Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation and learning of laproscopic donor nephrectomy by a non‐transplant general surgeon with advanced laparoscopic skills

Introduction: Traditionally performed by vascular surgeons or urologists, laparoscopic nephrectomy for live kidney donor transplantation has emerged as a new effective and safe technique. This study examines the implementation of this technique at our centre, as performed by a single general surgeon with expertise in advanced laparoscopic surgery.
Comparison of methods and sampling designs to test for association between rare variants and quantitative traits

Genome‐wide association studies succeeded in finding genetic variants associated with various phenotypes, but a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some missing variation is due to rare variants. Latest sequencing technology facilitates the investigation of such rare variants, but their statistical analysis remains challenging. For quantitative traits, a commonly used approach is to contrast the frequency of putatively functional rare variants between subjects in the two tails of the trait distribution. The contrast is usually performed by Fisher's exact or similar test. These tests are conservative as they discard trait rank information and are most useful under the unrealistic homogeneity assumption (i.e., variants have similar effects). We propose, and investigate via simulations, various designs for resequencing studies and statistical methods that incorporate information about rank, predicted function and allow for heterogeneity of effects. We propose designs which accommodate heterogeneity by sequencing both tails and the middle of the trait and novel statistical tests for trend, for heterogeneity and for a combination of the two. The conclusions of the simulations are four fold: (1) sequencing both tails and the middle of the trait distributions is desirable when heterogeneity is suspected, (2) trend and heterogeneity statistics should be used alongside other methods, (3) using rank information improves power over Fisher's exact test when the number of rare variants is not very large and (4) due to high misclassification rates, incorporating current predictions of a variant's function does not improve power. Genet. Epidemiol. 35: 226‐235, 2011. © 2011 Wiley‐Liss, Inc.
Matryoshka Peek: Toward Learning Fine-Grained, Robust, Discriminative Features for Product Search

In sharp contrast to the traditional category/subcategory level image retrieval, product image search aims to find the images containing the exact same product. This is a challenging problem because in addition to being robust under different imaging conditions such as varying viewpoints and illumination changes, the features should also be able to distinguish the specific product among many similar products. Consequently, it is important to utilize a large dataset, containing many product classes, to learn a strongly discriminative representation. Building such a dataset requires laborious manual annotation. Toward learning fine-grained, robust, discriminative features for product image search, we present a novel paradigm that can construct the required dataset without any human annotation. Unlike other fine-grained recognition works that rely on high-quality annotated datasets and are very narrowly focused on a specific object category, our method handles multiple object classes and requires minimum human effort. First, an ImageNet pretrained model is used to generate product clusters. As the original features from ImageNet are not discriminative, the clusters generated by this unsupervised procedure contain much noise. We alleviate noise by explicitly modeling noise distribution and automatically detecting errors during learning. The proposed paradigm is general, requires minimum human efforts, and is applicable to any deep learning task where fine-grained discriminative features are desired. Extensive experiments on the ALISC dataset have demonstrated that our approach is sound and effective, surpassing the baseline GoogleNet model by 15.09%.
Sloping Binary Numbers: A New Sequence Related to the Binary Numbers

If the list of binary numbers is read by upward-sloping diagonals, the resulting ``sloping binary numbers'' 0, 11, 110, 101, 100, 1111, 1010, . (or 0, 3, 6, 5, 4, 15, 10, .) have some surprising properties. We give formulae for the n-th term and the n-th missing term, and discuss a number of related sequences.
Mechanical properties of defective carbon nanotube/polyethylene nanocomposites: A molecular dynamics simulation study

Because of their remarkable performance properties and technological promise, polymer nanocomposites reinforced with single-walled carbon nanotubes (SWCNTs) have attracted considerable attention in the engineering, applied physics, and materials science communities. Recent experimental and computational investigations have shown that the presence of nanoscale defects in CNTs can significantly impact their electrical, mechanical, and thermal properties. In this article, for the first time, we examine the effect of defective CNTs on the interfacial characteristics and mechanical properties of CNT/polyethylene (PE) nanocomposites. Our molecular dynamics simulations show that as few as five vacancy defects in each CNT in a high-volume-fraction CNT/PE nanocomposite can decrease the longitudinal Young's modulus of the nanocomposite by as much as 18%, and the shear stress at the CNT/polymer interface by as much as 38%. By accounting for nanoscale defects and their effect on the CNT/polymer interfacial mechanics, our findings provide a practical guide for designing nanocomposites that are capable of attaining a desired set of elastic performance properties. POLYM. COMPOS. , 2014. © 2014 Society of Plastics Engineers
Binding characteristics of Trichoderma reesei cellulases on untreated, ammonia fiber expansion (AFEX), and dilute‐acid pretreated lignocellulosic biomass

Studying the binding properties of cellulases to lignocellulosic substrates is critical to achieving a fundamental understanding of plant cell wall saccharification. Lignin auto‐fluorescence and degradation products formed during pretreatment impede accurate quantification of individual glycosyl hydrolases (GH) binding to pretreated cell walls. A high‐throughput fast protein liquid chromatography (HT‐FPLC)‐based method has been developed to quantify cellobiohydrolase I (CBH I or Cel7A), cellobiohydrolase II (CBH II or Cel6A), and endoglucanase I (EG I or Cel7B) present in hydrolyzates of untreated, ammonia fiber expansion (AFEX), and dilute‐acid pretreated corn stover (CS). This method can accurately quantify individual enzymes present in complex binary and ternary protein mixtures without interference from plant cell wall‐derived components. The binding isotherms for CBH I, CBH II, and EG I were obtained after incubation for 2 h at 4°C. Both AFEX and dilute acid pretreatment resulted in increased cellulase binding compared with untreated CS. Cooperative binding of CBH I and/or CBH II in the presence of EG I was observed only for AFEX treated CS. Competitive binding between enzymes was found for certain other enzyme–substrate combinations over the protein loading range tested (i.e., 25–450 mg/g glucan). Langmuir single‐site adsorption model was fitted to the binding isotherm data to estimate total available binding sites Ebm (mg/g glucan) and association constant Ka (L/mg). Our results clearly demonstrate that the characteristics of cellulase binding depend not only on the enzyme GH family but also on the type of pretreatment method employed. Biotechnol. Bioeng. 2011; 108:1788–1800. © 2011 Wiley Periodicals, Inc.
Structural Characteristic of the Initial Unfolded State on Refolding Determines Catalytic Efficiency of the Folded Protein in Presence of Osmolytes

Osmolytes are low molecular weight organic molecules accumulated by organisms to assist proper protein folding, and to provide protection to the structural integrity of proteins under denaturing stress conditions. It is known that osmolyte-induced protein folding is brought by unfavorable interaction of osmolytes with the denatured/unfolded states. The interaction of osmolyte with the native state does not significantly contribute to the osmolyte-induced protein folding. We have therefore investigated if different denatured states of a protein (generated by different denaturing agents) interact differently with the osmolytes to induce protein folding. We observed that osmolyte-assisted refolding of protein obtained from heat-induced denatured state produces native molecules with higher enzyme activity than those initiated from GdmCl- or urea-induced denatured state indicating that the structural property of the initial denatured state during refolding by osmolytes determines the catalytic efficiency of the folded protein molecule. These conclusions have been reached from the systematic measurements of enzymatic kinetic parameters (K m and k cat), thermodynamic stability (T m and ΔH m) and secondary and tertiary structures of the folded native proteins obtained from refolding of various denatured states (due to heat-, urea- and GdmCl-induced denaturation) of RNase-A in the presence of various osmolytes.
Handwritten and Machine Printed Text Separation in Document Images Using the Bag of Visual Words Paradigm

In a number of types of documents, ranging from forms to archive documents and books with annotations, machine printed and handwritten text may be present in the same document image, giving rise to significant issues within a digitisation and recognition pipeline. It is therefore necessary to separate the two types of text before applying different recognition methodologies to each. In this paper, a new approach is proposed which strives towards identifying and separating handwritten from machine printed text using the Bag of Visual Words paradigm (BoVW). Initially, blocks of interest are detected in the document image. For each block, a descriptor is calculated based on the BoVW. The final characterization of the blocks as Handwritten, Machine Printed or Noise is made by a Support Vector Machine classifier. The promising performance of the proposed approach is shown by using a consistent evaluation methodology which couples meaningful measures along with a new dataset.
Validation of executable application models mapped onto network-on-chip platforms

Due to the increasing design size, complexity, and heterogeneity of todaypsilas embedded systems, designers need novel design methods in order to validate application-specific functionality together with different platform implementation alternatives. Ideally, this should happen at as early stage of the design process as possible, so that designers can explore the design space before they have to commit to specific processor architectures or custom hardware implementation. This paper takes advantage of the hierarchical design style and the support for heterogeneous models of computation (MoC) existing in actor-oriented frameworks and presents a methodology for modelling and validation of multiprocessor embedded systems. The proposed methodology is fully model-based, with different modelling styles for the application and the underlying implementation platform. In this paper we focus on the validation of applications modelled using Ptolemy II actors and UML sequence diagrams, mapped onto multiprocessor network-on-chip (NoC) platforms. We also present a case study, where one executable application model is mapped onto different NoC topologies, and show the simulation results for communication latency of each alternative.
Connectivity, flow and transport in network models of fractured media

﻿ In order to evaluate the safety of radioactive waste disposal underground it is important to understand the way in which radioactive material is transported through the rock to the surface. If the rock is fractured the usual models may not be applicable. In this work we look at three aspects of fracture networks: connectivity, flow and transport. These are studied numerically by generating fracture networks in a computer and modelling the processes which occur. Connectivity relates to percolation theory, and critical densities for fracture systems are found in two and three dimensions. The permeability of two-dimensional networks is studied. The way that permeability depends on fracture density, network size and spread of fracture length can be predicted using a cut lattice model. Transport through the fracture network by convection through the fractures and mixing at the intersections is studied. The Fickian dispersion equation does not describe the resulting hydrodynamic dispersion. Extensions to the techniques to three dimensions and to include other processes are discussed.
COMPLEMENTING MHC‐ AND NON‐MHC‐LINKED GENES AND RESISTANCE TO AVIAN SARCOMA VIRUS‐INDUCED TUMOURS IN INBRED LINES OF CHICKENS

Schmidt‐Ruppin Rous sarcoma virus, subgroup B (SR‐RSV‐B), was inoculated into the wingwebs of chickens from three partially congenic inbred lines, G‐B1, G‐B2 and G‐B3, homozygous for different MHC (B region) haplotypes (genotypes =B1/B1, B2/B2 and B3/B3 respectively). All birds developed tumours but only the G‐B2 line resisted progressive tumour growth. Birds from lines G‐B1 and G‐B3 approached 100% susceptibility to progressive tumour growth, whereas most (G‐B1 x G‐B3) F1 hybrids were resistant to tumours induced by SR‐RSV‐B. The association of the resistance trait in F1 hybrids with genes of the B region was investigated by testing progeny of (G‐B1 x G‐B3) x G‐B1 F1 and (G‐B1 x G‐B2) x G‐B3 F1 backcross matings. Approximately 27% of the backcross population was resistant to SR‐RSV‐B‐induced tumours and these resistant offspring were predominantly of the B1/B3 phenotype.
Realized Volatility and Absolute Return Volatility: A Comparison Indicating Market Risk

Measuring volatility in financial markets is a primary challenge in the theory and practice of risk management and is essential when developing investment strategies. Although the vast literature on the topic describes many different models, two nonparametric measurements have emerged and received wide use over the past decade: realized volatility and absolute return volatility. The former is strongly favored in the financial sector and the latter by econophysicists. We examine the memory and clustering features of these two methods and find that both enable strong predictions. We compare the two in detail and find that although realized volatility has a better short-term effect that allows predictions of near-future market behavior, absolute return volatility is easier to calculate and, as a risk indicator, has approximately the same sensitivity as realized volatility. Our detailed empirical analysis yields valuable guidelines for both researchers and market participants because it provides a significantly clearer comparison of the strengths and weaknesses of the two methods.
Orthogonal Matching Pursuit: A Brownian Motion Analysis

A well-known analysis of Tropp and Gilbert shows that orthogonal matching pursuit (OMP) can recover a <i>k</i>-sparse <i>n</i>-dimensional real vector from <i>m</i>=4<i>k</i>log(<i>n</i>) noise-free linear measurements obtained through a random Gaussian measurement matrix with a probability that approaches one as <i>n</i>→∞. This work strengthens this result by showing that a lower number of measurements, <i>m</i>=2<i>k</i>log(<i>n</i>-<i>k</i>) , is in fact sufficient for asymptotic recovery. More generally, when the sparsity level satisfies <i>k</i><sub>min</sub> ≤ <i>k</i> ≤ <i>k</i><sub>max</sub> but is unknown, <i>m</i>=2<i>k</i><sub>max</sub>log(<i>n</i>-<i>k</i><sub>min</sub>) measurements is sufficient. Furthermore, this number of measurements is also sufficient for detection of the sparsity pattern (support) of the vector with measurement errors provided the signal-to-noise ratio (SNR) scales to infinity. The scaling <i>m</i>=2<i>k</i>log(<i>n</i>-<i>k</i>) exactly matches the number of measurements required by the more complex lasso method for signal recovery with a similar SNR scaling.
Faraday's Law via e-experiments as an example of inquiry-based learning

The contribution demonstrates a practical application of the strategy of Integrated e-Learning via hands-on, remote and virtual experiments by means of the prepared interactive teaching tool in the form of a webpage titled “Electromagnetism” (http://e-materialy.net76.net/index.html). It is designed in accordance with the method of inquiry-based learning where the active involvement of the students in the construction of their knowledge plays a decisive role. The paper presents the possibility of the utilization of e-experiments to secondary school physics education. The design and the realization of simple electromagnetic experiments as well as the remote experiment Faraday's Law are also introduced (free available on http://remotelab4.truni.sk/faraday.html).
Effect of Wollastonite Microfiber on Ultra-High-Performance Fiber-Reinforced Cement-Based Composites Based on Application of Multi-Scale Fiber-Reinforcement System

The development of ultra-high-performance fiber-reinforced cement-based composites (UHP-FRCCs) was motivated by the need for a new and versatile material with high energy absorption capacity. With its excellent cracking resistance and consequent long life, UHP-FRCC is suitable for use in seismic design applications. The present study proposes a material design concept based on a multi-scale fiber-reinforcement system. In this approach, long, thick macrofibers are blended with short, thin mesofibers and microfibers. Such a combination of macrofibers, mesofibers, and microfibers is expected to enhance the mechanical properties of the composite under tension. However, the ductility of cement-based composites reinforced solely by microfibers is largely unknown. Therefore, in this study, the authors assessed whether microfiber improves the ductility of UHP-FRCC in two series of experiments. Wollastonite, which is a needle-shape mineral, is employed as a microfiber, and two different types of steel fibers are used as mesoand macrofibers. First, the enhanced toughness was evaluated in three-point bending tests on notched mortar beams. Second, the influence of wollastonite microfiber on the mechanical properties of the blended multi-scale fiber-reinforcement system was evaluated in uniaxial tension tests. Blends of macrofibers, mesofibers, and wollastonite microfibers exhibited strong reinforcement characteristics. The results indicate that the ductility of composites reinforced with wollastonite microfibers is highly dependent on the microfiber contents and type of fiber used and that blending of micro-, meso-, and macrofibers produces a highly ductile UHP-FRCC. Thus the material design concept based on the multi-scale fiber-reinforcement system proposed in this paper was shown to be effective in increasing the ductility of UHP-FRCC, even under uniaxial tension.
Novel cellulose-based composites based on nanofibrillated plant and bacterial cellulose: recent advances at the University of Aveiro – a review

Abstract The development of (nano)materials based on the renewable cellulose is a challenge. The present article provides a brief overview of the recent research efforts carried out at the CICECO Laboratory of the University of Aveiro on the development of novel composites based on nanofibrillated plant and bacterial cellulose embedded in natural and synthetic polymeric matrices such as poly(lactic acid), chitosan, starch, and pullulan. These materials have high potential for applications in packaging, paper coating, organic electronics, and biomedical products and devices.
Rapid Relief of Signs/Symptoms in Chronic Venous Microangiopathy With Pycnogenol®: A Prospective, Controlled Study

The aim of this study was to investigate the clinical efficacy of oral Pycnogenol® (Horphag Research Ltd, UK) in patients with severe chronic venous insufficiency. Patients with severe venous hypertension (chronic venous insufficiency, ankle swelling) and history of venous ulcerations were treated with Pycnogenol. Patients received oral Pycnogenol (50 mg capsules, 3 times daily for a total of 150 mg daily) for 8 weeks. A group of 21 patients was included in the treatment group and 18 equivalent patients were observed as controls (no treatment during the observation period). All 21 patients (age 53 years; range, 42-60 years; M:F=11:10) in the treatment group completed the 8-week study. Also the 18 controls completed the follow-up period. There were no drop-outs. The average ambulatory venous pressure was 59.3 (SD 7.2; range 50-68) with a refilling time shorter than 10 seconds (average 7.6; SD 3). There were no differences in ambulatory venous pressure or refilling time between the treatment and control patients. The duration of the disease—from the first signs/symptoms—was on average 5.7 years (SD 2.1). At 4 and 8 weeks, in all Pycnogenol-treated subjects, microcirculatory and clinical evaluations indicated a progressive decrease in skin flux, indicating an improvement in the level of microangiopathy; a significant decrease in capillary filtration; a significant improvement in the symptomatic score; and a reduction in edema. There were no visible effects in controls. In conclusion, this study confirms the fast clinical efficacy of Pycnogenol in patients with chronic venous insufficiency and venous microangiopathy. The study indicates the significant clinical role of Pycnogenol in the management, treatment and control of this common clinical problem. The treatment may be also useful to prevent ulcerations by controlling the level of venous microangiopathy.
Electromyography in sports and occupational settings : an update of its limits and possibilities

The detection of the electrical signal from human and animal muscle dates from long before L. Galvani who took credit for it. J. Swammerdam had already shown the Duke of Tuscany in 1658 the mechanics of muscular contraction. Even if 'electrology or localised e1ectrisation'the original terminology for electromyography (EMG)-contained the oldest biological scientific detection and measuring techniques, EMG remained a 'supporting'. measurement with limited discriminating use, except in conjunction with other methods. All this changed when EMG became a diagnostic tool for studies of muscle weakness, fatigue, pareses, paralysis, and nerve conduction velocities, lesions of the motor unit or for neurogenic and myogenic problems. In addition to the measurement qualities, the electrical signal could be induced as functional electrical stimulation (FES), which developed as a specific rehabilitation tool. Almost in parallel and within the expanding area of EMG, a speciality developed wherein the aim was to use EMG for the study of muscular function and coordination of muscles in different movements and postures. Kinesiological EMG and therewith surface EMG can be applied in studies of normal muscle function during selected movements and postures; muscle activity in complex sports; occupational and rehabilitation movements; isometric contraction with increasing tension up to the maximal voluntary contraction, evaluation of functional anatomical muscle activity (validation of classical anatomical functions); coordination and synchronization studies (kinematic chain); specificity and efficiency of training methods; fatigue; the relationship between EMG and force; the human-machine interaction; the influence of material on muscle activity, occupational loading in relation to lower back pain and joint kinematics. within these various applications the recording system (e.g. the signal detection, the volume conduction, signal amplification, impedance and frequency responses, the signal characteristics) and the dataprocessing system (e.g. rectification, linear envelope and normalization methods) go hand in hand with a critical appraisal of choices, limits and possibilities.