Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Resistance to Experimental Infection with Mycobacterium bovis in Red Deer (Cervus elaphus)

ABSTRACT Tuberculosis (Tb) caused by Mycobacterium bovis is a worldwide threat to livestock and humans. One control strategy is to breed livestock that are more resistant to Mycobacterium bovis. In a 3-year heritability study 6 farmed red deer stags were selected from 39 on the basis of their differing responses to experimental challenge via the tonsillar sac with approximately 500 CFU of M. bovis. Two stags remained uninfected, two were moderately affected, and two developed serious spreading Tb. Seventy offspring, bred from these six stags by artificial insemination using stored semen, were similarly challenged withM. bovis. The offspring showed patterns of response toM. bovis challenge similar to those of their sires, providing evidence for a strong genetic basis to resistance to Tb, with an estimated heritability of 0.48 (standard error, 0.096; P< 0.01). This is the first time the heritability of Tb resistance in domestic livestock has been measured. The breeding of selection lines of resistant and susceptible deer will provide an ideal model to study the mechanisms of Tb resistance in a ruminant and could provide an additional strategy for reducing the number and severity of outbreaks of Tb in farmed deer herds. Laboratory studies to identify genetic and immunological markers for resistance to Tb are under way. Preliminary studies showed no associations between NRAMP or DRB genes and resistance to Tb in deer. Patterns of immune responses seen in resistant animals suggest that both innate and acquired pathways of immunity are necessary to produce the resistant phenotype.
Focal cartilage defect compromises fluid‐pressure dependent load support in the knee joint

A focal cartilage defect involves tissue loss or rupture. Altered mechanics in the affected joint may play an essential role in the onset and progression of osteoarthritis. The objective of the present study was to determine the compromised load support in the human knee joint during defect progression from the cartilage surface to the cartilage–bone interface. Ten normal and defect cases were simulated with a previously tested 3D finite element model of the knee. The focal defects were considered in both condyles within high load‐bearing regions. Fluid pressurization, anisotropic fibril‐reinforcement, and depth‐dependent mechanical properties were considered for the articular cartilages and menisci. The results showed that a small cartilage defect could cause 25% reduction in the load support of the knee joint due to a reduced capacity of fluid pressurization in the defect cartilage. A partial‐thickness defect could cause a fluid pressure decrease or increase in the remaining underlying cartilage depending on the defect depth. A cartilage defect also increased the shear strain at the cartilage–bone interface, which was more significant with a full‐thickness defect. The effect of cartilage defect on the fluid pressurization also depended on the defect sites and contact conditions. In conclusion, a focal cartilage defect causes a fluid‐pressure dependent load reallocation and a compromised load support in the joint, which depend on the defect depth, site, and contact condition. Copyright © 2015 John Wiley & Sons, Ltd.
Chemotherapy in head and neck cancer.

SQUAMOUS-CELL carcinoma of the head and neck accounts for five per cent of the cases of cancer in the United States. Only one third of patients with this neoplasm present with localized disease easily curable by surgery and radiation. These treatment methods, however, have not provided adequate tumor control in the majority of patients who present with advanced local and regional disease. Local recurrences occur in up to 60 per cent of these patients, and distant metastases develop in 20 to 30 per cent; survival remains poor (0 to 40 per cent). 1 , 2 Until recently, chemotherapy has been reserved only for .
The Growth and Volatility of French Exporters

This paper provides evidence about the respective impact of age and size on the dynamics of rms in foreign markets, a critical input in models of rms dynamics. The analysis uses a census of French exports by rm-destinations-product over the period 1994-2008 with a monthly frequency. A rst result is that the growth of exporters between the rst and the second year is biased upwards when the growth rate is computed using calendar years instead of the birth date. Our estimations show that, controlling for size, age is negatively related to net growth of exports for surviving exporters. Controlling for age, the relation between average size and net growth of exports is non-monotonic. Finally, the contribution of entry and exit in foreign markets (products and destinations) to total exports growth by rms is decreasing with age and (sharply) with size.
Automatic Segmentation and Quantification of White and Brown Adipose Tissues from PET/CT Scans

In this paper, we investigate the automatic detection of white and brown adipose tissues using Positron Emission Tomography/Computed Tomography (PET/CT) scans, and develop methods for the quantification of these tissues at the whole-body and body-region levels. We propose a patient-specific automatic adiposity analysis system with two modules. In the first module, we detect white adipose tissue (WAT) and its two sub-types from CT scans: Visceral Adipose Tissue (VAT) and Subcutaneous Adipose Tissue (SAT). This process relies conventionally on manual or semi-automated segmentation, leading to inefficient solutions. Our novel framework addresses this challenge by proposing an unsupervised learning method to separate VAT from SAT in the abdominal region for the clinical quantification of central obesity. This step is followed by a context driven label fusion algorithm through sparse 3D Conditional Random Fields (CRF) for volumetric adiposity analysis. In the second module, we automatically detect, segment, and quantify brown adipose tissue (BAT) using PET scans because unlike WAT, BAT is metabolically active. After identifying BAT regions using PET, we perform a co-segmentation procedure utilizing asymmetric complementary information from PET and CT. Finally, we present a new probabilistic distance metric for differentiating BAT from non-BAT regions. Both modules are integrated via an automatic body-region detection unit based on one-shot learning. Experimental evaluations conducted on 151 PET/CT scans achieve state-of-the-art performances in both central obesity as well as brown adiposity quantification.
Screening for depression among patients with multiple sclerosis: two questions may be enough

Background Depression among patients with multiple sclerosis (MS) is common and has a significant impact on quality of life. As many as two-thirds of depressed MS patients receive no treatment for their depression. While guidelines for depression management suggest screening, the only validated screening tools are questionnaires, which have not been widely implemented in practice. This is the first study on the effectiveness of using two questions assessing mood and anhedonia (loss of interest or pleasure) in screening for major depressive disorder (MDD) in MS. Methods MS patients under the care of neurologists were recruited from a large health maintenance organization (HMO). The MDD module of the Structured Clinical Interview for the DSM-IV and screening questions was administered. Results Of the 260 participants, 26% met the criteria for MDD. Among patients with MDD, 67% received no anti-depressant medication. The MDD screen identified 99% (95% CI: 91–100%) of cases. Discussion A brief, two question screen is reliable in identifying MS patients with MDD. This suggests that asking these two brief questions could identify almost all MS patients meeting MDD criteria, with minimal numbers of false positives. Multiple Sclerosis 2007; 13: 215–219. http://msj.sagepub. com
Enhancing the Frequency Adaptability of Periodic Current Controllers With a Fixed Sampling Rate for Grid-Connected Power Converters

Grid-connected power converters should employ advanced current controllers, e.g., proportional resonant (PR) and repetitive controllers (RC), in order to produce high-quality feed-in currents that are required to be synchronized with the grid voltage. The synchronization is actually to detect the instantaneous grid information (e.g., frequency and phase of the grid voltage) for the current control, which is commonly performed by a phase-locked loop (PLL) system. Hence, harmonics and deviations in the estimated frequency by the PLL could lead to current tracking performance degradation, especially for the periodic signal controllers (e.g., PR and RC) with a fixed sampling rate. In this paper, the impacts of frequency deviations induced by the PLL and/or the grid disturbances on the selected current controllers are investigated by analyzing the frequency adaptability of these current controllers. Subsequently, strategies to enhance the frequency adaptability of the current controllers are proposed for the power converters to produce high-quality feed-in currents even in the presence of grid frequency deviations. Specifically, by feeding back the PLL estimated frequency to update the center frequencies of the resonant controllers and by approximating the fractional delay using a Lagrange interpolating polynomial for the RC, respectively, the frequency-variation-immunity of these periodic current controllers with a fixed sampling rate is improved. Experiments on a single-phase grid-connected system are presented, which have verified the discussions and the effectiveness of the frequency adaptive current controllers.
Analysis of pristanic acid beta-oxidation intermediates in plasma from healthy controls and patients affected with peroxisomal disorders by stable isotope dilution gas chromatography mass spectrometry.

In this paper we report the development of highly sensitive, selective, and accurate stable isotope dilution gas chromatography negative chemical ionization mass spectrometry (GC-NCI-MS) methods for quantification of peroxisomal beta-oxidation intermediates of pristanic acid in human plasma: 2,3-pristenic acid, 3-hydroxypristanic acid, and 3-ketopristanic acid. The carboxylic groups of the intermediates were converted into pentafluorobenzyl esters, whereas hydroxyl groups were acetylated and ketogroups were methoximized. Hereafter, the samples were subjected to clean-up by high performance liquid chromatography. Analyses were performed by selected monitoring of the carboxylate anions of the derivatives. Control values of all three metabolites were established (2,3-pristenic acid: 2-48 nm, 3-hydroxypristanic acid: 0.02-0.81 nm, 3-ketopristanic acid: 0.07-1.45 nm). A correlation between the concentrations of pristanic acid and its intermediates in plasma was found. The diagnostic value of the methods is illustrated by measurements of the intermediates in plasma from patients with peroxisomal disorders. It is shown that in generalized peroxisomal disorders, the absolute concentrations of 2,3-pristenic acid, 3-hydroxypristanic acid, and 3-ketopristanic acid were comparable to those in the controls, whereas relative to the pristanic acid concentrations these intermediates were significantly decreased. In bifunctional protein deficiency, elevated levels of 2,3-pristenic acid and 3-hydroxypristanic acid were found. 3-Ketopristanic acid, although within the normal range, was relatively low when compared to the high pristanic acid levels in these patients. -Verhoeven, N. M. , D. S. M. Schor, E. A. Struys, E. E. W. Jansen, H. J. ten Brink, R. J. A. Wanders, and C. Jakobs. Analysis of pristanic acid beta-oxidation intermediates in plasma from healthy controls and patients affected with peroxisomal disorders by stable isotope dilution gas chromatography mass spectrometry.
Identification of power line outages

This paper considers the problem of identifying power line outages throughout an electric interconnection based on changes in phasor angles observed at a limited number of buses. In existing approaches for solving the line outage identification problem the unobserved phasor angle data is ignored and identification is based on the observed phasor angles extracted from the data. We propose, instead, a least-squares approach for estimating the unobserved phasor angles, which is shown to yield a solution to the line outage identification problem that is equivalent to the solution obtained with existing approaches. This equivalence suggests an implementation of the solution to the line outage identification problem that is computationally more efficient than previous methods. A natural extension of the least-squares formulation leads to a generalization of the line outages identification problem in which the grid parameters are unknown.
Active and passive mechanisms of helicases

In this work, we discuss the active or passive character of helicases. In the past years, several studies have used the theoretical framework proposed by Betterton and Julicher [Betterton, M.D. and Julicher, F. (2005) Opening of nucleic-acid double strands by helicases: active versus passive opening. Phys. Rev. E, 71, 11904–11911. ] to analyse the unwinding data and assess the mechanism of the helicase under study (active versus passive). However, this procedure has given rise to apparently contradictory interpretations: helicases exhibiting similar behaviour have been classified as both active and passive enzymes [Johnson, D.S. , Bai, L. Smith, B.Y. , Patel, S.S. and Wang, M.D. (2007) Single-molecule studies reveal dynamics of DNA unwinding by the ring-shaped T7 helicase. Cell, 129, 1299–1309; Lionnet, T. , Spiering, M.M. , Benkovic, S.J., Bensimon, D. and Croquette, V. (2007) Real-time observation of bacteriophage T4 gp41 helicase reveals an unwinding mechanism Proc. Natl Acid. Sci., 104, 19790–19795]. In this work, we show that when the helicase under study has not been previously well characterized (namely, if its step size and rate of slippage are unknown) a multi-parameter fit to the afore-mentioned model can indeed lead to contradictory interpretations. We thus propose to differentiate between active and passive helicases on the basis of the comparison between their observed translocation velocity on single-stranded nucleic acid and their unwinding rate of double-stranded nucleic acid (with various GC content and under different tensions). A threshold separating active from passive behaviour is proposed following an analysis of the reported activities of different helicases. We study and contrast the mechanism of two helicases that exemplify these two behaviours: active for the RecQ helicase and passive for the gp41 helicase.
Regular coordinate systems for Schwarzschild and other spherical spacetimes

The continuation of the Schwarzschild metric across the event horizon is a well-understood problem discussed in most textbooks on general relativity. Among the most popular coordinate systems that are regular at the horizon are the Kruskal–Szekeres and Eddington–Finkelstein coordinates. Our first objective in this paper is to popularize another set of coordinates, the Painleve–Gullstrand coordinates. These were first introduced in the 1920s, and have been periodically rediscovered since; they are especially attractive and pedagogically powerful. Our second objective is to provide generalizations of these coordinates, first within the specific context of Schwarzschild spacetime, and then in the context of more general spherical spacetimes.
The Radar Data Transmission to Computer Support System of Ship Safety

The radar system with automatic radar plotting aid constitutes a source of input data for algorithm determining safe trajectory of a ship. The article introduces radar data transmission details. It also presents the application of computer decision support system in collision situations of passage with greater quantity of met objects on board research and training ship m/v HORYZONT II. The system enables navigational data transmission from radar system and automatic determining of safe manoeuvre or safe trajectory of a ship. Computer programme used for communication with ARPA system was designed in Matlab software.
Feasiblity of Hungarian algorithm based Scheduling

An optimal resource allocation algorithm, Hungarian algorithm, is not directly applicable to manufacturing scheduling problems, because solutions of resource allocation problems may violate precedence constraints among processes that constitute individual manufacturing jobs. To apply Hungarian algorithm to scheduling problems, in this paper, several strategies for assigning prices to time slots of individual machines, which are allocated to processes, are proposed. Preliminary experimentation results showed that these strategies can generate near optimal schedules, i.e. when lengths of scheduling horizons were larger than 3 times of the maximum lengths of jobs, generated schedules could complete given jobs while maintaining the deterioration of the efficiency less than 5% from optimal schedules.
The construction and approximation for feedforword neural networks with fixed weights

There have been various studies on approximation ability of feedforward neural networks. More existing studies are only concerned with the density on how a continuous function can be approximated by the networks. However, the results concerning the error of approximation of neural networks, in applications, are of particular interest to engineers. The results reported in the literature have “slow approximation rates” (of the order of 1/√n, where n is the number of nodes in the hid-den layer of neural networks). Here we show by a constructive method that for any f ∊ C [a, b], the function can be approximated by a neural network with one hidden layer, and the order of approximation is 1/nα for the target function f ∊ LipM (α), 0 < ≤ 1. This approach naturally yields the design of the hidden layer and some Jackson-type estimations.
A simple improved distributed algorithm for minimum CDS in unit disk graphs

Several routing schemes in ad hoc networks first establish a virtual backbone and then route messages via back-bone nodes. One common way of constructing such a backbone is based on the construction of a minimum connected dominating set (CDS). In this paper we present a very simple distributed algorithm for computing a small CDS. Our algorithm has an approximation factor of at most 6.91, improving upon the previous best known approximation factor of 8 due to Wan et al. [INFOCOM'02], The improvement relies on a refined analysis of the relationship between the size of a maximal independent set and a minimum CDS in a unit disk graph. This subresult also implies improved approximation factors for many existing algorithm.
Team formation for collaborative learning with social network consideration based on edX's online discussion board

Collaborative Learning (CL) along with the changing of the teaching environment, the way how students interact has also changed. The rise of Massive Open Online Courses (MOOCs) lets the teaching environment turn into online teaching. Deriving from MOOCs, Small Private Online Course (SPOC) incorporates the concept of Blended Learning (BL), which combines the advantage of MOOCs and face-to-face teaching. In this context, implies an enormous amount of consideration of group division factors and information volume when teachers organize groups. In the face of an unprecedented workload size, organizing groups manually is extremely time consuming and difficult for teachers. In this paper, we make use of the advantages of the conditions of SPOC, retrieving the social network of students on the online discussion board, then the heterogeneous division of groups based on academic results is the supplementary to do grouping. In addition, this paper makes use of edX, a representative platform of MOOCs, and develops the group division modules based on the format of the online discussion boards of the platform. Comparing with the way of grouping by students themselves in this context, the method which brought out by this paper do a better job in learning performance in spite of the satisfactions is worse.
Server consolidation in Clouds through gossiping

The success of Cloud computing, where computing power is treated as a utility, has resulted in the creation of many large datacenters that are very expensive to build and operate. In particular, the energy bill accounts for a significant fraction of the total operation costs. For this reason a significant attention is being devoted to energy conservation techniques, for example by taking advantage of the built-in power saving features of modern hardware. Cloud computing offers novel opportunities for achieving energy savings: Cloud systems rely on virtualization techniques to allocate computing resources on demand, and modern Virtual Machine (VM) monitors allow live migration of running VMs. Thus, energy conservation can be achieved through server consolidation, moving VM instances away from lightly loaded computing nodes so that they become empty and can be switched to low-power mode. In this paper we present V-MAN, a fully decentralized algorithm for consolidating VMs in large Cloud datacenters. V-MAN can operate on any arbitrary initial allocation of VMs on the Cloud, iteratively producing new allocations that quickly converge towards the one maximizing the number of idle hosts. V-MAN uses a simple gossip protocol to achieve efficiency, scalability and robustness to failures. Simulation experiments indicate that, starting from a random allocation, V-MAN produces an almost-optimal VM placement in just a few rounds; the protocol is intrinsically robust and can cope with computing nodes being added to or removed from the Cloud.
Credibility: How Agents Can Handle Unfair Third-Party Testimonies in Computational Trust Models

Usually, agents within multiagent systems represent different stakeholders that have their own distinct and sometimes conflicting interests and objectives. They would behave in such a way so as to achieve their own objectives, even at the cost of others. Therefore, there are risks in interacting with other agents. A number of computational trust models have been proposed to manage such risk. However, the performance of most computational trust models that rely on third-party recommendations as part of the mechanism to derive trust is easily deteriorated by the presence of unfair testimonies. There have been several attempts to combat the influence of unfair testimonies. Nevertheless, they are either not readily applicable since they require additional information which is not available in realistic settings, or ad hoc as they are tightly coupled with specific trust models. Against this background, a general credibility model is proposed in this paper. Empirical studies have shown that the proposed credibility model is more effective than related work in mitigating the adverse influence of unfair testimonies.