Miracle-dz/UniFAR-FTUs huggingface dataset:
One-sided Logic in Two-sided Markets

In this paper, I consider eight basic fallacies that can arise from using conventional wisdom from one-sided markets in two-sided market settings. These fallacies are illustrated using statements made in the context of regulatory investigations into credit card schemes in Australia and the United Kingdom. I discuss how these fallacies may be reconciled by proper use of a two-sided market analysis, making reference to the relevant economics literature where applicable. The analysis is supported by observations on other two-sided markets.
Statistical approach for behavior detection of routing metrics in MANET

Mobile ad-hoc network technology has gained popularity in recent years by researchers on account of its flexibility, low cost and each of deployment. The objective of this paper is to model the behavior of routing metrics in MANET for different protocols. These metrics have been generated by Network Simulator NS 2.34 tools and the node movement has been generated using Bonmotion 1.4. The metrics behavior for each protocol is hypothesized to be dependent on node density, pause time, number of packets transferred, and the number of connection. A statistical model is implemented on MATLAB 7.0 and the model is found to be satisfactory with fitness value almost ideal value (1.0).
Imaging of leiomyosarcoma of the inferior vena cava: comparison of 2 cases and review of the literature

Abstract Leiomyosarcoma of the inferior vena cava is a rare tumour arising from the smooth muscle fibres of the media with a mean size at diagnosis generally around 12 cm (range 2–38 cm). This study compares a 4-cm leiomyosarcoma of the inferior vena cava discovered incidentally with a symptomatic late stage leiomyosarcoma.
Treat samples differently: Object tracking with semi-supervised online CovBoost

Most feature selection methods for object tracking assume that the labeled samples obtained in the next frames follow the similar distribution with the samples in the previous frame. However, this assumption is not true in some scenarios. As a result, the selected features are not suitable for tracking and the “drift” problem happens. In this paper, we consider data's distribution in tracking from a new perspective. We classify the samples into three categories: auxiliary samples (samples in the previous frames), target samples (collected in the current frame) and unlabeled samples (obtained in the next frame). To make the best use of them for tracking, we propose a novel semi-supervised transfer learning approach. Specifically, we assume only target samples follow the same distribution as the unlabeled samples and develop a novel semi-supervised CovBoost method. It could utilize auxiliary samples and unlabeled samples effectively when training the best strong classifier for tracking. Furthermore, we develop a new online updating algorithm for semi-supervised CovBoost, making our tracker handle with significant variations of the tracked target and background successfully. We demonstrate the excellent performance of the proposed tracker on several challenging test videos.
The ModelCraft framework: Capturing freehand annotations and edits to facilitate the 3D model design process using a digital pen

Recent advancements in rapid prototyping techniques such as 3D printing and laser cutting are changing the perception of physical 3D models in architecture and industrial design. Physical models are frequently created not only to finalize a project but also to demonstrate an idea in early design stages. For such tasks, models can easily be annotated to capture comments, edits, and other forms of feedback. Unfortunately, these annotations remain in the physical world and cannot easily be transferred back to the digital world. Our system, ModelCraft, addresses this problem by augmenting the surface of a model with a traceable pattern. Any sketch drawn on the surface of the model using a digital pen is recovered as part of a digital representation. Sketches can also be interpreted as edit marks that trigger the corresponding operations on the CAD model. ModelCraft supports a wide range of operations on complex models, from editing a model to assembling multiple models, and offers physical tools to capture free-space input. Several interviews and a formal study with the potential users of our system proved the ModelCraft system useful. Our system is inexpensive, requires no tracking infrastructure or per object calibration, and we show how it could be extended seamlessly to use current 3D printing technology.
Eureka: a new 5-degree-of-freedom redundant parallel mechanism with high tilting capabilities

This paper introduces Eureka, a new parallel mechanism providing five motions: three translations plus two rotations. This device is able to reach high tilting angles (/spl plusmn/90/spl deg/ about a first given axis and a whole revolution about the following axis). This is due to actuation redundancy and to the specific traveling plate. Kinematic models are derived. Due to its particular shape the forward geometrical model is also derived easily. A plot of its well conditioned workspace is given. Practical designs, free of self-collisions, are shown.
Aligned grains and inferred toroidal magnetic fields in the envelopes of massive young stellar objects

Massive young stellar objects (YSOs), like low-mass YSOs, are thought to be surrounded by optically thick envelopes and/or discs and are observed to have associated regions that produce polarized light at near-infrared wavelengths. These polarized regions are thought to be lower-density outflows along the polar axes of the YSO envelopes. Using the 0.2-arcsec spatial resolution of the Near-Infrared Camera and Multi-Object Spectrometer on the Hubble Space Telescope we are examining the structure of the envelopes and outflow regions of massive YSOs in star-forming regions within a few kpc of the Sun. Here we report on 2-µm polarimetry of Mon R2-IRS3, S140-IRS1, and AFGL 2591. All three sources contain YSOs with highly-polarized monopolar outflows, with Mon R2-IRS3 containing at least two YSOs in a small cluster. The central stars of all four YSOs are also polarized, with position angles perpendicular to the directions of the outflows. We infer that this polarization is due to scattering and absorption by aligned grains. We have modelled our observations of S140-IRS1 and AFGL 2591 as light scattered and absorbed both by spherical grains and by elongated grains that are aligned by magnetic fields. Models that best reproduce the observations have a substantial toroidal component to the magnetic field in the equatorial plane. Moreover, the toroidal magnetic field in the model that best fits AFGL 2591 extends a large fraction of the height of the model cavity, which is 10 5 au. We conclude that the massive YSOs in this study all show evidence of the presence of a substantial toroidal magnetic field.
A Dielectric-Filled Waveguide Antenna Element for 3D Imaging Radar in High Temperature and Excessive Dust Conditions

Three-dimensional information of the burden surface in high temperature and excessive dust industrial conditions has been previously hard to obtain. This paper presents a novel microstrip-fed dielectric-filled waveguide antenna element which is resistant to dust and high temperatures. A novel microstrip-to-dielectric-loaded waveguide transition was developed. A cylinder and cuboid composite structure was employed at the terminal of the antenna element, which improved the return loss performance and reduced the size. The proposed antenna element was easily integrated into a T-shape multiple-input multiple-output (MIMO) imaging radar system and tested in both the laboratory environment and real blast furnace environment. The measurement results show that the proposed antenna element works very well in industrial 3D imaging radar.
Ionic Mechanisms of Endogenous Bursting in CA3 Hippocampal Pyramidal Neurons: A Model Study

A critical property of some neurons is burst firing, which in the hippocampus plays a primary role in reliable transmission of electrical signals. However, bursting may also contribute to synchronization of electrical activity in networks of neurons, a hallmark of epilepsy. Understanding the ionic mechanisms of bursting in a single neuron, and how mutations associated with epilepsy modify these mechanisms, is an important building block for understanding the emergent network behaviors. We present a single-compartment model of a CA3 hippocampal pyramidal neuron based on recent experimental data. We then use the model to determine the roles of primary depolarizing currents in burst generation. The single compartment model incorporates accurate representations of sodium (Na+) channels (NaV1.1) and T-type calcium (Ca2+) channel subtypes (CaV3.1, CaV3.2, and CaV3.3). Our simulations predict the importance of Na+ and T-type Ca2+ channels in hippocampal pyramidal cell bursting and reveal the distinct contribution of each subtype to burst morphology. We also performed fast-slow analysis in a reduced comparable model, which shows that our model burst is generated as a result of the interaction of two slow variables, the T-type Ca2+ channel activation gate and the Ca2+-dependent potassium (K+) channel activation gate. The model reproduces a range of experimentally observed phenomena including afterdepolarizing potentials, spike widening at the end of the burst, and rebound. Finally, we use the model to simulate the effects of two epilepsy-linked mutations: R1648H in NaV1.1 and C456S in CaV3.2, both of which result in increased cellular excitability.
An Evaluation of Different DLP Alternatives for the Embedded Media Domain

The importance of media processing has produced a revolution in the design of embedded processors. In order to face the high computational and technological demands of near future media applications, new embedded processors are including features that were commonly restricted to the general purpose and the supercomputing domains. In this paper we have evaluated the performance of various DLP (Data Level Parallelism) oriented embedded architectures and analyzed quantitative data in order to determine the highlights and disadvantages of each approach. Additionally we have analyzed the differences between the explicit parallel versions of code (often based on the standard algorithms) and the high-tuned, non-vectorizable versions usually found in real multimedia programs. We will show that sub-word SIMD architectures (like MMX) are a very costeffective solution, and that, while long vector architectures provide few improvements at a very high cost, a smart combination between vector and SIMD-like architectures is the alternative that leverages best performance at a reasonable cost. We will also show that the memory latency tolerance, typical of vector architectures, is partially compensated by the worse spatial locality found when executing vector code.
Parton percolation in nuclear collisions

An essential prerequisite for quark-gluon plasma production in nuclear collisions is cross-talk between the partons from different nucleons in the colliding nuclei. The initial density of partons is determined by the parton distribution functions obtained from deep inelastic lepton-hadron scattering and by the nuclear geometry; it increases with increasing $A$ and/or $\sqrt s$. In the transverse collision plane, this results in clusters of overlapping partons, and at some critical density, the cluster size suddenly reaches the size of the system. The onset of large-scale cross-talk through color connection thus occurs as geometric critical behavior. Percolation theory specifies the details of this transition, which leads to the formation of a condensate of deconfined partons. Given sufficient time, this condensate could eventually thermalize. However, already the onset of parton condensation in the initial state, without subsequent thermalization, leads to a number of interesting observable consequences.
Linearization of F-I Curves by Adaptation

We show that negative feedback to highly nonlinear frequency-current (F-I) curves results in an effective linearization. (By highly nonlinear we mean that the slope at threshold is infinite or very steep.) We then apply this to a specific model for spiking neurons and show that the details of the adaptation mechanism do not affect the results. The crucial points are that the adaptation is slow compared to other processes and the unadapted F-I curve is highly nonlinear.
Patterns and transitions of query reformulation during web searching

Purpose – To investigate and identify the patterns of interaction between searchers and search engine during web searching. Design/methodology/approach – The authors examined 2,465,145 interactions from 534,507 users of Dogpile.com submitted on May 6, 2005, and compared query reformulation patterns. They investigated the type of query modifications and query modification transitions within sessions. Findings – The paper identifies three strong query reformulation transition patterns: between specialization and generalization; between video and audio, and between content change and system assistance. In addition, the findings show that web and images content were the most popular media collections. Originality/value – This research sheds light on the more complex aspects of web searching involving query modifications.
A Time-Predictable Memory Network-on-Chip

To derive safe bounds on worst-case execution times (WCETs), all components of a computer system need to be time-predictable: the processor pipeline, the caches, the memory controller, and memory arbitration on a multicore processor. This paper presents a solution for time-predictable memory arbitration and access for chip-multiprocessors. The memory network-on-chip is organized as a tree with time-division multiplexing (TDM) of accesses to the shared memory. The TDM based arbitration completely decouples processor cores and allows WCET analysis of the memory accesses on individual cores without considering the tasks on the other cores. Furthermore, we perform local, distributed arbitration according to the global TDM schedule. This solution avoids a central arbiter and scales to a large number of processors.
JTExpert at the Fourth Unit Testing Tool Competition

JTExpert is a software testing tool that automatically generates a whole test suite to satisfy the branch-coverage criterion. It takes as inputs a Java source code and its dependencies and automatically produces a test-case suite in JUnit format. In this paper, we summarize our results for the Unit Testing Tool Competition held at the fourth SBST Contest, where JTExpert received $931$ points and was ranked third. We also analyze our tool's performance.
Integrity Verification in Multi-Cloud Storage Using Cooperative Provable Data Possession

Storage outsourcing in cloud computing is a rising trend which prompts a number of interesting security issues. Provable data possession (PDP) is a method for ensuring the integrity of data in storage outsourcing. This research addresses the construction of efficient PDP which called as CooperativePDP (CPDP) mechanism for distributed cloud storage to support data migration and scalability of service, which considers the existence of multiple cloud service providers to collaboratively store and maintain the clients’ data. CooperativePDP (CPDP) mechanism is based on homomorphic verifiable response, hash index hierarchy for dynamic scalability, cryptographic encryption for security. Moreover, it proves the security of scheme based on multi-prover zeroknowledge proof system, which can satisfy knowledge soundness, completeness, and zero-knowledge properties. This research introduces lower computation and communication overheads in comparison with non-cooperative approaches. Keywords— Multiple Cloud, Cloud Storage Security, Cooperative Provable Data Possession, Homomorphic Variable Response, Zero knowledge
Nonparametric Bayesian Storyline Detection from Microtexts

News events and social media are composed of evolving storylines, which capture public attention for a limited period of time. Identifying storylines requires integrating temporal and linguistic information, and prior work takes a largely heuristic approach. We present a novel online non-parametric Bayesian framework for storyline detection, using the distance-dependent Chinese Restaurant Process (dd-CRP). To ensure efficient linear-time inference, we employ a fixed-lag Gibbs sampling procedure, which is novel for the dd-CRP. We evaluate on the TREC Twitter Timeline Generation (TTG), obtaining encouraging results: despite using a weak baseline retrieval model, the dd-CRP story clustering method is competitive with the best entries in the 2014 TTG task.
Earth System Dynamics The influence of dynamic vegetation on the present-day simulation and future projections of the South Asian summer monsoon in the HadGEM 2 family

Various studies have shown the importance of Earth System feedbacks in the climate system and the necessity of including these in models used for making climate change projections. The HadGEM2 family of Met Office Unified Model configurations combines model components which facilitate the representation of many different processes within the climate system, including atmosphere, ocean and sea ice, and Earth System components including the terrestrial and oceanic carbon cycle and tropospheric chemistry. We examine the climatology of the Asian summer monsoon in present-day simulations and in idealised climate change experiments. Members of the HadGEM2 family are used, with a common physical framework (one of which includes tropospheric chemistry and an interactive terrestrial and oceanic carbon cycle), to investigate whether such components affect the way in which the monsoon changes. We focus particularly on the role of interactive vegetation in the simulations from these model configurations. Using an atmosphere-only HadGEM2 configuration, we investigate how the changes in land cover which result from the interaction between the dynamic vegetation and the model systematic rainfall biases affect the Asian summer monsoon, both in the present-day and in future climate projections. We demonstrate that the response of the dynamic vegetation to biases in regional climate, such as lack of rainfall over tropical dustproducing regions, can affect both the present-day simulation and the response to climate change forcing scenarios.
YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae

The Yeast search for transcriptional regulators and consensus tracking (YEASTRACT) information system (www.yeastract.com) was developed to support the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in September 2007, this database contains over 30 990 regulatory associations between Transcription Factors (TFs) and target genes and includes 284 specific DNA binding sites for 108 characterized TFs. Computational tools are also provided to facilitate the exploitation of the gathered data when solving a number of biological questions, in particular the ones that involve the analysis of global gene expression results. In this new release, YEASTRACT includes DISCOVERER, a set of computational tools that can be used to identify complex motifs over-represented in the promoter regions of co-regulated genes. The motifs identified are then clustered in families, represented by a position weight matrix and are automatically compared with the known transcription factor binding sites described in YEASTRACT. Additionally, in this new release, it is possible to generate graphic depictions of transcriptional regulatory networks for documented or potential regulatory associations between TFs and target genes. The visual display of these networks of interactions is instrumental in functional studies. Tutorials are available on the system to exemplify the use of all the available tools.
Ontologies for Smart Homes and energy management: An implementation-driven survey

Semantic Web technologies have become a reference technology for information modelling and reasoning support in Smart Homes. This paper provides an extensive review of the ontologies developed in this scenario. Also, it discusses how they can be connected and expanded to create a complete framework that covers all the aspects of a Smart Home, ranging from device description to energy management, under a unifying holistic vision.
Effect of long-term oxygen therapy on survival in patients with chronic obstructive pulmonary disease with moderate hypoxaemia.

BACKGROUND: To date only two controlled studies have been published on the effects of domiciliary oxygen treatment on survival in patients with chronic obstructive pulmonary disease (COPD) with advanced respiratory failure. The survival in such patients despite oxygen treatment remains poor. The prescription of long term oxygen therapy (LTOT) in less severe disease remains controversial. The aim of this study was to evaluate the rationale for prescribing oxygen to patients with COPD with moderate hypoxaemia. METHODS: One hundred and thirty five patients with COPD, with PaO2 7.4-8.7 kPa (56-65 mmHg) and advanced airflow limitation (mean (SD) forced expiratory volume in one second (FEV1) 0.83 (0.28) 1), were randomly allocated to a control (n = 67) and LTOT (n = 68) group. The patients were followed every three months for at least three years or until death. RESULTS: The cumulative survival rate was 88% at one year, 77% at two years, and 66% at three years. No significant differences were found in survival rates between patients treated with LTOT and controls, nor did longer oxygen use (over 15 hours per day) improve survival. Younger age, better spirometric values, and higher body mass index predicted better survival. CONCLUSIONS: Domiciliary oxygen treatment does not prolong survival in patients with COPD with moderate hypoxaemia. Airway limitation seems to determine survival in this group of patients.
OPTIMAL MEASUREMENT SCHEDULING AND DESIGN WITH DYNAMIC PROGRAMMING

We shall present approaches to optimize the design of a measurement system and schedule dynamically a versatile measurement resource. The analysis is based on expressing the system management task as a dynamic programming problem in which the system state is partially observable. We shall review the well-known linear- quadratic-Gaussian case, and discuss and give examples solutions of discrete state systems. Furthermore, we discuss on approximate dynamic programming methods to solve such problems in practice.