Miracle-dz/UniFAR-FTUs huggingface dataset:
A Framework for Distributing Scalable Content over Peer-to-Peer Networks

Peer-to-Peer systems are nowadays a very popular solution for multimedia distribution, as they provide significant cost benefits compared with traditional server-client distribution. Additionally, the distribution of scalable content enables the consumption of the content in a quality suited for the available bandwidth and the capabilities of the end-user devices. Thus, the distribution of scalable content over Peerto- Peer network is a very actual research topic. This paper presents a framework for the distribution of scalable content in a fully distributed Peer-to-Peer network. The architectural description includes how the scalable layers of the content are mapped to the pieces distributed in the Peer-to-Peer system and detailed descriptions of the producer- and consumer-site architecture of the system. Additionally, an evaluation of the system’s performance in different scenarios is provided. The test series in the evaluation section assess the performance of our layered piece-picking core and provide a comparison of the performance of our system’s multi layer and single layer implementations. The presented system is to our knowledge the first open-source Peer-to-Peer network with full Scalable Video Coding support.
Enhancement of growth performance in pre-weaning suckling Boer kids supplemented with creep feed containing alfalfa

Aim: This study examined the effects of creep feed (CF) supplementation (with or without Alfalfa) on the pre-weaning growth performance of nursing goat kids. Materials and Methods: A total of forty eight (48), 7 days old, single born kids (live weight 4.4±0.09 kg) were divided into three treatment groups, each containing eight males and eight females. All three groups had access to their dams’ milk (DM). The kids from the first treatment group had free access to CF containing alfalfa (CFA) while those from the second group had free access to CF without alfalfa. The third treatment group (control) had access to their DM only. All three groups were kept isolated from the dams from 800 to 1200 h and from 1400 to 1800 h while having access to CF. Results: Total weight gain and average daily gain of kids from CFA group (11.2±0.36 kg, 145.2±4.64 g) was significantly higher (p<0.05) than kids from CF (7.9±0.49 kg, 102.9±6.43 g) and DM (5.5±0.43 kg, 71.1±5.56 g) groups. The weaning weight of kids from CFA group (15.6±0.39 kg) was significantly higher (p<0.05) than those from CF (12.1±0.56 kg) and DM (9.9±0.59 kg) groups. Conclusion: This result shows that supplementation of CF combined with alfalfa from birth to weaning enhances growth performance of cross-bred Boer goat kids.
AN EFFICIENT REDUCED-ORDER METHOD FOR HESSIAN MATRIX CONSTRUCTION

When nonlinear behavior must be considered in sensitivity analysis studies, one needs to approximate higher order derivatives of the response of interest with respect to all input data. This paper presents an application of a general reduced order method to constructing higher order derivatives of response of interest with respect to all input data. In particular, we apply the method to constructing all second order derivatives which are often compactly combined in a matrix denoted by the Hessian matrix. Compared to the state-of-the-art methods for Hessian constructions including notably rank-update formulas, the presented Subspace Reduced Order Method requires only r evaluations of the first order derivatives as opposed to n, where r is the rank of the Hessian matrix, and n is the number of input data. Moreover, the new method is less sensitive to numerical errors as it does not rely on rank-update formulas. Finally, in contract to a class of rank-update methods which requires serial evaluation of derivatives, our method evaluates the r derivatives in parallel, thereby rendering it more suitable for coarse-grain parallelization. The paper derives the new methods and applies it to a criticality problem employing the SCALE 6.1 (TSUNAMI-2D) code system.
Contamination of Cluster Radio Sources in the Measurement of the Thermal Sunyaev-Zel’dovich Angular Power Spectrum

We present a quantitative estimate of the contamination of cluster radio halos and galaxies in the measurement of the angular power spectrum of the thermal Sunyaev-Zel'dovich (SZ) effect. To achieve the goal, we use a purely analytic approach to both radio sources and dark matter of clusters by incorporating empirical models and observational facts together with some theoretical considerations. It is shown that the correction of cluster radio halos and galaxies to the measurement of the thermal SZ angular power spectrum is no more than 20% at l > 2000 for observing frequencies ν > 30 GHz. This eliminates the concern that the SZ measurement may be seriously contaminated by the existence of cluster radio sources.
USTC System for Blizzard Challenge 2006 an Improved HMM-based Speech Synthesis Method

This paper introduces the USTC speech synthesis system for Blizzard Challenge 2006. The HMM-based parametric synthesis approach was adopted for its convenience and effectiveness in building a new voice, especially for the nonnative developers. Some useful techniques were also integrated into our system, such as minimum generation error (MGE) training, phone duration modeling and linear spectral pair (LSP) based formant enhancement. The evaluation results show that the proposed system is able to synthesize speech with high naturalness and intelligibility by using either full database or only ARCTIC subset.
Scalable approaches for path computation

Optimal and fast approaches for path computation are of paramount importance especially for the path computation elements (PCE) of generalized multi-protocol label switching (GMPLS) networks. To overcome the computational complexity, optimality must be traded for the execution time, enabling scalable computation. This paper considers the typical routing problems addressed by PCE and compares different optimization approaches based on integer linear programming (ILP) formulation and its relaxation, with the objective of assessing optimality and scalability of the approaches.
An Novel Energy-Efficient MAC Protocol Based on Collision Avoidance for Wireless Sensor Networks

Wireless sensor networks have been widely used in many important areas. Medium access control (MAC) protocols have a significant effect on the function and performance of sensor network. This paper summarizes the present design paradigms of the MAC protocol in wireless sensor networks, then based on ring topology based on virtual grid and token ring ideas, an novel energy-efficient MAC protocol based on collision avoidance (EECA-MAC)for wireless sensor networks is proposed. Comparing with other algorithms, EECA-MAC has two obvious features: Firstly, it improves energy utility by changing the activity of wireless communication module of sensor nodes, energy model and state transition of sensor nodes. Secondly, EECA-MAC adopts ring topology based on virtual grid intracluster and time slot ideas to avoid collision intra-cluster. Simulation results show that, compared with TDMA and SMAC, EECA-MAC significantly reduce in energy consumption and prolong the network lifetime.
Optimizing Software Quality Assurance

A major concern for managers of software projects are the triple constraints of cost, schedule and quality due to the difficulties to quantify accurately the trade-offs between them. Project managers working for accredited companies with a high maturity will typically use software cost estimation models like COCOMO II and predict software quality by the estimated number of defects the product is likely to contain at release. However, most of these models are used separately and the interplay between cost/effort estimation, project scheduling and the resultant quality of the software product is not well understood. In this paper, we propose a regression-based model that allows project managers to estimate the trade-off between the quality, cost and development time of a software product, based on previously collected data.
Regularized EM Algorithms: A Unified Framework and Provable Statistical Guarantees

Latent variable models are a fundamental modeling tool in machine learning applications, but they present significant computational and analytical challenges. The popular EM algorithm and its variants, is a much used algorithmic tool; yet our rigorous understanding of its performance is highly incomplete. Recently, work in Balakrishnan et al. (2014) has demonstrated that for an important class of problems, EM exhibits linear local convergence. In the high-dimensional setting, however, the M-step may not be well defined. We address precisely this setting through a unified treatment using regularization. While regularization for high-dimensional problems is by now well understood, the iterative EM algorithm requires a careful balancing of making progress towards the solution while identifying the right structure (e.g., sparsity or low-rank). In particular, regularizing the M-step using the state-of-the-art high-dimensional prescriptions (e.g., Wainwright (2014)) is not guaranteed to provide this balance. Our algorithm and analysis are linked in a way that reveals the balance between optimization and statistical errors. We specialize our general framework to sparse gaussian mixture models, high-dimensional mixed regression, and regression with missing variables, obtaining statistical guarantees for each of these examples.
On the extraction of threshold voltage, effective channel length and series resistance of MOSFETs

The first part of this article presents the modeling of the long-channel bulk MOSFET as a particular case of the SOI MOSFET. The second part reviews compares and scrutinizes various methods to extract the threshold voltage, the effective channel and the individual values of drain and source resistances. These are important device parameters for modeling and circuit simulation.
AUTONOMOUS NAVIGATION FIELD RESULTS OF A PLANETARY ANALOG ROBOT IN ANTARCTICA

The Robotic Antarctic Meteorite Search at Carnegie Mellon is developing robotic technologies to allow for autonomous search and classification of meteorites in Antarctica. In November 1998, the robot Nomad was deployed in the Patriot Hills region of Antarctica to perform several demonstrations and experiments of these technologies in a polar environment. Nomad drove 10.3km autonomously in Antarctica under a variety of weather and terrain conditions. This paper presents the results of this traverse, the ability of stereo vision and laser scanner to perceive polar terrain and the autonomous navigation system used.
Colour constancy in diurnal and nocturnal hawkmoths

SUMMARY Diurnal and nocturnal hawkmoths have been shown to use colour vision for flower discrimination. Here, we present evidence that the nocturnal hawkmoth Deilephila elpenor and the diurnal hawkmoth Macroglossum stellatarum also have colour constancy. Colour constancy was shown in D. elpenor in two multiple-choice experiments with five different bluish colour patches under white and blue illumination and with five yellowish colour patches under white, blue and yellow illumination. The mechanism underlying colour constancy in both species was investigated in two dual-choice experiments. The choice behaviour is consistent with the use of the von Kries coefficient law. Although the moths have colour constancy, they react to the colour of the illumination. They make fewer choices when tested under the changed illumination, where they never receive a reward, compared with the training illumination. Even if colour constancy can be explained by a von Kries adaptation mechanism, the fact that the animals discriminate between different illuminations indicates that some additional process must be involved.
Representing Measurement Results

To gain insight into the relationship between physical theories and com- putation, we examine the link between measurement devices and computers in the framework of TTE. Starting from a formal definition of a measurement procedure, different approaches to associate a representation with a measurement procedure are studied, and an equivalence class of representations suitable for representing the results of a measurement is defined for each measurement procedure.
Compressive Light Field Displays

Light fields are the multiview extension of stereo image pairs: a collection of images showing a 3D scene from slightly different perspectives. Depicting high-resolution light fields usually requires an excessively large display bandwidth; compressive light field displays are enabled by the codesign of optical elements and computational-processing algorithms. Rather than pursuing a direct "optical" solution (for example, adding one more pixel to support the emission of one additional light ray), compressive displays aim to create flexible optical systems that can synthesize a compressed target light field. In effect, each pixel emits a superposition of light rays. Through compression and tailored optical designs, fewer display pixels are necessary to emit a given light field than a direct optical solution would require.
Effects of Ankle Arthrodesis on Biomechanical Performance of the Entire Foot

Background/Methodology Ankle arthrodesis is one popular surgical treatment for ankle arthritis, chronic instability, and degenerative deformity. However, complications such as foot pain, joint arthritis, and bone fracture may cause patients to suffer other problems. Understanding the internal biomechanics of the foot is critical for assessing the effectiveness of ankle arthrodesis and provides a baseline for the surgical plan. This study aimed to understand the biomechanical effects of ankle arthrodesis on the entire foot and ankle using finite element analyses. A three-dimensional finite element model of the foot and ankle, involving 28 bones, 103 ligaments, the plantar fascia, major muscle groups, and encapsulated soft tissue, was developed and validated. The biomechanical performances of a normal foot and a foot with ankle arthrodesis were compared at three gait instants, first-peak, mid-stance, and second-peak. Principal Findings/Conclusions Changes in plantar pressure distribution, joint contact pressure and forces, von Mises stress on bone and foot deformation were predicted. Compared with those in the normal foot, the peak plantar pressure was increased and the center of pressure moved anteriorly in the foot with ankle arthrodesis. The talonavicular joint and joints of the first to third rays in the hind- and mid-foot bore the majority of the loading and sustained substantially increased loading after ankle arthrodesis. An average contact pressure of 2.14 MPa was predicted at the talonavicular joint after surgery and the maximum variation was shown to be 80% in joints of the first ray. The contact force and pressure of the subtalar joint decreased after surgery, indicating that arthritis at this joint was not necessarily a consequence of ankle arthrodesis but rather a progression of pre-existing degenerative changes. Von Mises stress in the second and third metatarsal bones at the second-peak instant increased to 52 MPa and 34 MPa, respectively, after surgery. These variations can provide indications for outcome assessment of ankle arthrodesis surgery.
forqs: forward-in-time simulation of recombination, quantitative traits and selection

Summary: forqs is a forward-in-time simulation of recombination, quantitative traits and selection. It was designed to investigate haplotype patterns resulting from scenarios where substantial evolutionary change has taken place in a small number of generations due to recombination and/or selection on polygenic quantitative traits. Availability and implementation: forqs is implemented as a command-line C++ program. Source code and binary executables for Linux, OSX and Windows are freely available under a permissive BSD license: https://bitbucket.org/dkessner/forqs. Contact: jnovembre@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Veillonella montpellierensis Endocarditis

Veillonella spp. rarely cause infections in humans. We report a case of Veillonella endocarditis documented by isolating a slow-growing, gram-negative microbe in blood cultures. This microbe was identified as the newly recognized species Veillonella montpellierensis (100% homology) by 16S RNA gene sequence analysis.
Animal Studies Repository Animal Studies Repository Volunteer Studies in Pain Research — Opportunities and Challenges to Replace Animal Experiments: the Report and Recommendations of a Focus on Alternatives Workshop Recommended Citation Volunteer Studies in Pain Research — Opportunities and Challeng

Despite considerable research, effective and safe treatments for human pain disorders remain elusive. Understanding the biology of different human pain conditions and researching effective treatments continue to be dominated by animal models, some of which are of limited value. British and European legislation demands that non-animal approaches should be considered before embarking on research using experimental animals. Recent scientific and technical developments, particularly in human neuroimaging, offer the potential to replace some animal procedures in the study of human pain. A group of pain research experts from academia and industry met with the aim of exploring creatively the tools, strategies and challenges of replacing some animal experiments in pain research with ethically conducted studies of human patients and healthy volunteers, in combination with in vitro methods. This report considers how a range of neuroimaging techniques including functional magnetic resonance imaging, magnetoencephalography and positron emission tomography, singly and combined, can address human pain conditions. In addition, microdialysis in human subjects; genome-wide association research, twin studies and other epidemiological approaches; and in vitro cell and tissue research, are examined for their replacement potential in combination with neuroimaging. Recommendations highlight further opportunities to advance the replacement of animal studies with robust methods of relevance to understanding and treating human pain.
An Approach for Data Storage Security in Cloud Computing

Cloud computing is now days emerging field because of its performance, high availability, low cost. In the cloud many services are provided to the client by cloud. Data store is main future that cloud service provides to the companies to store huge amount of storage capacity. But still many companies are not ready to implement cloud computing technology due to lack of proper security control policy and weakness in protection which lead to many challenge in cloud computing. The main objectives of this paper are, 1) To prevent Data access from unauthorized access, it propose a distributed scheme to provide security of the data in cloud . This could be achieved by using homomorphism token with distributed verification of erasure-coded data. 2) Proposed scheme perfectly stores the data and identifies the any tamper at the cloud server.3) And also performs some of the tasks like data updating, deleting, appending. This paper also provides a process to avoid Collusion attacks of server modification by unauthorized users. The proposed techniques is been implementation and results are shown at the below. Keyword: cloud computing, Authentication, homomorphism token, Collusion attacks.
Human mesenchymal stem cells seeded on extracellular matrix‐scaffold: Viability and osteogenic potential

The development and the optimization of novel culture systems of mesenchymal osteoprogenitors are some of the most important challenges in the field of bone tissue engineering (TE). A new combination between cells and extracellular matrix (ECM)‐scaffold, containing ECM has here been analyzed. As source for osteoprogenitors, mesenchymal stem cells obtained from human umbilical cord Wharton's Jelly (hWJMSCs), were used. As ECM‐scaffold, a powder form of isolated and purified porcine urinary bladder matrix (pUBM), was employed. The goals of the current work were: (1) the characterization of the in vitro hWJMSCs behavior, in terms of viability, proliferation, and adhesion to ECM‐scaffold; (2) the effectiveness of ECM‐scaffold to induce/modulate the osteoblastic differentiation; and (3) the proposal for a possible application of cells/ECM‐scaffold construct to the field of cell/TE. In this respect, the properties of the pUBM‐scaffold in promoting and guiding the in vitro adhesion, proliferation, and three‐dimensional colonization of hWJMSCs, without altering viability and morphological characteristics of the cells, are here described. Finally, we have also demonstrated that pUBM‐scaffolds positively affect the expression of typical osteoblastic markers in hWJMSCs. J. Cell. Physiol. 227: 857–866, 2012. © 2011 Wiley Periodicals, Inc.
Pride, shame, and guilt: socio-emotional aspects of the encounter between the Bedouin and Fellahi dialects

ABSTRACT This article examines the encounter between two Arabic dialects, one in use in Arab communities in central Israel (originally a community of farmers – Fellahin) and one in use among Bedouins who migrated to the area from the southern Negev area. We relied on semi-structured in-depth interviews with 18 participants representing four Bedouin migrant generations. The findings indicated that Bedouin migrants perceive the Bedouin dialect as a different language, which they have to ‘translate’ to the local Fellahi population. A clear inter-generational distinction was found in the willingness to switch from the Bedouin to the Fellahi dialect or to mix the two. Migrant parents have more negative feelings about mixing the Bedouin and Fellahi dialects than children who did not experience migration. Linguistically, the first generation exhibited differentiation, hybridity, and a tendency to avoid integration into the local population in an attempt to preserve the Bedouin dialect. This pattern dwindled in subsequent generations – the second tended to adopt an ‘intermediate’ dialect, whereas the third tends to mix the two and use each one according to the home or public spheres. Further conclusions and implications are also considered.
NextMe: Localization Using Cellular Traces in Internet of Things

The Internet of Things (IoT) opens up tremendous opportunities to location-based industrial applications that leverage both Internet-resident resources and phones' processing power and sensors to provide location information. Location-based service is one of the vital applications in commercial, economic, and public domains. In this paper, we propose a novel localization scheme called NextMe, which is based on cellular phone traces. We find that the mobile call patterns are strongly correlated with the co-locate patterns. We extract such correlation as social interplay from cellular calls, and use it for location prediction from temporal and spatial perspectives. NextMe consists of data preprocessing, call pattern recognition, and a hybrid predictor. To design the call pattern recognition module, we introduce the notions of critical calls and corresponding patterns. In addition, NextMe does not require that the cell tower addresses should be bounded with concrete coordinates, e.g., global positioning system (GPS) coordinates. We validate NextMe across MIT Reality Mining Dataset, involving 500 000 h of continuous behavior information and 112 508 cellular calls. Experimental results show that NextMe achieves fine-grained prediction accuracy at cell tower level in the forthcoming 1-6 h with 12% accuracy enhancement averagely from cellular calls.