Do ozone and boric acid affect microleakage in class V composite restorations?

The aim of this in vitro study was to evaluate the effects of chlorhexidine gluconate (2%), sodium hypochloride (2.5%), ozone gas, and boric acid at different concentrations (1%, 3%, 5%, and 7%) on microleakage from composite restorations.

In a total of 80 extracted human canine teeth, a class V cavity was opened on the buccal surface and the samples were separated into eight groups. In the control group, no procedure was applied for cavity disinfection, then composite restoration (Z250, 3M) was made using single-stage, self-etch adhesive (Single Bond 3M). In the other groups, seven different disinfectants were used, then the cavity was restored. The teeth were split into two in the buccolingual direction, parallel to the long axes. Stain penetration was examined under stereomicroscope and scored. Examination with SEM was made on one sample from each group, selected at random. Statistical evaluations were made using Dunnett C Post Hoc Comparison and Kruskal–Wallis H tests.

In the occlusal region evaluation, the groups with the lowest level of leakage were the 3% and 5% boric acid groups, and the highest levels of microleakage were determined in the chlorhexidine group and the 1% boric acid group. In the gingival region, the lowest level of microleakage was in the 5% boric acid group and the highest levels were determined in the 1% and 7% boric acid groups.

Boric acid disinfectants used at suitable concentrations were not seen to create a risk in respect of microleakage.     

Systematic multiscale models to predict the compressive strength of self-compacting concretes modified with nanosilica at different curing ages

The evolution of nanotechnology brings materials with novel performance and during last year’s much attempt has been established to include nanoparticles especially nano-silica (NS) into the concrete to improve performance and develop concrete with enhanced characteristics. Generally, NS is incorporated into the self-compacting concrete (SCC) aiming to positively influence the fresh, mechanical, microstructure, and durability properties of the composite. The most important mechanical property for all types of concrete composites is compressive strength. Therefore, developing reliable models for predicting the compressive strength of SCC is crucial regarding saving time, energy, and cost-effectiveness. Moreover, it gives valuable information for scheduling the construction work and provides information about the correct time for removing the formwork. In this study, three different models including the linear relationship model (LR), nonlinear model (NLR), and multi-logistic model (MLR) were proposed to predict the compressive strength of SCC mixtures made with or without NS. In this regard, a comprehensive data set that consists of 450 samples were collected and analyzed to develop the models. In the modeling process, the most important variables affecting the compressive strength such as NS content, cement content, water to binder ratio, curing time from 1 to 180 days, superplasticizer content, fine aggregate content, and coarse aggregate content were considered as input variables. Various statistical assessments such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Scatter Index (SI), OBJ value, and the coefficient of determination (R²) were used to evaluate the performance of the proposed models. The results indicated that the MLR model performed better for forecasting the compression strength of SCC mixtures modified with NS compared to other models. The SI and OBJ values of the MLR model were 18.8% and 16.7% lower than the NLR model, indicating the superior performance of the MLR model. Moreover, the sensitivity analysis demonstrated that the curing time is the most affecting variable for forecasting the compressive strength of SCC modified with NS.

     

Highly active and stable CeO2 supported nickel-complex catalyst in hydrogen generation

Cerium oxide supported 5-Amino-2,4-dichlorophenol-3,5-ditertbutylsalisylaldimine-Nickel complex for the first time was used to produce H₂ from hydrolysis of sodium borohydride. Cerium oxide supported Nickel complex catalyzed hydrolysis system was studied depend on temperature, concentration of sodium hydroxide, amount of Cerium oxide supported Ni complex catalyst, concentration of Ni complex and concentration of sodium borohydride. Cerium oxide supported Ni(II) complex display highly effective catalytic activity in sodium borohydride hydrolysis reaction. The obtained Cerium oxide supported Ni(II) complex catalyst was characterized by using Fourier Transform Infrared Spectroscopy, Scanning Electron Microscope, Transmission Electron Microscope, Brunauer-Emmett-Teller Surface Area Analysis, X-Ray Diffraction Analysis techniques. The catalyst stability was tested, even the fifth recycle the catalytic activity was maintained at 100%. Additionally the proposed Cerium oxide supported-Ni (II) complex catalyzed sodium borohydride hydrolysis mechanism was determined carefully. The experimental results showed that Cerium oxide supported Ni (II) complex catalyst accelerate sodium borohydride hydrolysis with 43,392 and 19,630 mL H₂ g_cat^?1 min^?1 hydrogen production rates at 50 °C and 30 °C respectively and 20,587 kJ mol^?1 activation energy.     

Hardware architecture of the Protein Processing Associative Memory and the effects of dimensionality and quantisation on performance

The Protein Processor Associative Memory (PPAM) is a novel hardware architecture for a distributed, decentralised, robust and scalable, bidirectional, hetero-associative memory, that can adapt online to changes in the training data. The PPAM uses the location of data in memory to identify relationships and is therefore fundamentally different from traditional processing methods that tend to use arithmetic operations to perform computation. This paper presents the hardware architecture and details a sample digital logic implementation with an analysis of the implications of using existing techniques for such hardware architectures. It also presents the results of implementing the PPAM for a robotic application that involves learning the forward and inverse kinematics. The results show that, contrary to most other techniques, the PPAM benefits from higher dimensionality of data, and that quantisation intervals are crucial to the performance of the PPAM.     

Using Circular Conduits in Ozone Injection

Dissolved oxygen is the amount of oxygen dissolved in water corresponding to an important water quality parameter in rivers, streams, and lakes. Hydraulic structures can increase dissolved oxygen levels by creating turbulent conditions where small air bubbles are carried into the bulk of the flow. A gated conduit is a hydraulic structure that can be used efficiently in aeration and oxygen transfer. The subatmospheric pressure between the upstream and downstream of the gate is the reason for the air injection. Ozone is an unstable gas comprised of three oxygen atoms, and it can be used for water treatment. Ozone is thermodynamically unstable and spontaneously reverts back into oxygen. Ozone has been widely accepted as an effective disinfectant and a chemical oxidant. In this study a series of experiments was conducted to determine the ozone injection performance of circular conduits. Results showed that circular conduits are very effective for ozone injection.     

Structural Response of World Trade Center Buildings 1, 2 and 7 to Impact and Fire Damage

The National Institute of Standards and Technology (NIST) conducted an extensive investigation of the collapse of World Trade Center towers (WTC 1 and WTC 2) and the WTC 7 building. This paper describes the component, subsystem, and global analyses performed for the reconstruction of the structural response of WTC buildings 1, 2, and 7 to impact and fire damage. To illustrate the component and subsystem analyses, the approach taken for simulating the performance of concrete slabs and shear stud connectors in composite floors subject to fire conditions are presented, as well as steel floor framing connections for beams and girders. The development of the global models from the component and subsystem analyses is briefly described, including the sets of input data used to bound the probable conditions of impact and fire damage. The final analysis results that were used to develop the probable collapse hypotheses, and a comparison of the results against observed events, are presented for each building. A review of research activities focused on improving understanding of structural system response to multi-floor fires following the WTC disaster is also provided.     

Machining strategy development and parameter selection in 5-axis milling based on process simulations

Fused deposition modeling (FDM) is one of the most popular additive manufacturing technologies for fabricating prototypes with complex geometry and different materials. However, current commercial FDM machines have the limitations in process reliability and product quality. In order to overcome these limitations and increase the levels of machine intelligence and automation, machine conditions need to be monitored more closely as in closed-loop control systems. In this study, a new method for in situ monitoring of FDM machine conditions is proposed, where acoustic emission (AE) technique is applied. The proposed method allows for the identification of both normal and abnormal states of the machine conditions. The time-domain features of AE hits are used as the indicators. Support vector machines with the radial basis function kernel are applied for state identification. Experimental results show that this new method can potentially serve as a non-intrusive diagnostic and prognostic tool for FDM machine maintenance and process control.