bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nutritional screening, assessment and implementation strategies for adults in an Australian acute tertiary hospital: a best practice implementation report
Authors: Smith Louise , Chapman Amanda , Flowers Kelli , Wright Kylie , Chen Tanghua , O’Connor Charmaine , Astorga Cecilia , Francis Nevenka , Vigh Gia , Wainwright Craig 
Published: January 2018

ABSTRACTObjective:The project aimed to improve the effectiveness of nutritional screening and assessment practices through clinical audits and the implementation of evidence-based practice recommendations.Introduction:In the absence of optimal nutrition, health may decline and potentially manifest as adverse health outcomes. In a hospitalized person, poor nutrition may adversely impact on the person's outcome. If the nutritional status can be ascertained, nutritional needs can be addressed and potential risks minimized.The overall purpose of this project was to review and monitor staff compliance with nutritional screening and assessment best practice recommendations ensuring there is timely, relevant and structured nutritional therapeutic practices that support safe, compassionate and person-centered care in adults in a tertiary hospital in South Western Sydney, Australia, in the acute care setting.Methods:A baseline retrospective chart audit was conducted and measured against 10 best practice criteria in relation to nutritional screening and assessment practices. This was followed by a facilitated multidisciplinary focus group to identify targeted strategies, implementation of targeted strategies, and a post strategy implementation chart audit.The project utilized the Joanna Briggs Institute Practical Application of Clinical Evidence System (JBI PACES) and Getting Research into Practice (GRIP) tool, including evidence from other available supporting literature, for promoting change in healthcare practice.Results:The baseline audit revealed deficits between current practice and best practice across the 10 criteria. Barriers for implementation of nutritional screening and assessment best practice criteria were identified by the focus group and an education strategy was implemented. There were improved outcomes across all best practice criteria in the follow-up audit.Conclusions:The baseline audit revealed gaps between current practice and best practice. Through the implementation of a targeted education program and resource package, outcomes improved in the follow up audit. The findings indicated that engagement from multidisciplinary team members and consumers was effective in developing tailored education that improved knowledge of best practice. This was demonstrated by an increase in the percentage of compliance across the 10 criteria, although leaving room for more improvement. A policy has been developed for implementation and future audits are planned to measure whether improved practices have been sustained.
Falls assessment and interventions among older patients in two medical and one surgical hospital wards in Spain: a best practice implementation project
Authors: Albornos-Muñoz Laura , Melián-Correa Esther , Acosta-Arrocha Amanda , Gallo-Blanco Carmen , Béjar-Bacas Felicidad , Alonso-Poncelas Emma , Serra-Estrada Montserrat , González-María Esther , Moreno-Casbas María Teresa 
Published: January 2018

ABSTRACT

Objective:
The current project aimed to improve fall prevention and management through clinical audits and the implementation of a quality-improvement cycle at the local level.

Introduction:
Falls are one of the most common adverse events reported in hospitals; evidence-based fall prevention interventions aim to reduce the number of people who fall.

Methods:
A one-year clinical audit was conducted using a pre-post implementation audit method, namely the Joanna Briggs Institute's (JBI) Practical Application of Clinical Evidence System and the getting research into practice audit and feedback tool. Two medical wards and a surgical ward in a Spanish hospital participated. The subjects were evaluated at baseline and at a follow-up at six months after key strategies had been implemented.

Results:
Compliance rates for the evidence-based criteria were low in the baseline audit. Five barriers were identified in relation to fall assessment and management and, based on getting research into practice, strategies were designed, developed and implemented to overcome these barriers. After implementation, most of the fall-risk-assessment criteria showed an overall improvement, but there was no effect on care plan recording. Awareness of the assessment and management of fall risks were increased among professionals and patients on all three study wards.

Conclusions:
The current project may improve compliance with regard to promoting evidence-based fall prevention and management interventions. Further audits are necessary to evaluate any improvements achieved, in particular, care plans.
Retracted: “Residential Energy Efficiency Improvement Using Solar Heating of Water and Air: A Computational Study” [ASME 2017 International Mechanical Engineering Congress and Exposition, Volume 6: Energy, Tampa, Florida, USA, November 3–9, 2017, Conference Sponsors: ASME, ISBN: 978-0-7918-5841-7, Copyright © 2017 by ASME. Paper No. IMECE2017-70041, pp. V006T08A037; 7 pages; doi: 10.1115/IMECE2017-70041]
Authors: ASME  
Published: January 2018

Abstract
The above referenced paper has been removed from publication. (March 10, 2020)
Copyright © 2020 by ASME
Development of Artificial Neural Network Based Design Tool for Aircraft Engine Bolted Flange Connection Subject to Combined Axial and Moment Load
Authors: Sanli T. Volkan , Gürses Ercan , Çöker Demirkan , Kayran Altan 
Published: January 2018

Bolted flange connections are one of the most commonly used joint types in aircraft structures. Typically, bolted flange connections are used in aircraft engines. The main duty of a bolted flange connection in an aircraft engine is to serve as the load transfer interface from one part of the engine to the other part of the engine. In aircraft structures, weight is a very critical parameter which has to be minimized while having the required margin of safety for the structural integrity. Therefore, optimum design of the bolted flange connection is crucial to minimize the weight. In the preliminary design stage of the bolted flange connection, many repetitive analyses have to be made in order to decide on the optimum design parameters of the bolted flange connection. Two main methods used for analyzing bolted flange connections are the hand calculations based on simplified approaches and finite element analysis (FEA). While hand calculations lack achieving optimum weight as they tend to give over safe results, finite element analysis is computationally expensive because of the non-linear feature of the problem due to contact definitions between the mating parts.
In this study, a fast but very accurate design tool based on artificial neural network (ANN) is developed for the cylindrical bolted flange connection of a typical aircraft engine under combined axial and bending moment load. ANN uses the FEA database generated by taking permutations of the parametric design variables of the bolted flange connection. The selected parameters are the number of bolts, the bolt size, the flange thickness, the web thickness, the preload level of the bolt and the external combined loads of bending moment and axial force. The bolt reaction force and the average flange stress are taken as the output variables and the results of 12000 different finite element analyses are gathered to form a database for the training of the ANN. Results of the trained ANN are then compared with the finite element analysis results and it is shown that an excellent agreement exists between the ANN and the non-linear finite element analysis results within the training limits of the artificial neural network. We believe that the ANN established can be a very robust and accurate approximate model replacing the non-linear finite element solver in the optimization of the bolted flange connection of the aircraft engine to achieve weight reduction.
Anisotropy and Failure in Octahedral Lattice Structure Parts Fabricated Using the FDM Technology
Authors: Calise Gian J. , Saigal Anil 
Published: January 2018

Mechanical metamaterials are man-made materials in which the mechanical properties are mainly defined by their structures instead of the properties of each component. Periodic cellular structures consisting of honeycomb, tetrahedral, 3D Kagome and pyramidal truss arrangement of webs or struts have recently attracted a lot of attention since they have a broad range of applications including structural components, energy absorption, heat exchangers, catalyst support, filters and biomaterials. In addition, lattice structures such as the octahedral are being investigated since they are structurally more efficient than foams of a similar density made from the same material, and the ease with which these structures can now be produced using 3D printing and additive manufacturing.
This research investigates the mechanical behavior and anisotropy in octahedral lattice structures of two different relative densities fabricated out of Acrylonitrile butadiene styrene (ABS) using Stratasys FDM 360mc and Dimension sst 1200es 3D printers. The machines were used to print octahedral lattice structured parts with struts 1.00 mm in diameter followed by parts with struts 2.6 mm in diameter and tested in compression in three mutually perpendicular directions. The compressive stress-strain behavior of the lattice structures observed is typical of cellular structures which include a region of nominally elastic response, yielding, and plastic strain hardening to a peak in strength, followed by a drop in flow stress. It was found that not only is the stiffness and strength of the as fabricated parts anisotropic but they, in addition to failure, are also a function of the relative density/strut diameter of the structure.
Intelligent Tire Based Pressure Monitoring Algorithm
Authors: Khaleghian Seyedmeysam , Taheri Saied 
Published: January 2018

Intelligent tire is a relatively new technology that provides useful tire-road contact information by directly monitoring the interaction between the tire and the road. Different types of sensors are attached to the tire inner-liner for this purpose; the sensor data then will be used to estimate the tire-road contact parameters as well as to monitor the tire conditions.
In this study, a tri-axial accelerometer was used and a two-steps intelligent tire based pressure monitoring algorithm was developed in this study. First, the angular velocity of the wheel was estimated based on the parameters extracted from the acceleration components through a trained neural network. Then the estimated wheel angular velocity from the first step was used along with the acceleration components to estimate the power of radial acceleration. The estimated power was compared to the actual one and the tire pressure condition was judged to be “normal” or “low”. To train the neural networks, the experimental data collected using an instrumented vehicle was used. A VW Jetta 2003 was used for this purpose and instrumented with appropriate sensors; intelligent tires, steering wheel sensor to measure the steering angle, steering velocity and steering torque, encoders to measure the angular speed of the wheels and an Inertial Measurement Unit (IMU) to measure the vehicle linear and angular acceleration.
Another set of experimental data with different tire pressures and different vehicle velocity was then used to validate the algorithm; good agreements were observed between the estimated tire pressures and the actual ones.
Data Flow and Communication Framework Supporting Digital Twin for Geometry Assurance
Authors: Bohlin Robert , Hagmar Jonas , Bengtsson Kristofer , Lindkvist Lars , Carlson Johan S. , Söderberg Rikard 
Published: January 2018

Faster optimization algorithms, increased computer power and amount of available data, can leverage the area of simulation towards real-time control and optimization of products and production systems. This concept — often referred to as Digital Twin — enables real-time geometry assurance and allows moving from mass production to more individualized production.
To master the challenges of a Digital Twin for Geometry Assurance the project Smart Assembly 4.0 gathers Swedish researchers within product development, automation, virtual manufacturing, control theory, data analysis and machine learning. The vision of Smart Assembly 4.0 is the autonomous, self-optimizing robotized assembly factory, which maximizes quality and throughput, while keeping flexibility and reducing cost, by a sensing, thinking and acting strategy. The concept is based on active part matching and self-adjusting equipment which improves geometric quality without tightening the tolerances of incoming parts. The goal is to assemble products with higher quality than the incoming parts. The concept utilizes information about individual parts to be joined (sensing), selects the best combination of parts (thinking) and adjust locator positions, clamps, weld/rivet positions and sequences (acting).
The project is ongoing, and this paper specifies and highlights the infrastructure, components and data flows necessary in the Digital Twin in order to realize Smart Assembly 4.0. The framework is generic, but the paper focuses on a spot weld station where two robots join two sheet metal parts in an adjustable fixture.
MicroSurface Texturing for a Minimum Coefficient of Friction
Authors: Rashwan Ola H. , Stoilov Vesselin 
Published: January 2018

In recent years, micro surface texturing for friction and adhesion control has gained momentum in a wide range of applications, such as MEMS devices, punches, and tools used metal forming processes, and injection molding machines.
In this study, air hardened tool steel, A2, with micro hexagonal dimples of different sizes and densities but constant depth, have been modeled and tested under dry sliding contact. Three-dimensional finite element models depict sliding dry contact between a rigid indenter and elastic-plastic textured surfaces are simulated. Coefficients of friction have been determined and compared for different texturing sizes and densities. In addition, these hexagonal patterns were fabricated on tool steel (A2) samples using photolithography. Coefficients of friction were experimentally measured using micro scratch tribometer. Both simulation and experimental results show there is a strong correlation between micro-texturing parameters and coefficient of friction. The results demonstrate that under dry sliding contact, coefficient of friction can be controlled through optimization of micro texturing parameters, specifically the spatial texture density (D/L) which is equal to the ratio of the size of the dimple (D) to the distance between the centers of two consecutive dimples (L). A minimum coefficient of friction exits at values of spatial texture densities (D/L) that range between 0.25 and 0.5 for this specific material.
Design Optimisation of Composite Overwrapped Pressure Vessel Through Finite Element Analysis
Authors: Alam Shah , Divekar Abhijeet 
Published: January 2018

COPVs are currently used at NASA to contain high-pressure fluids in propulsion, science experiments and life support applications. These COPVs have a significant weight advantage over all-metal vessels; but, as compared to all-metal vessels, COPVs require unique design, manufacturing, and test requirements. The most significant difference from metal pressure vessel designs is that COPVs involve a much more complex mechanical understanding due to the interplay between the composite overwrap and the inner liner.
Often only limited analysis is performed to obtain an initial design, and then the design is refined through number of “build and burst” iterations. However, the cost in material and resources to fabricate multiple test specimens is extremely prohibitive. To avoid these high cost and time for build and burst iterations, FEA is often employed in an attempt to reduce the number of iterations required. FEA process becomes more of a design confirmation effort rather than a design iteration effort. In this research, we aimed to establish a detailed design optimization of a complete COPV through Finite Element simulation.
High Performance Buildings: The Impact of Building Orientation on HVAC System Loads
Authors: Shah Rushang B. , Goudarzi Navid 
Published: January 2018

Energy demand growth and depletion of conventional energy resources in recent years have led to exploring alternative energy resources and further concentration on improving energy efficiency of segments with higher energy consumption. Building energy demand is among the main areas of concern with a 40% average of total energy consumption in the US energy market. Within building energy demand approximately, the Heating, Ventilation and Air Conditioning (HVAC) system, lighting system, has the largest energy consumption share compared to other systems such as electronics systems, water-heating-cooking, and other systems. This implies that small improvements in HVAC system loads will result in significant energy savings. Novel cost-effective solutions should be developed to integrate and optimize all the essential high-performance building attributes, especially energy efficiency and occupant productivity. Employing comprehensive building energy analysis (BEA) simulation tools are among the cheapest, yet are the cost-effective approaches in improving building energy performance. This paper follows the energy saving practice using existing BEA simulation tools with a focus on two major aspects that can contribute to building thermal loads: building orientation and integrating renewable energy. The results show the significant impact of building orientation for developing energy efficiency solutions with focus on integrating renewable energy technologies within high performance buildings.
This work provides a basis for the follow on phases of this research to develop smart energy saving solutions using current BEA simulation platforms. Such adds-on features enable users to improve building energy saving by determining building design features and integrating renewable energy solutions based on identified optimal building orientations.
A Framework to Bridge Teachers, Student’s Affective State, and Improve Academic Performance
Authors: Calado Jorge , Luís-Ferreira Fernando , Sarraipa Joao , Jardim-Goncalves Ricardo 
Published: January 2018

Some of the biggest problems tackling Higher Education Institutions (HEI) are student’s drop-out and academic disengagement. Physical or psychological disabilities, social-economic or academic marginalization, and emotional and affective problems, are some of the factors that can lead to it.
This problematic is worsened by the shortage of educational resources that can bridge the communication gap between the faculty staff and the affective needs of these students.
In this paper, we present a framework capable of collecting analytic data, from an array of emotions, affects and behaviours, acquired either by human observations, like a teacher in a classroom or a psychologist, or by electronic sensors and automatic analysis software, such as eye tracking devices, emotion detection through automatic facial expression recognition software, among others.
This framework compiles the gathered data in an ontology, and will be able to extract patterns outliers via machine learning, enabling the profiling of the students in critical situations, such as disengagement, attention deficit, drop-out, and other sociological issues, setting real time alerts when these profiles are detected.
The goal is that, by providing insightful real time cognitive data and allowing the profiling of the student’s problems, a faster personalized response to help the student is enabled, allowing academic performance improvements.
A Novel Inhibitor of the LolCDE ABC Transporter Essential for Lipoprotein Trafficking in Gram-Negative Bacteria
Authors: Nickerson Nicholas N. , Jao Christine C. , Xu Yiming , Quinn John , Skippington Elizabeth , Alexander Mary Kate , Miu Anh , Skelton Nicholas , Hankins Jessica V. , Lopez Michael S. , Koth Christopher M. , Rutherford Steven , Nishiyama Mireille 
Published: January 2018

ABSTRACT

The outer membrane is an essential structural component of Gram-negative bacteria that is composed of lipoproteins, lipopolysaccharides, phospholipids, and integral β-barrel membrane proteins. A dedicated machinery, called the Lol system, ensures proper trafficking of lipoproteins from the inner to the outer membrane. The LolCDE ABC transporter is the inner membrane component, which is essential for bacterial viability. Here, we report a novel pyrrolopyrimidinedione compound, G0507, which was identified in a phenotypic screen for inhibitors of
Escherichia coli
growth followed by selection of compounds that induced the extracytoplasmic σ
E
stress response. Mutations in
lolC
,
lolD
, and
lolE
conferred resistance to G0507, suggesting LolCDE as its molecular target. Treatment of
E. coli
cells with G0507 resulted in accumulation of fully processed Lpp, an outer membrane lipoprotein, in the inner membrane. Using purified protein complexes, we found that G0507 binds to LolCDE and stimulates its ATPase activity. G0507 still binds to LolCDE harboring a Q258K substitution in LolC (LolC
Q258K
), which confers high-level resistance to G0507
in vivo
but no longer stimulates ATPase activity. Our work demonstrates that G0507 has significant promise as a chemical probe to dissect lipoprotein trafficking in Gram-negative bacteria.
Novel Two-Component System of Streptococcus sanguinis Affecting Functions Associated with Viability in Saliva and Biofilm Formation
Authors: Camargo Tarsila M. , Stipp Rafael N. , Alves Lívia A. , Harth-Chu Erika N. , Höfling José F. , Mattos-Graner Renata O. 
Published: January 2018

ABSTRACT

Streptococcus sanguinis
is a pioneer species of teeth and a common opportunistic pathogen of infective endocarditis. In this study, we identified a two-component system,
S. sanguinis
SptRS (SptRS

Ss

), affecting
S. sanguinis
survival in saliva and biofilm formation. Isogenic mutants of

sptR
Ss

(SKsptR) and

sptS
Ss

(SKsptS) showed reduced cell counts in
ex vivo
assays of viability in saliva compared to those of parent strain SK36 and complemented mutants. Reduced counts of the mutants in saliva were associated with reduced growth rates in nutrient-poor medium (RPMI) and increased susceptibility to the deposition of C3b and the membrane attach complex (MAC) of the complement system, a defense component of saliva and serum. Conversely,

sptR
Ss

and

sptS
Ss

mutants showed increased biofilm formation associated with higher levels of production of H
2
O
2
and extracellular DNA. Reverse transcription-quantitative PCR (RT-qPCR) comparisons of strains indicated a global role of SptRS

Ss

in repressing genes for H
2
O
2
production (2.5- to 15-fold upregulation of
spxB
,
spxR
,
vicR
,
tpk
, and
ackA
in

sptR
Ss

and

sptS
Ss

mutants), biofilm formation, and/or evasion of host immunity (2.1- to 11.4-fold upregulation of
srtA
,
pcsB
,
cwdP
,
iga
, and
nt5e
). Compatible with the homology of SptR

Ss

with AraC-type regulators, duplicate to multiple conserved repeats were identified in 1,000-bp regulatory regions of downstream genes, suggesting that SptR

Ss

regulates transcription by DNA looping. Significant transcriptional changes in the regulatory genes
vicR
,
spxR
,
comE
,
comX
, and
mecA
in the

sptR
Ss

and

sptS
Ss

mutants further indicated that SptRS

Ss

is part of a regulatory network that coordinates cell wall homeostasis, H
2
O
2
production, and competence. This study reveals that SptRS

Ss

is involved in the regulation of crucial functions for
S. sanguinis
persistence in the oral cavity.