversteer phenomenon) that the trailers of this kind of systems exhibit when they are following trajectories with a certain radius of curvature. Numerical simulations show the performance of the control law and a comparison is made between the control law with and without the sliding kingpin technique.
Perceptual Processing Affects Conceptual Processing

According to the Perceptual Symbols Theory of cognition (Barsalou, 1999), modality-specific simulations underlie the representation of concepts. A strong prediction of this view is that perceptual processing affects conceptual processing. In this study, participants performed a perceptual detection task and a conceptual property-verification task in alternation. Responses on the property-verification task were slower for those trials that were preceded by a perceptual trial in a different modality than for those that were preceded by a perceptual trial in the same modality. This finding of a modality-switch effect across perceptual processing and conceptual processing supports the hypothesis that perceptual and conceptual representations are partially based on the same systems.
Effectiveness of a mobile health intervention on infant and young child feeding among children ≤ 24 months of age in rural Islamabad over six months duration [version 1; peer review: 3 approved with reservations]

Background: Childhood development is highly influenced by feeding practices at the infancy and young age of children. Unfortunately, according to the National Nutrition Survey (2011), the prevalence of exclusive breastfeeding in Pakistan was 21% at four months, and 13% at six months of age with 51.3% of mothers initiating semisolid foods to their children at the recommended 6-8 months of age. The latest Pakistan Demographic & Health Survey (PDHS 2018) however; indicates that only 48% of infants are exclusively breastfed which has been improved from 38% as reported in the past five years but still more improvement is anticipated. Methods: A quasi-experimental study design was employed for this post-intervention survey assessing effectiveness of mobile health (mhealth) regarding infant & young child feeding (IYCF) among pregnant and lactating mothers in Tarlai, Islamabad from May to June 2018. A total of 135 mothers who were earlier included in the intervention phase were recruited after obtaining verbal & written consent. The data was entered in EpiData (3.1) and analyzed in SPSS version 21. Results: The mean age of these pregnant and lactating mothers was Open Peer Review
Accumulated Citation Count as Fertileness of Scientific Article

The literature survey by scientific bibliographic data base is indispensable in the research activities. We can find related articles with appropriate keywords. However, the threads of related research are not easy to grasp from the search result. It is necessary to repeat a search, judge a citation relation and figure out the thread. The present paper proposes the index "accumulated citation count" of a scientific article to measure the thread of citations that starts from the article.
On the meaning of computer models of robot- environment interaction

The “meaning” of a computer model — a computer simulation — of some physical system is an ill-defined concept, and clearly it would strengthen any hypotheses based on such models if some formal model verification was possible. In this paper we present experiments on computer modelling of mobile robot operation, in which the interaction of a Scitos G5 mobile robot with a carefully chosen environment is modelled. The experimental setup chosen was such that we could determine from theoretical considerations what the model should be. The comparison between the actually obtained computer model and the theoretically correct solution demonstrates that in the experiments conducted the obtained models are “correct”. Disciplines Physical Sciences and Mathematics Publication Details Nehmzow, U. , McKerrow, P. J. & Billings, S. 2007, ''On the meaning of computer models of robotenvironment interaction'', Proceedings TAROS'07: Towards Robots and Systems, University of Wales, Aberystwyth, pp. 33-39. This conference paper is available at Research Online: http://ro.uow. edu.au/infopapers/3016 On the Meaning of Computer Models of Robot-Environment Interaction Ulrich Nehmzow, Phillip McKerrow and Steve Billings University of Essex, UK University of Wollongong, Australia University of Sheffield, UK