Miracle-dz/UniFAR-FTUs huggingface dataset:
Rheumatoid Elbow Destruction and its Treatment with Souter-Strathclyde Arthroplasty

Elbow involvement is very rarely seen in the early years of rheumatoid arthritis, but 15 years after onset of disease approximately two thirds of patients have symptoms or/and radiological changes in their elbows. The severity of elbow deformity depends on the activity of synovitis, which may cause destruction of the cartilage, the bones and the ligaments. Surgical treatment of the rheumatoid elbow is not very common; approximately one hundred elbow replacements are performed in Finland annually and apparently, the number of synovectomies is even smaller. In Study l the incidence of involvement and nature of destruction of humeroulnar and humeroradial joints were evaluated in a prospectively followed cohort of 74 patients with seropositive and erosive rheumatoid arthritis. At the 15-year follow-up standard anteroposterior and lateral radiographs were taken of 148 elbow joints and the grade of destruction assessed by the Larsen method. Erosive involvement (> Larsen grade 2) was observed in 75 (51%) of the 148 joints in 45 (61%) patients out of 74. Thirty patients had bilateral and 15 unilateral affection. Erosions were most often found on the capitellum (43%) and the lateral epicondyle (39%) of the humerus or on the olecranon of the ulna (35%). Studies ll-Vl were based on a follow-up of 525 consecutive Souter-Strathclyde elbow replacements undertaken during the years 1982-1997. There were 372 female and 34 male patients with a mean age of 57 years. A total of 119 patients underwent a bilateral procedure. The indication for operation in 522 cases was rheumatoid arthritis or other chronic inflammatory joint disease. The mean duration of the disease at time of operation was 25 years (2-70). By reason of complications there were 108 reoperations in 82 patients up to the end of 1998. During the early years of this study the relative number of primary complications
Microstructuring of Hyaluronic Acid cell cul- ture scaffolds

Animal models often fail to predict the efficacy and response to drugs in humans, and also raise ethical concerns as many experiments cause pain, suffering or distress in the animals used. Thus, there is a need to develop new and better in vitro models which can help reduce the need for animal experiments. The goal of this work is to explore the possibilities of using microstructured hyaluronic acid hydrogels as cell scaffolds for in vitro studies. Two different approaches have been investigated. The first approach is to pattern a photocrosslinkable hyaluronic acid and gelatin hydrogel using the well-known method of photolithography, providing cell culture scaffolds with tailor made topographies. The second approach is to chemically link RGD peptides, which provide cell adhesion sites, using a photoinduced reaction, thus allowing for photopatterned gels with RGD peptides present in specific patterns. The two approaches are one step on the way towards providing cell culture scaffolds which show the same rich variability in physical, topological and biochemical properties as the natural extra cellular matrix does in vivo.
The diffusion of carbon atoms inside carbon nanotubes

We combine electron irradiation experiments in a transmission electron microscope with kinetic Monte Carlo simulations to determine the mobility of interstitial carbon atoms in single-walled carbon nanotubes. We measure the irradiation dose necessary to cut nanotubes repeatedly with a focused electron beam as a function of the separation between the cuts and at different temperatures. As the cutting speed is related to the migration of displaced carbon atoms trapped inside the tube and to their recombination with vacancies, we obtain information about the mobility of the trapped atoms and estimate their migration barrier to be about 0.25 eV. This is an experimental confirmation of the remarkably high mobility of interstitial atoms inside carbon nanotubes, which shows that nanotubes have potential applications as pipelines for the transport of carbon atoms.
utologous skeletal myoblast transplantation in patients ith nonacute myocardial infarction: 1-year follow-up

ethods: Twelve patients with a previous myocardial infarction and ischemic oronary artery disease underwent treatment with coronary artery bypass grafting urgery and intramyocardial injection of autologous skeletal myoblasts cultured ith autologous serum. Global and regional cardiac function was assessed by echoardiogram. Fluorine 18 fluorodeoxyglucose and nitrogen 13–ammonia positron emision tomography studies were used to determine cardiac viability and perfusion. A roup of historical control patients (n 14) treated with coronary artery bypass rafting surgery without myoblast transplantation was analyzed.
Stimulation of inducer T lymphocytes to undergo clonal expansion and differ- entiation requires recognition of nominal antigen in the context of polymorphic determinants of class II major histocompatibility complex (MHC) 1 glycoproteins

Stimulation of inducer T lymphocytes to undergo clonal expansion and differentiation requires recognition of nominal antigen in the context of polymorphic determinants of class II major histocompatibility complex (MHC) 1 glycoproteins (Ia) displayed on specialized accessory cells (for review, see 1). Effective stimulation requires both an ill-defined "processing" of native antigen (2-6), perhaps corresponding to partial intracellular proteolysis and membrane reexpression of antigenic peptides, and the action of poorly characterized "lymphokines" (2, 4), possibly including, but not limited to, interleukin 1 (IL-1) (7). A more precise understanding of T cell antigen recognition thus requires greater knowledge of the structural features of the interacting components, i.e., the T cell receptor, Ia molecule, and immunogenic peptide, and more information about the additional membrane and soluble components involved in turning the recognition event into complete T cell activation. Substantial progress has recently been made in each of these areas. Detailed analyses of the minimal stimulatory peptide(s) of protein antigens has been carried out in several laboratories (6, 8-10). A two-chain polypeptide structure for the antigen receptor of MHC-restricted T cells has been demonstrated (11-14) and a gene encoding one of these peptides has been cloned (15, 16). Finally, the molecular cloning of class II genes of mouse and man has provided a relatively complete picture of the primary structure of these glycoproteins and identified the major site of intraspecies polymorphism as the amino-terminal domain of both a and/3 chains (reviewed in 17). The availability of these cloned Ia genes has permitted the initiation of studies
Neural Network Model for Predicting Students' Achievement in Blended Courses at the University of Dar Es Salaam

Educator’s knowledge about the likely students’ achievement in blended courses prior to sitting for examinations provides room for early intervention on students’ learning process, especially to those at risk. Unfortunately, Leaning Management Systems (LMSs), Moodle in particular lacks an environment to assist educators access such knowledge from time to time before undertaking their examinations. This raised the need to propose a model, of which from time to time would be providing the likely students’ achievement based on activities in Moodle and previous achievement, taking a case of postgraduate programmes at the University of Dar es Salaam. This study applied artificial neural networks in building a prediction model. Simulations were conducted in Matrix Laboratory (MATLAB) utilizing seventy eight instances (78) of students’ logs of three blended courses extracted from Moodle for 2013/2014 and 2014/2015 academic years. Mean Square Error (MSE) and Coefficient of Determination ( R 2 ) performance metrics were used to find the best prediction model considering ten possible models. The study revealed a model with architecture of 4:10:1 trained with Bayesian Regularization (BR) to be the best model resulting to least MSE of 0.0170 and high R 2 of 0.93 on training. During testing, the model successfully predicted 78% of the students’ achievement with risk and pass status.
REDES COMPLEXAS NA EXTRAÇÃO DE CARACTERÍSTICAS EM IMAGENS DE PEIXES

Este trabalho apresenta uma abordagem sobre a analise de imagens utilizando as tecnicas de Redes Complexas para a obtencao de similaridades entre imagens. Inicialmente serao extraidas as caracteristicas da borda das imagens, as quais serao entendidas computacionalmente como matrizes. Atraves dessas matrizes serao geradas matrizes de adjacencias, que serao utilizadas para a verificacao das conexoes dos vertices (pixels) das imagens. Extraida a matriz de adjacencia, sera realizada a extracao do grau dos vertices para um limiar T e a extracao do grau medio dos vertices. Na extracao do grau dos vertices cada limiar sera aplicado no calculo e retornara uma matriz que sera analisada com outras matrizes extraidas verificando a probabilidade de isomorfismo.
Human Age, Gender and Weight Determination Using Face Images

: Today life is rapidly changing. New innovations, new things daily happing in today’s life. Technology is going beyond our expectation. Also for this changing technology security issue is very important. This paper is about method for real time human Face detection and determining their age, gender and weight. Automatic age estimation, it remains a challenging problem. This is because the face aging process is determined not only by intrinsic factors, e.g. genetic factors, but also by ex-trinsic factors, e.g. lifestyle, expression, and environment. There are many methods have been proposed in the literature for the age estimation and gender classification. However, all of them have still disadvantage such as not complete reflection about face structure, face texture. We propose a hierarchical approach for automatic age estimation. Two main components for building an effective age estimator are facial feature extraction and estimator learning. Using feature extraction and comparing with our input data in which we have different age group face images with specified weight. Here we using raspberry pi for better efficiency. In this project work on the identification of younger image and older image are focused on the methods using image processing. First we extract certain features from the input Face images, later using different method like thresholding, segmentation, edge detection and thus we get related databases. Comparing several trained databases, we get a specific range for younger images and older images also get information of their gender and weight. Hence this project is very useful for detection of human age, weight and gender form face images only.
An asymmetric cryptographuic key assignment scheme for access control in totally-ordered hierarchies

Many methods based on cryptography have been proposed to solve the problem of access control in hierarchic structures. However, these schemes are only used in symmetric (or one-key) cryptosystems. In this article, we propose a new multilevel access control scheme for a totally-ordered hierarchy that can be used in asymmetric (or two-key) cryptosystem. It is well known that there are two main advantages in asymmetric cryptography: key distribution and authentication. Our scheme is, to our best knowledge, the first to be used as an asymmetric cryptosystem.
Contribution ENDOVASCULAR SHEAR STRAIN ELASTOGRAPHY FOR THE DETECTION AND CHARACTERIZATION OF THE SEVERITY OFATHEROSCLEROTIC PLAQUES : IN VITRO VALIDATION AND IN VIVO EVALUATION

YOUNES MAJDOULINE,* JACQUES OHAYON,yz ZAHRA KESHAVARZ-MOTAMED,* MARIE-H EL ENE ROY CARDINAL,* DAMIEN GARCIA,*xk LOUISE ALLARD,* SOPHIE LEROUGE,{# FR ED ERIC ARSENAULT,k** GILLES SOULEZ,k** and GUY CLOUTIER*k *Laboratory of Biorheology andMedical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montr eal, Qu ebec, Canada; yLaboratory TIMC-IMAG/DyCTiM, University Joseph-Fourier, CNRS UMR 5525, Grenoble, France; zUniversity of Savoie, Polytech Annecy-Chambery, Le Bourget du Lac, France; xResearch Unit of Biomechanics and Imaging in Cardiology, University of Montreal Hospital Research Center (CRCHUM), Montr eal, Qu ebec, Canada; kDepartment of Radiology, Radio-Oncology and Nuclear Medicine, and Institute of Biomedical Engineering, University of Montreal, Montr eal, Qu ebec, Canada; {Laboratory of Endovascular Biomaterials, University of Montreal Hospital Research Center (CRCHUM), Montr eal, Qu ebec, Canada; Department of Mechanical Engineering, Ecole de technologie sup erieure, Montr eal, Qu ebec, Canada; and **Department of Radiology, University of Montreal Hospital (CHUM), Montr eal, Qu ebec, Canada
Trial Implantation of Heart Rate Data Loggers in Pinnipeds

Abstract Pinnipeds are major consumers in marine ecosystems, and understanding their energy budgets is essential to determining their role in food webs, particularly where there is competition with fisheries. Food consumption and energy expenditure have been evaluated in pinnipeds using different methods, but the use of heart rate to estimate energy expenditure is potentially a very powerful tool suited to the life history of these animals. We tested a procedure for the subcutaneous implantation of heart rate data loggers to determine whether heart rate could be recorded for ≥1 year in free-ranging pinnipeds, as it has been in birds. We implanted 3 captive California sea lions (Zalophus californianus) and 3 captive northern elephant seals (Mirounga angustirostris) with heart rate data loggers and monitored their recovery and behavior in a controlled environment. In both species, the implantation site allowed for excellent detection of the electrocardiogram, and we observed heart rate signatures characteristic of behaviors such as resting and diving. Although all 3 sea lions recovered well from the implantation surgery, all 3 elephant seals showed a substantial inflammatory response for unknown reasons, and we removed the implanted data loggers. Subcutaneous implantation of data loggers is a powerful technique to study physiology, energetics, and behavior in California sea lions, but more work is required to realize the potential of this technique in northern elephant seals.
Evaluation of Aggregators for Integration of Large-scale Consumers in Smart Grid

Abstract Utilization of consumers to mitigate the impact of increasing renewable resources on power systems is one of the visions of future smart grids. Flexible consumers are consumers who can change their consumption patterns in such a way as to help the grid to tackle the balancing problem. In previous work, we proposed a hierarchical structure to provide regulating power to the grid by just utilizing the consumption units. The main focus of that work was on designing a centralized controller, a so-called aggregator, which is responsible for aggregating the flexibilities in an optimal way. To accomplish the optimization, the aggregator requires a model which describes the behavior of each consumption unit. These models should be sufficiently simple to be used in the optimization task. However, simple models might not capture all dynamics and features of the real system. In this paper, we will evaluate the proposed setup to understand to what extent the utilization of simplified models can lead to reasonable results. To this end, we will connect the aggregator to a complex and verified model of an actual supermarket refrigeration system which enables us to investigate the closed-loop behavior of the whole set-up.
Spatial quantum noise of semiconductor lasers

The transverse distribution of intensity noise in the far field of semiconductor lasers has been experimentally studied. For a single-mode edge-emitting laser, it has been found that a large amount of noise is present in higher-order nonlasing transverse modes parallel to the diode junction. In the case of a spatially multimode vertical-cavity surface-emitting laser, each mode exhibits a large noise, but these noises show strong anticorrelations.
Study of the Carrier-Aided Thin Film Electrode Array Design for Cochlear Insertion

The micro-fabricated thin film electrode array (TFEA) has been a promising design for cochlear implants (CIs) because of its cost-effectiveness and fabrication precision. The latest polymer-based cochlear TFEAs have faced difficulties for cochlear insertion due to the lack of structural stiffness. To stiffen the TFEA, dissolvable stiffening materials, TFEAs with different structures, and TFEAs with commercial CIs as carriers have been invested. In this work, the concept of enhancing a Parylene TFEA with Kapton tape as a simpler carrier for cochlear insertion has been proved to be feasible. The bending stiffness of the Kapton-aided TFEA was characterized with an analytical model, a finite element model, and a cantilever bending experiment, respectively. While the Kapton tape increased the bending stiffness of the Parylene TFEA by 103 times, the 6-μm-thick TFEA with a similar Young’s modulus, as a polyimide, in turn significantly increased the bending stiffness of the 170-μm-thick Kapton carrier by 60%. This result indicated that even the TFEA is ultra-flexible and that its bending stiffness should not be neglected in the design or selection of its carrier.
Experimental study of the anaerobic urban wastewater treatment in a submerged hollow-fiber membrane bioreactor at semi-industrial scale

The aim of this study was to assess the effect of several operational variables on both biological and separation process performance in a submerged anaerobic membrane bioreactor pilot plant that treats urban wastewater. The pilot plant is equipped with two industrial hollow-fiber ultrafiltration membrane modules (PURON ® Koch Membrane Systems, 30 m 2 of filtration surface each). It was operated under mesophilic conditions (at 33 oC), 70 days of SRT, and variable HRT ranging from 20 to 6 hours. The effects of the influent COD/SO4-S ratio (ranging from 2 to 12) and the MLTS concentration (ranging from 6 to 22 g·L -1 ) were also analysed. The main performance results were about 87% of COD removal, effluent VFA below 20 mg L -1 and biogas methane concentrations over 55% v/v. Methane yield was strongly affected by the influent COD/SO4-S ratio. No irreversible fouling problems were detected, even for MLTS concentrations above 22 g·L -1 .
Information Guided Exploration of Scalar Values and Isocontours in Ensemble Datasets

Uncertainty of scalar values in an ensemble dataset is often represented by the collection of their corresponding isocontours. Various techniques such as contour-boxplot, contour variability plot, glyphs and probabilistic marching-cubes have been proposed to analyze and visualize ensemble isocontours. All these techniques assume that a scalar value of interest is already known to the user. Not much work has been done in guiding users to select the scalar values for such uncertainty analysis. Moreover, analyzing and visualizing a large collection of ensemble isocontours for a selected scalar value has its own challenges. Interpreting the visualizations of such large collections of isocontours is also a difficult task. In this work, we propose a new information-theoretic approach towards addressing these issues. Using specific information measures that estimate the predictability and surprise of specific scalar values, we evaluate the overall uncertainty associated with all the scalar values in an ensemble system. This helps the scientist to understand the effects of uncertainty on different data features. To understand in finer details the contribution of individual members towards the uncertainty of the ensemble isocontours of a selected scalar value, we propose a conditional entropy based algorithm to quantify the individual contributions. This can help simplify analysis and visualization for systems with more members by identifying the members contributing the most towards overall uncertainty. We demonstrate the efficacy of our method by applying it on real-world datasets from material sciences, weather forecasting and ocean simulation experiments.
Improving Jet Mass and Transverse Momentum Calibration in the ATLAS Detector With Machine Learning Techniques

I investigate an improved method for correcting jet energy scale and mass measurements obtained in the ATLAS detector at the LHC. Machine learning techniques present an aractive alternative to the current manual approach used to determine how to adjust measurements of jet transverse momentum, energy, and mass based on all reported jet aributes. Using the Python module Tensorow for machine learning functions, I explored the calibration of jet measurements from the ATLAS detector using training and validation data sets of Monte Carlo-simulated events and corresponding simulated detector measurements. I optimized the neural network used to calibrate the measurements in order to improve the calibration and beer understand the network and the quantities it is calibrating. Dierent node activation functions, optimizers, network layouts, initialization options, data normalization techniques, learning rates, and network inputs were explored. For the validation sample of jets, the ratio of the quantity (transverse momentum, mass, etc.) calculated based on the neural network calibration to the true value was ploed. e quality of the network calibration was determined by the narrowness and proximity to one of the distribution of these ratios for the validation jets. For the jet transverse momentum, the calibrations improve slightly on the manual calibrations, and are achieved in minutes at most (hours if jet substructure data is included), resulting in a mean of 1.0 and an RMS of 0.05 for this distribution. For the jet mass scale calibration, the neural network output represents a signicant accuracy improvement over the existing jet mass calibration method, yielding a mean of 1.01 and an RMS of 0.41 for the distribution, and takes approximately ve hours to train.
SURGICAL PERSONNEL' ADHERENCE TO ANTIBIOTIC POLICIES

SUMMARY - Objectives. This work aimed at studying the adherence of personnel of the Surgery clinic of our institute to antibiotic policies in place. - Methods. Antimicrobial resistance surveillance of the alert resistant microorganisms (Staphylococcus aureus (MRSA), Enterobacteriaceae (ESBL-producing), Pseudomonas aeruginosa, MDR); Antibiotic consumption calculation (ABC calc, D. Monnet); Audits of antibiotic prescriptions, and Inquiries – were performed. - Results. Current antibiotic policies in the Surgery clinic (50-bed) were prepared, discussed and introduced in 2003. Since then, five 3-month audits of antibiotic prescriptions took place. During the last four years (2006-2009), the problem resistant organisms were: MRSA, 10-36 %; ESBL-producing Enterobacteriaceae, 14-23 %; MDR P. aeruginosa, 30-47 % and carbapenem-resistant, 0-35 %. Antibiotic consumption was between 47.9 and 61.9 DDD/100 bed-day, and first generation cephalosporins were the top used antibiotics (29.535.2 DDD/100 bed-day). Two inquiries (2007 and 2009) revealed: - a good compliance with the policies, with the exception of the duration of antibiotic prophylaxis, - and a comprehensive knowledge on antibiotics and antibiotic resistance. - Conclusion. With one exception (the duration of antibiotic prophylaxis) this study revealed good adherence to antibiotic policies, as well as professional attitudes towards the rational use of antibiotics.