Compositional analysis of biofilms formed by Staphylococcus aureus isolated from food sources

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb. 2016.00390

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.

Plastic-damage smeared crack model to simulate the behaviour of structures made by cement based materials

This work proposes a constitutive model to simulate nonlinear behaviour of cement based materials subjected to different loading paths. The model incorporates a multidirectional fixed smeared crack approach to simulate crack initiation and propagation, whereas the inelastic behaviour of material between cracks is treated by a numerical strategy that combines plasticity and damage theories. For capturing more realistically the shear stress transfer between the crack surfaces, a softening diagram is assumed for modelling the crack shear stress versus crack shear strain. The plastic damage model is based on the yield function, flow rule and evolution law for hardening variable, and includes an explicit isotropic damage law to simulate the stiffness degradation and the softening behaviour of cement based materials in compression. This model was implemented into the FEMIX computer program, and experimental tests at material scale were simulated to appraise the predictive performance of this constitutive model. The applicability of the model for simulating the behaviour of reinforced concrete shear wall panels submitted to biaxial loading conditions, and RC beams failing in shear is investigated.

Real-Time models to predict the use of vasopressors in monitored patients

The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.

A FEM-based model to study the behaviour of corroded RC beams shear repaired by NSM CFRP rods technique

This paper presents the main features of finite element FE numerical model developed using the computer code FEMIX to predict the near-surface mounted NSM carbon-fiber-reinforced polymer CFRP rods shear repair contribution to corroded reinforced concrete RC beams. In the RC beams shear repaired with NSM technique, the Carbon Fibre Reinforced Polymer (CFRP) rods are placed inside pre-cut grooves onto the concrete cover of the RC beam’s lateral faces and are bonded to the concrete with high epoxy adhesive. Experimental and 3D numerical modelling results are presented in this paper in terms of load-deflection curves, and failure modes for 4 short corroded beams: two corroded beams (A1CL3-B and A1CL3-SB) and two control beams (A1T-B and A1T-SB), the beams noted with B were let repaired in bending only with NSM CFRP rods while the ones noted with SB were repaired in both bending and shear with NSM technique. The corrosion of the tensile steel bars and its effect on the shear capacity of the RC beams was discussed. Results showed that the FE model was able to capture the main aspects of the experimental load-deflection curves of the RC beams, moreover it has presented the experimental failure modes and FE numerical modelling crack patterns and both gave similar results for non-shear repaired beams which failed in diagonal tension mode of failure and for shear-repaired beams which failed due to large flexural crack at the middle of the beams along with the concrete crushing, three dimensional crack patterns were produced for shear-repaired beams in order to investigate the splitting cracks occurred at the middle of the beams and near the support.

A FEM-based model to study the behaviour of corroded RC beams shear repaired by NSM CFRP rods technique

This paper presents the main features of finite element FE numerical model developed using the computer code FEMIX to predict the near-surface mounted NSM carbon-fiber-reinforced polymer CFRP rods shear repair contribution to corroded reinforced concrete RC beams. In the RC beams shear repaired with NSM technique, the Carbon Fibre Reinforced Polymer (CFRP) rods are placed inside pre-cut grooves onto the concrete cover of the RC beam’s lateral faces and are bonded to the concrete with high epoxy adhesive. Experimental and 3D numerical modelling results are presented in this paper in terms of load-deflection curves, failure modes and slip information of the tensile steel bars for 4 short corroded beams: two corroded beams (A1CL3-B and A1CL3-SB) and two control beams (A1T-B and A1T-SB), the beams noted with B were let repaired in bending only with NSM CFRP rods while the ones noted with SB were repaired in both bending and shear with NSM technique. The corrosion of the tensile steel bars and its effect on the shear capacity of the RC beams was discussed. Results showed that the FE model was able to capture the main aspects of the experimental load-deflection curves of the RC beams, moreover it has presented the experimental failure modes and FE numerical modelling crack patterns and both gave similar results for non-shear repaired beams which failed in diagonal tension mode of failure and for shear-repaired beams which failed due to large flexural crack at the middle of the beams along with the concrete crushing, three dimensional crack patterns were produced for shear-repaired beams in order to investigate the splitting cracks occurred at the middle of the beams and near the support.

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.

Pervasive business intelligence platform to improve the quality of decision process in primary and secondary education – A Portuguese case study

Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

Promoting sustainability as a strategy to mitigate the effects of economic downturn on the construction industry

During the recent years followed by the Global Financial Crisis (GFC), most of business and industries around the globe have been hardly hit to the limit that it still struggling to survive, suffering from the crisis financial consequences. For instance, in the construction industry; many construction projects have been suspended or totally cancelled. Nevertheless, among this dilemma, a call has been raised to use the sustainable practices to mitigate the effects of the GFC on construction industry. For the first look, it seems that there is contradiction since the sustainable solutions are often associated with an increase in the initial cost, undoubtedly, the sustainable practices have many advantages in both economic and environment aspects, however, the question which needs to be addressed here is, to what extent using such sustainable practices can mitigate the negative effects of the economic downturn on construction industry. Therefore, it is a challenging argument for using such sustainable construction from its economic perspective, however, this paper is aiming to present the economical benefits of sustainable practices in construction industry, and trying to clear the doubt of the high initial costs of the sustainable construction through studying the life cycle benefit of green building.

Hind limb ischemia in type 1 diabetic mice as useful tool to evaluate the neovascularization of tissue engineering constructs

Hind-limb ischemia has been used in type 1 diabetic mice to evaluate treatments for peripheral arterial disease or mechanisms of vascular impairment in diabetes [1]. Vascular deficiency is not only a pathophysiological condition, but also an obvious circumstance in tissue regeneration and in tissue engineering and regenerative medicine (TERM) strategies. We performed a pilot experiment of hind-limb ischemia in streptozotocin(STZ)-induced type 1 diabetic mice to hypothesise whether diabetes influences neovascularization induced by biomaterials. The dependent variables included blood flow and markers of arteriogenesis and angiogenesis. Type 1 diabetes was induced in 8-week-old C57BL/6 mice by an i.p. injection of STZ (50 mg/kg daily for 5 days). Hind-limb ischemia was created under deep anaesthesia and the left femoral artery and vein were isolated, ligated, and excised. The contralateral hind limb served as an internal control within each mouse. Non-diabetic ischaemic mice were used as experiment controls. At the hind-limb ischemia surgical procedure, different types of biomaterials were placed in the blood vessels gap. Blood flow was estimated by Laser Doppler perfusion imager, right after surgery and then weekly. After 28 days of implantation, surrounding muscle was excised and evaluated by histological analysis for arteriogenesis and angiogenesis. The results showed that implanted biomaterials were promote faster restoration of blood flow in the ischemic limbs and improved neovascularization in the diabetic mice. Therefore, we herein demonstrate that the combined model of hind-limb ischemia in type 1 diabetes mice is suitable to evaluate the neovascularization potential of biomaterials and eventually tissue engineering constructs.  

Layer-by-layer technique to developing functional nanolaminate films with antifungal activity

The layer-by-layer (LbL) deposition method was used to build up alternating layers (five) of different polyelectrolyte solutions (alginate, zein-carvacrol nanocapsules, chitosan and chitosan-carvacrol emulsions) on an aminolysed/charged polyethylene terephthalate (A/C PET) film. These nanolaminated films were characterised by contact angle measurements and through the determination of water vapour (WVTR) and oxygen (O2TR) transmission rates. The effect of active nanolaminated films against the Alternaria sp. and Rhizopus stolonifer was also evaluated. This procedure allowed developing optically transparent nanolaminated films with tuneable water vapour and gas properties and antifungal activity. The water and oxygen transmission rate values for the multilayer films were lower than those previously reported for the neat alginate or chitosan films. The presence of carvacrol and zein nanocapsules significantly decreased the water transmission rate (up to 40 %) of the nanolaminated films. However, the O2TR behaved differently and was only improved (up to 45 %) when carvacrol was encapsulated, i.e. nanolaminated films prepared by alternating alginate with nanocapsules of zein-carvacrol layers showed better oxygen barrier properties than those prepared as an emulsion of chitosan and carvacrol. These films containing zein-carvacrol nanocapsules also showed the highest antifungal activity (30 %), which did not significantly differ from those obtained with the highest amount of carvacrol, probably due to the controlled release of the active agent (carvacrol) from the zein-carvacrol nanocapsules. Thus, this work shows that nanolaminated films prepared with alternating layers of alginate and zein-carvacrol nanocapsules can be considered to improve the shelf-life of foodstuffs.