Miracle-dz/UniFAR-FTUs huggingface dataset:
Hearing in a shoe-box: Binaural source position and wall absorption estimation using virtually supervised learning

This paper introduces a new framework for supervised sound source localization referred to as virtually-supervised learning. An acoustic shoe-box room simulator is used to generate a large number of binaural single-source audio scenes. These scenes are used to build a dataset of spatial binaural features annotated with acoustic properties such as the 3D source position and the walls' absorption coefficients. A probabilistic high- to low-dimensional regression framework is used to learn a mapping from these features to the acoustic properties. Results indicate that this mapping successfully estimates the azimuth and elevation of new sources, but also their range and even the walls' absorption coefficients solely based on binaural signals. Results also reveal that incorporating random-diffusion effects in the data significantly improves the estimation of all parameters.
Modeling and Evaluating of the Stewart Platform

This paper presents an algorithm for solving forward kinematics problem of the Stewart Platform and an application for modeling of the Stewart Platform's motions. The developed application is able to solve forward kinematics problem in given accuracy; to calculate curve of the tool positioned on the mobile platform; to calculate possible deviation of the tool from a nominal position if lengths of the legs can vary in given range; to detect crossing of the legs during motions of the mobile platform. The movements of the Stewart Platform can be specified though explicit laws of motions or trough spline-interpolation based on given nodes. The computational engine of the program is constructed on new effective methods and algorithms.
Elementary Characterization of Elds by Their Absolute Galois Group

We classify all elds whose elementary theory is encoded in their absolute Galois group and vice versa. It turns out that | apart from very few exotic elds, which probably don't exist | there are three types of such elds: real closed elds, certain p-adically closed elds and very special generalized power series elds over those p-adically closed elds. The classiication is based on a Galois characterization of henselian elds, an analysis of the absolute Galois group of henselian elds of mixed characteristic and an account on rst-order deenablity of valuations in the language of elds.
Learning Faults Detection by AIS Techniques in CSCL Environments

By the increase of e-learning platforms, huge data sets are made from different kinds of the collected traces. These traces differ from one learner to another according to their characteristics (learning styles, preferences, performed actions, etc.). Learners' traces are very heterogeneous and voluminous, so their treatments and exploitations are difficult, that make hard the tutors' tasks. This paper introduces one of the bio-inspired computing techniques to improve the learning quality. In fact, Artificial Immune System (AIS) is a technique which was adapted for designing an assistant system that detects the wrong scenarios made by learners. Furthermore, this assistant system assists the learners in their activities. The main aim is to present the basic concepts of a new approach that aims at providing learners with relevant traces to improve their learning in order to minimize the tutor's tasks. A novel algorithm is proposed to design the assistant system based on the two mechanisms of the AIS techniques (negative and clonal selection). The proposed algorithm was applied on a collaborative learning system called LETline 2.0 (http://www.labstic.com/letline/). An experiment was conducted in an Algerian University. The obtained results from this experiment were good and very efficient. The proposed approach enhances the cognitive and behavioral profiles of learners. In fact, the results show that the cognitive profiles of most students were improved. Also, it minimizes the tutor's tasks.
Information Cost Tradeoffs for Augmented Index and Streaming Language Recognition

This paper makes three main contributions to the theory of communication complexity and stream computation. First, we present new bounds on the information complexity of AUGMENTED-INDEX. In contrast to analogous results for INDEX by Jain, Radhakrishnan and Sen [J. ACM, 2009], we have to overcome the significant technical challenge that protocols for AUGMENTED-INDEX may violate the ``rectangle property'' due to the inherent input sharing. Second, we use these bounds to resolve an open problem of Magniez, Mathieu and Nayak [STOC, 2010] on the multi-pass complexity of recognizing Dyck languages. This results in a natural separation between the standard multi-pass model and the multi-pass model that permits reverse passes. Third, we present the first passive memory checkers that verify the interaction transcripts of priority queues, stacks, and double-ended queues. We obtain tight upper and lower bounds for these problems, thereby addressing an important sub-class of the memory checking framework of Blum et al. [Algorithmica, 1994].
Maximizing rewards for real-time applications with energy constraints

New technologies have brought about a proliferation of embedded systems, which vary from control systems to sensor networks to personal digital assistants. Many of the portable embedded devices run several applications, which typically have three constraints that need to be addressed: energy, deadline, and reward. However, many of these portable devices do not have powerful enough CPUs and batteries to run all applications within their deadlines. An optimal scheme would allow the device to run the most applications, each using the most amount of CPU cycles possible, without depleting the energy source while still meeting all deadlines. In this paper we propose a solution to this problem; to our knowledge, this is the first solution that combines the three constraints mentioned above. We devise two algorithms, an optimal algorithm for homogeneous applications (with respect to power consumption) and a heuristic iterative algorithm that can also accommodate heterogeneous applications (i.e., those with different power consumption functions). We show by simulation that our iterative algorithm is fast and within 1% of the optimal.
Real models and virtual simulators in otolaryngology: review of literature

Summary Introduction and Aims Real models and virtual simulators have been used with positive results in several fields of medicine. These new devices can enhance teaching, learning and also training in Otolaryngology, reducing associated costs and potentially reducing medical errors. We reviewed the literature on the real and virtual models and simulators used for education and training in our medical specialty, discussing some of them and the results achieved with such instruments. Moreover, we also discuss the future perspectives in education and training in our medical specialty. Methods Literature review. Conclusions Otolaryngology, a clinical and surgical field of medicine, should be at the forefront of this technological revolution. In our specialty, real models and virtual simulators and environments have a great teaching and learning potential. With equipment costs dropping, thanks to technological development, these tools tend to become increasingly more popular.
Pharmacological considerations on the use of antiretrovirals in pregnancy.

PURPOSE OF REVIEW Treatment with combination antiretroviral therapy during pregnancy reduces the chance of mother to child transmission of HIV. Physiological changes during pregnancy can lead to lower exposure to antiretrovirals, possibly resulting in virological failure. For most antiretrovirals, data on exposure during pregnancy and transplacental passage are limited. This review summarizes the most recent information on pharmacokinetics (including transplacental passage), efficacy, as well as the safety of antiretrovirals during pregnancy. RECENT FINDINGS Intensive-sampling pharmacokinetic studies as well as observational studies using sparse sampling were performed to explore the exposure to antiretrovirals during pregnancy. Transplacental passage, efficacy (viral load at delivery and infection status of the newborn) and safety information were evaluated for several antiretrovirals. SUMMARY For most nucleoside/nucleotide reverse transcriptase inhibitors and protease inhibitors, recent research shows a decreased exposure during pregnancy. However, the advantage of a general dose increase during pregnancy still remains unclear. For newer compounds and efavirenz, limited or no data on pharmacokinetics during pregnancy or transplacentally are available, while the mechanisms of transplacental passage also remain unknown. For safety reasons, it will be important to monitor pregnancy outcomes in resource-limited settings during the implementation of the WHO guidelines (including the use of efavirenz during pregnancy).
Giant optical transmission of sub-wavelength apertures: physics and applications

The transmission of light through an aperture in a metal film is extremely small when the aperture diameter is much smaller than the optical wavelength. But when the metal surface surrounding the subwavelength hole is corrugated, the incident light can couple to surface plasmons (SP), excitation modes on the metal surface. A resonant interaction leads to an enhanced transmission at wavelengths determined by the corrugation pitch. We discuss applications of the SP enhanced transmission in near-field scanning optical microscopy and in high-density optical data storage.
Kraken: Leveraging Live Traffic Tests to Identify and Resolve Resource Utilization Bottlenecks in Large Scale Web Services

Modern web services such as Facebook are made up of hundreds of systems running in geographically-distributed data centers. Each system needs to be allocated capacity, configured, and tuned to use data center resources efficiently. Keeping a model of capacity allocation current is challenging given that user behavior and software components evolve constantly. Three insights motivate our work: (1) the live user traffic accessing a web service provides the most current target workload possible, (2) we can empirically test the system to identify its scalability limits, and (3) the user impact and operational overhead of empirical testing can be largely eliminated by building automation which adjusts live traffic based on feedback. We build on these insights in Kraken, a new system that runs load tests by continually shifting live user traffic to one or more data centers. Kraken enables empirical testing by monitoring user experience (e.g., latency) and system health (e.g., error rate) in a feedback loop between traffic shifts. We analyze the behavior of individual systems and groups of systems to identify resource utilization bottlenecks such as capacity, load balancing, software regressions, performance tuning, and so on, which can be iteratively fixed and verified in subsequent load tests. Kraken, which manages the traffic generated by 1.7 billion users, has been in production at Facebook for three years and has allowed us to improve our hardware utilization by over 20%.
Surveillance Data Highlights Feed Form, Biosecurity, and Disease Control as Significant Factors Associated with Salmonella Infection on Farrow-to-Finish Pig Farms

Among the zoonotic pathogens affecting pigs, Salmonella stands out due to the high number of human cases linked to pork consumption. In the last two decades many countries have put considerable effort into the control of the infection by surveillance and control strategies on farm. Despite this effort, many herds still have a high Salmonella prevalence and they require guidance to address this problem. The present study, using the serological surveillance data of finishing pigs from the Irish National pig Salmonella Control Programme, aimed to highlight factors associated with increased risk or that might mitigate Salmonella occurrence on farm. A questionnaire with 33 questions regarding herd characteristics, management, feeding, biosecurity, and health was completed for 61 individual herds. After the multivariate analysis by linear regression, nine variables were retained in the final model and linked to herd seroprevalence. Home produced-feed linked to the use of meal showed an eight points reduction in Salmonella prevalence compared to purchased feed (p = 0.042). Different biosecurity measures were associated to lower seroprevalence. Changing of footwear from outside to inside the farm decreased seroprevalence nearly 20 units (p = 0.014) and policies not permitting access to the farmyard to feed trucks (p = 0.048) or avoiding the presence of cats on the farm (p = 0.05) were estimated in 10 units less of seroprevalence. In contrast, the lack of perimeter fence increased the chance to have higher seroprevalence in five units (p = 0.05). Finally, intestinal diseases such as swine dysentery (p = 0.044) and E. coli diarrhea (p = 0.1) were estimated to increase Salmonella prevalence in ~20 and 10 units, respectively, demonstrating the importance of controlling other enteric pathogens in an on-farm Salmonella control programme. These results show the usefulness of surveillance data to improve on-farm control and confirm that Salmonella infection in pigs is multi-factorial and the approach to its control should be multifaceted.
A unicast-based approach for streaming multicast

Network layer multicast is know as the most efficient way to support multicast sessions. However, for security, QoS and other considerations, most of the real-time application protocols can be better served by upper layer (transport or application) multicast. We propose a scheme called M-RTP for multicast RTP sessions. The idea behind this scheme is to set up the multicast RTP session over a set of unicast RTP sessions, established between the various participants (source and destinations) of the multicast session. We then address the issue of finding a set of paths with maximum bottleneck for an M-RTP session. We show that this problem is NP-complete, and propose several heuristics to solve it.
The Ecology of Community Networking

"Last mile" is a supply-side driven term used by telecommunications providers to refer to the local loop; the last to be economically viable. In globally networked societies, localities have opportunities to grow new economies. Local must be considered the "First Mile". "First Mile" is based on demand-side understandings. It describes a local orientation for telecommunications infrastructure and services, focused on the difference to be made in the quality of peoples’ lives. "First Mile" is a realization of the emerging ‘hyperarchical’ nature of networked economies, local-global relationships, innovation and social change; with intention that the Information Revolution be a "people’s revolution".
Qinghai-Tibet railway emergency management problem analysis and countermeasures

The importance of Qinghai-Tibet railway emergency management is pointed out and problems in Qinghai-Tibet railway emergency management are analyzed. Then suggestions and countermeasures in respect of the Qinghai-Tibet railway risk assessment, emergency preplan, and emergency resource allocation are put forward to solve existing problems. These countermeasures should play an active role in improving Qinghai-Tibet railway emergency management capability and efficiency to ensure operational safety.
The deformation of foamed elastic materials

A theoretical treatment is given which predicts the behavior of a foamed elastic material on the basis of a model consisting of a network of thin threads. Two cases are considered: (1) small strains, and (2) finite compressions, when the major part of the deformation of the threads is attributed to buckling. The behavior is given in terms of Young's modulus of the matrix and the density of the foam. Measurements of the load-deformation relations for small tensile strains and finite compressions are described for natural rubber foams prepared from latex. A wide range of density is covered (0.09–0.57), giving a variation of compression hardness of about 100:1. Satisfactory agreement with theory is found for both the cases considered, indicating that the basic concepts of the structure and mode of deformation are correct.
Seismic Detailing and Behavior of Coupling Beams with High-Peformance Fiber- Reinforced Concrete

This paper provides a summary of a series of tests that were performed on strain hardening High-Performance Fiber-Reinforced Concrete (HPFRC) coupling beams with span length-to-depth ratios (ln/h) of 1.75 and 2.75. These tests show that incorporating HPFRC simplifies the detailing required to ensure a stable response of coupling beams that are subjected to earthquake induced displacement reversals. Results from five tests of precast coupling beams, three with ln/h = 1.75 and two with ln/h = 2.75, are reported in the paper. Strategies for embedding the precast HPFRC coupling beams into the structural walls without interfering with boundary element reinforcement were explored. Test results confirm that HPFRC can reliably confine diagonal reinforcement and ensure stable hysteresis behavior. HPFRC was also found to significantly increase shear strength, thereby forcing a flexurally dominated failure mode with modest stiffness degradation and excellent energy dissipation. A revised coupling beam design philosophy is outlined in order to ensure ductile flexural behavior.
Harder than diamond: Dreams and reality

Abstract Analysis of correlations between various physical properties of solids provides a formulation of simple criteria applicable to the search for new superhard materials. The prospects for the synthesis of new substances with the key elastic moduli, whose values approach or even exceed those of diamond are also discussed. We introduce the concept of ideal hardness and strength, which relates the elastic properties of materials to the corresponding mechanical characteristics, the concepts that are less unambiguously determined and that depend on the conditions of measurements. The control of material nanostructure makes it possible to approach the ideal hardness. The formulation of trends interrelating physical properties is expected to allow an essential guidance in the synthesis of new classes of superhard materials.
The application of flux balance analysis in systems biology

An increasing number of genome‐scale reconstructions of intracellular biochemical networks are being generated. Coupled with these stoichiometric models, several systems‐based approaches for probing these reconstructions in silico have been developed. One such approach, called flux balance analysis (FBA), has been effective at predicting systemic phenotypes in the form of fluxes through a reaction network. FBA employs a linear programming (LP) strategy to generate a flux distribution that is optimized toward a particular ‘objective,’ subject to a set of underlying physicochemical and thermodynamic constraints. Although classical FBA assumes steady‐state conditions, several extensions have been proposed in recent years to constrain the allowable flux distributions and enable characterization of dynamic profiles even with minimal kinetic information. Furthermore, FBA coupled with techniques for measuring fluxes in vivo has facilitated integration of computational and experimental approaches, and is allowing pursuit of rational hypothesis‐driven research. Ultimately, as we will describe in this review, studying intracellular reaction fluxes allows us to understand network structure and function and has broad applications ranging from metabolic engineering to drug discovery. Copyright © 2009 John Wiley & Sons, Inc.
Regge trajectories for mesons in the holographic dual of large-N(c) QCD

We discuss Regge trajectories of dynamical mesons in large-Nc QCD, using the supergravity background describing Nc D4-branes compactified on a thermal circle. The flavor degrees of freedom arise from the addition of Nf << Nc D6 probe branes. Our work provides a string theoretical derivation, via the gauge/string correspondence, of a phenomenological model describing the meson as rotating point-like massive particles connected by a flux string. The massive endpoints induce nonlinearities for the Regge trajectory. For light quarks the Regge trajectories of mesons are essentially linear. For massive quarks our trajectories qualitatively capture the nonlinearity detected in lattice calculations.
Who gets the care in Medicare?

here is considerable evidence for disparities in health and risk factors for ill health of Australians on the basis of socioeconomic status.1 While the health of the population is improving overall (eg, increasing life expectancy, reduced cardiovascular mortality), these disparities are remaining or even widening.2 As we move from higher to lower socioeconomic status, many markers of health and disability become progressively worse — what has been described as the socioeconomic gradient.3 The socioeconomic gradient in health is influenced by a broad range of social determinants. Use of health care is only one factor that contributes to health. However, timely use of health care does contribute to health and reduce disability — something that is evident in countries where access is extremely poor.4 This is of course strongly influenced by the affordability of health care to patients, along with other factors such as workforce availability. The latter is a major factor responsible for reduced Medicare spending in rural and remote areas. Universal health insurance was introduced in Australia in 1975 (initially called Medibank and later reintroduced as Medicare), financed through the tax system.5 This was designed to make health insurance fairer and more affordable for all Australians, avoiding patients having to face catastrophic health expenditure. There is increasing Who gets the care in Medicare?
Elastic network monitoring with virtual probes

The next generation monitoring solutions should evolve as fast as the applications they will support both in terms of functionality (e.g. new protocols, monitoring function, etc.) as well as in terms of scale and performance. We believe the field of network monitoring is yet to experience the same revolutionary transformation as software-defined networking (SDN) and network function visualization (NFV) brought to the telecom world. To this end we present a flexible network monitoring application we use to demonstrate the potential of next generation network monitoring with advanced probe functionality and virtualization. Our demonstration shows a new OVS-based (Open vSwitch) vProbe capable of adding and processing monitoring metadata in IETF's recently proposed network service header (NSH) for service chaining [1], [2]. The monitoring metadata in this work is used for troubleshooting performance issues (i.e. excessive latency) along service function paths (SFPs). Benefits of our approach are the flexibility it offers to create new monitoring solutions as well as the virtualization of monitoring resources in order to benefit from the same economies of scale and elasticity features of NFV. This demonstration is built as part of our proposed monitoring framework presented in [3] which consists of a monitoring platform which, on the northbound, offers a full control as well as a more limiting intent based interface. It can spin new vProbes when and where needed. The data plane used in this demonstration consists of OpenFlow switches (OVS) extended with the NSH header [4]. This work can be described as a troubleshooting use case customized for service chaining. We demonstrate a video traffic performance degradation scenario and pin down where the issue is for a given flow on a service chain.