Ethanol combined with heparin as a locking solution for the prevention of catheter related blood stream infections in hemodialysis patients: A prospective randomized study

Introduction: Ethanol lock solution has been mainly administered in paediatric and home parenteral nutrition patients in order to prevent catheter related blood stream infections (CRBSI). Its utility in hemodialysis (HD) patients with non‐tunneled‐uncuffed catheter (NTC) has been poorly explored. Methods: We conducted a prospective randomized study in chronic HD patients requiring a newly inserted NTC‐while awaiting for the maturation of an already established arteriovenous fistula (AVF) or arteriovenous graft (AVG) or tunneled‐cuffed catheter insertion. Patients were randomized in two groups: Group A, where the lock solution was ethanol 70% + unfractionated heparin 2000 U/mL and group B, that received only unfractionated heparin 2000 U/mL. Primary end point was CRBSIs whereas exit site infections, thrombotic and bleeding episodes were the secondary end points. Findings: One hundred three HD patients were enrolled in the study (group A, n = 52; group B, n = 51). The median number of catheter days was 32 for group A (range: 23–39) and 34 (range: 27–40) for group B with no statistically significant difference between the two groups. Group A (ethanol + heparin) demonstrated 4/52 episodes (7.69%) of CRBSI whereas Group B (heparin) 11/51 episodes (21.57%) (P = 0.04). CRBSI rates per 1000 catheter days were 2.53/1000 catheter days for group A and 6.7/1000 catheter days for group B (P = 0.04). Mean cumulative infection‐free catheter survival in the ethanol group did not differ significantly compared to the heparin group (log‐rank test = 2.99, P = 0.08). Thrombotic episodes did not differ between the two groups. Discussion: Locking of NTCs in HD patients with ethanol 70% + unfractionated heparin reduces CRBSI rates without increasing the thrombotic episodes.     

Modeling and experimental validation of a new type of tuned liquid damper

This paper introduces a new type of tuned liquid damper (TLD) having a relatively simple, easy-to-model behavior and high effectiveness in controlling structural vibrations. It consists of a traditional TLD with addition of a floating roof. Since the roof is much stiffer than water, it prevents wave breaking, hence making the response linear even at large amplitudes. The roof also facilitates the incorporation of supplemental devices with which the level of damping of the liquid vibration can be substantially augmented. This newly proposed TLD, denoted as tuned liquid damper with floating roof (TLD-FR), maintains the traditional advantages of TLDs (low cost, easy installation and tuning), but its numerical characterization is much simpler because the floating roof suppresses higher sloshing vibration modes, resulting in a system that can be represented by a single-degree-of-freedom model. An efficient numerical scheme, where the dynamic behavior of the TLD-FR is expressed as a second-order lineal system of equations, is discussed and validated by scaled experimental tests. The equations of motion of a structure equipped with a TLD-FR are then derived and manipulated to offer a unifying representation dependent upon only four model characteristics of the TLD-FR: The first three (mass, frequency and damping ratios) are common for all type of mass dampers, whereas the final one, termed efficiency index, is related to a similar parameter used to characterize liquid column dampers. Through this approach, the behavior of the proposed TLD-FR can be easily correlated with the behavior of other well-known linear mass damper devices. The relationship between these parameters and the geometrical characteristics of the TLD-FR is also examined. Finally, the identification of the optimal characteristic of the TLD-FR (natural frequency and damping) under stationary stochastic excitation is discussed.     

A Unified Framework for Providing Recommendations in Social Tagging Systems Based on Ternary Semantic Analysis

Social Tagging is the process by which many users add metadata in the form of keywords, to annotate and categorize items (songs, pictures, Web links, products, etc.). Social tagging systems (STSs) can provide three different types of recommendations: They can recommend 1) tags to users, based on what tags other users have used for the same items, 2) items to users, based on tags they have in common with other similar users, and 3) users with common social interest, based on common tags on similar items. However, users may have different interests for an item, and items may have multiple facets. In contrast to the current recommendation algorithms, our approach develops a unified framework to model the three types of entities that exist in a social tagging system: users, items, and tags. These data are modeled by a 3-order tensor, on which multiway latent semantic analysis and dimensionality reduction is performed using both the Higher Order Singular Value Decomposition (HOSVD) method and the Kernel-SVD smoothing technique. We perform experimental comparison of the proposed method against state-of-the-art recommendation algorithms with two real data sets (Last.fm and BibSonomy). Our results show significant improvements in terms of effectiveness measured through recall/precision.     

Phone duration modeling: overview of techniques and performance optimization via feature selection in the context of emotional speech

Accurate modeling of prosody is prerequisite for the production of synthetic speech of high quality. Phone duration, as one of the key prosodic parameters, plays an important role for the generation of emotional synthetic speech with natural sounding. In the present work we offer an overview of various phone duration modeling techniques, and consequently evaluate ten models, based on decision trees, linear regression, lazy-learning algorithms and meta-learning algorithms, which over the past decades have been successfully used in various modeling tasks. Furthermore, we study the opportunity for performance optimization by applying two feature selection techniques, the RReliefF and the Correlation-based Feature Selection, on a large set of numerical and nominal linguistic features extracted from text, such as: phonetic, phonologic and morphosyntactic ones, which have been reported successful on the phone and syllable duration modeling task. We investigate the practical usefulness of these phone duration modeling techniques on a Modern Greek emotional speech database, which consists of five categories of emotional speech: anger, fear, joy, neutral, sadness. The experimental results demonstrated that feature selection significantly improves the accuracy of phone duration prediction regardless of the type of machine learning algorithm used for phone duration modeling. Specifically, in four out of the five categories of emotional speech, feature selection contributed to the improvement of the phone duration modeling, when compared to the case without feature selection. The M5p trees based phone duration model was observed to achieve the best phone duration prediction accuracy in terms of RMSE and MAE.     

Modeling and optimization of a 1 kWe HT-PEMFC-based micro-CHP residential system

A high temperature-proton exchange membrane (HT-PEMFC)-based micro-combined-heat-and-power (CHP) residential system is designed and optimized, using a genetic algorithm (GA) optimization strategy. The proposed system consists of a fuel cell stack, steam methane reformer (SMR) reactor, water gas shift (WGS) reactor, heat exchangers, and other balance-of-plant (BOP) components. The objective function of the single-objective optimization strategy is the net electrical efficiency of the micro-CHP system. The implemented optimization procedure attempts to maximize the objective function by variation of nine decision variables. The value of the objective function for the optimum design configuration is significantly higher than the initial one, with a 20.7% increase.     

Modeling of NC-AFM Imaging of Alkanethiols on the Au (111) Surface

We investigate the mechanisms of contrast formation in NC-AFM imaging of self-assembled monolayers of alkanethiols on the Au (111) surface. Comparing the potential models with implicit and explicit electrostatics, we demonstrate that, similar to the imaging of polar solid surfaces, the electrostatic interaction plays the central role in contrast formation. Careful comparison of several tip models showed that the model of a clean SiO₂ tip gives the closest agreement with the experimental data.     

A discrete methodology for controlling the sign of curvature and torsion for NURBS

This paper develops a discrete methodology for approximating the so-called convex domain of a NURBS curve, namely the domain in the ambient space, where a user-specified control point is free to move so that the curvature and torsion retains its sign along the NURBS parametric domain of definition. The methodology provides a monotonic sequence of convex polyhedra, converging from the interior to the convex domain. If the latter is non-empty, a simple algorithm is proposed, that yields a sequence of polytopes converging uniformly to the restriction of the convex domain to any user-specified bounding box. The algorithm is illustrated for a pair of planar and a spatial Bézier configuration.     

Initial use of 1-hydroxybenzotriazole in the chemistry of group 12 metals: An 1D zinc(II) coordination polymer and a mononuclear cadmium(II) complex containing the deprotonated ligand in a novel monodentate ligation mode

The chemistry of 1-hydroxybenzotriazole (btaOH) with the group 12 metal ions Zn(II) and Cd(II) resulted in the 1D coordination polymer [Zn(btaO)₂]_n (1) and the mononuclear complex [Cd(btaO)₂(H₂O)₄] · 3H₂O (2 · 3H₂O), respectively. Polymer 1 forms double-stranded chains which are further supported by weak C–H?O hydrogen bonds resulting in a pcu (primitive cubic) rod packing. The mononuclear complexes of 2 form undulating hydrogen bonded layers while the lattice water molecules form 1D hydrogen bonded tapes, comprising 4- and 6-membered rings, within the layers and bridge them to the third dimension. The thermal and optical properties of both compounds are presented. IR data are discussed in terms of the chemical composition of the compounds and the coordination mode of btaO^?.     

Impact of configuration errors on DNS robustness

During the past twenty years the Domain Name System (DNS) has sustained phenomenal growth while maintaining satisfactory user-level performance. However, the original design focused mainly on system robustness against physical failures, and neglected the impact of operational errors such as mis-configurations. Our measurement efforts have revealed a number of mis-configurations in DNS today: delegation inconsistency, lame delegation, diminished server redundancy, and cyclic zone dependency. Zones with configuration errors suffer from reduced availability and increased query delays up to an order of magnitude. The original DNS design assumed that redundant DNS servers fail independently, but our measurements show that operational choices create dependencies between servers. We found that, left unchecked, DNS configuration errors are widespread. Specifically, lame delegation affects 15% of the measured DNS zones, delegation inconsistency appears in 21% of the zones, diminished server redundancy is even more prevalent, and cyclic dependency appears in 2% of the zones. We also noted that the degrees of mis-configuration vary from zone to zone, with the most popular zones having the lowest percentage of errors. Our results indicate that DNS, as well as any other truly robust large-scale system, must include systematic checking mechanisms to cope with operational errors.