The eco-friendly advantages of using glass powder and feldspar emphasize the benefits of utilizing these materials in the concrete industry. The current study aims to investigate the mechanical ...properties, thermal durability, and chloride penetration resistance of Ground Granulated Blast-furnace Slag (GGBFS) based geopolymer mortars containing Glass Powder (GP), feldspar, and Metakaolin (MK) under both standard and accelerated curing conditions. The GP, feldspar, and MK were utilized individually and in combination as replacements for GGBFS at the substitution rates of 10–25%. Twelve mix designs were generally considered in two series: without MK and with MK. The specimens were cured under two different conditions and then subjected to compressive strength tests at 7 and 28 days and flexural strength tests at 28 days. Each mixture was assessed for electrical resistivity and water absorption. For thermal durability, residual compressive strength was investigated after exposure to temperatures ranging from 100 to 600°C. Microstructure evaluation was also conducted using Scanning Electron Microscope (SEM) images. The results indicated that, by substituting GGBFS with the optimal proportion of feldspar and GP, a notable enhancement in thermal durability and chloride penetration resistance is attainable.
•The effects of Glass powder, Feldspar, and Metakaolin as partial substitutes in geopolymer mortars are investigated.•The influences of curing conditions on geopolymer mortars are assessed.•The optimum GP, Feldspar, and MK content for thermal durability and chloride penetration resistance was proposed.•Accelerated curing generally improved the mechanical properties and thermal durability of mixes.•Microstructural analysis in geopolymer mortars before and after exposure to elevated temperature was investigated.
In the current research, for the first time, Nano-scale finger gate vacuum channel field emission transistor (FGVFET) scaling down and its limitations considering electrical characteristics are ...studied. The FGVFET with different cathode electrode materials, channel dimensions, and finger widths is considered and the impacts of these structural and physical changes on the key indicators of the device are assessed to achieve a comprehensive design guideline. The sensitivity analysis reveals that the channel height modification by changing gate-anode oxide and cathode-gate oxide thicknesses can be assumed as the most significant design factor in the determination of ON-OFF-state currents. The results indicate that the gate leakage current as a salient parameter in device performance is dependent on the cathode material, channel depth, and height. Furthermore, investigating cutoff frequency as the prominent factor in high-speed applications indicates that cathode-gate oxide thickness may fundamentally modify this factor.
•A novel approach to the periodic train crew scheduling problem is introduced.•Crew schedule construction and crew schedule generation techniques are presented.•The problem is transformed into a ...single-period problem using “frames”.•The model is solved with and advanced, accelerated column generation technique.•The approach is suitable for parallel computing implementations.
We present an alternative approach to the problem of periodic crew scheduling. We introduce the concept of frames which leads us to a modeling approach which suits well the current practice of the majority of European railway operators. It results in a model facilitating column generation techniques resulting in a Dantzig-Wolfe type decomposition, and thus suitable for a parallel implementation in a high-performance computing environment. We exploit the properties of network flow models to avoid several additional integer constraints. We compare two approaches to solve the problem. The first approach consists of solving the original problem by single model. The second approach is our step-by-step column generation. The comparison is based on our implementation which we describe in detail along with its application to certain benchmark instances. The benchmarks originate in real or close-to-realistic problems from railway systems in Slovakia and Hungary. The case studies demonstrate that our model is well-suited for real-life applications.
Abstract
Ionic liquids (ILs) have emerged as suitable options for gas storage applications over the past decade. Consequently, accurate prediction of gas solubility in ILs is crucial for their ...application in the industry. In this study, four intelligent techniques including Extreme Learning Machine (ELM), Deep Belief Network (DBN), Multivariate Adaptive Regression Splines (MARS), and Boosting-Support Vector Regression (Boost-SVR) have been proposed to estimate the solubility of some gaseous hydrocarbons in ILs based on two distinct methods. In the first method, the thermodynamic properties of hydrocarbons and ILs were used as input parameters, while in the second method, the chemical structure of ILs and hydrocarbons along with temperature and pressure were used. The results show that in the first method, the DBN model with root mean square error (RMSE) and coefficient of determination (R
2
) values of 0.0054 and 0.9961, respectively, and in the second method, the DBN model with RMSE and R
2
values of 0.0065 and 0.9943, respectively, have the most accurate predictions. To evaluate the performance of intelligent models, the obtained results were compared with previous studies and equations of the state including Peng–Robinson (PR), Soave–Redlich–Kwong (SRK), Redlich–Kwong (RK), and Zudkevitch–Joffe (ZJ). Findings show that intelligent models have high accuracy compared to equations of state. Finally, the investigation of the effect of different factors such as alkyl chain length, type of anion and cation, pressure, temperature, and type of hydrocarbon on the solubility of gaseous hydrocarbons in ILs shows that pressure and temperature have a direct and inverse effect on increasing the solubility of gaseous hydrocarbons in ILs, respectively. Also, the evaluation of the effect of hydrocarbon type shows that increasing the molecular weight of hydrocarbons increases the solubility of gaseous hydrocarbons in ILs.
Abstract
In the context of gas processing and carbon sequestration, an adequate understanding of the solubility of acid gases in ionic liquids (ILs) under various thermodynamic circumstances is ...crucial. A poisonous, combustible, and acidic gas that can cause environmental damage is hydrogen sulfide (H
2
S). ILs are good choices for appropriate solvents in gas separation procedures. In this work, a variety of machine learning techniques, such as white-box machine learning, deep learning, and ensemble learning, were established to determine the solubility of H
2
S in ILs. The white-box models are group method of data handling (GMDH) and genetic programming (GP), the deep learning approach is deep belief network (DBN) and extreme gradient boosting (XGBoost) was selected as an ensemble approach. The models were established utilizing an extensive database with 1516 data points on the H
2
S solubility in 37 ILs throughout an extensive pressure and temperature range. Seven input variables, including temperature (T), pressure (P), two critical variables such as temperature (T
c
) and pressure (P
c
), acentric factor (ω), boiling temperature (T
b
), and molecular weight (Mw), were used in these models; the output was the solubility of H
2
S. The findings show that the XGBoost model, with statistical parameters such as an average absolute percent relative error (AAPRE) of 1.14%, root mean square error (RMSE) of 0.002, standard deviation (SD) of 0.01, and a determination coefficient (R
2
) of 0.99, provides more precise calculations for H
2
S solubility in ILs. The sensitivity assessment demonstrated that temperature and pressure had the highest negative and highest positive affect on the H
2
S solubility in ILs, respectively. The Taylor diagram, cumulative frequency plot, cross-plot, and error bar all demonstrated the high effectiveness, accuracy, and reality of the XGBoost approach for predicting the H
2
S solubility in various ILs. The leverage analysis shows that the majority of the data points are experimentally reliable and just a small number of data points are found beyond the application domain of the XGBoost paradigm. Beyond these statistical results, some chemical structure effects were evaluated. First, it was shown that the lengthening of the cation alkyl chain enhances the H
2
S solubility in ILs. As another chemical structure effect, it was shown that higher fluorine content in anion leads to higher solubility in ILs. These phenomena were confirmed by experimental data and the model results. Connecting solubility data to the chemical structure of ILs, the results of this study can further assist to find appropriate ILs for specialized processes (based on the process conditions) as solvents for H
2
S.
Neurons undergo substantial morphological and functional changes during development to form precise synaptic connections and acquire specific physiological properties. What are the underlying ...transcriptomic bases? Here, we obtained the single-cell transcriptomes of
olfactory projection neurons (PNs) at four developmental stages. We decoded the identity of 21 transcriptomic clusters corresponding to 20 PN types and developed methods to match transcriptomic clusters representing the same PN type across development. We discovered that PN transcriptomes reflect unique biological processes unfolding at each stage-neurite growth and pruning during metamorphosis at an early pupal stage; peaked transcriptomic diversity during olfactory circuit assembly at mid-pupal stages; and neuronal signaling in adults. At early developmental stages, PN types with adjacent birth order share similar transcriptomes. Together, our work reveals principles of cellular diversity during brain development and provides a resource for future studies of neural development in PNs and other neuronal types.
In order to achieve a durable repair overlay, high bonding strength to substrate concrete and having the least amount of cracks in overlay are the main issues. Polymer Modified Concrete (PMC) ...consists of Portland cement concrete with a polymer modifier. Its advantages are proper bonding strength to substrate concrete, high tensile and flexural strength and low amount of shrinkage and permeability which makes it a suitable material for repair overlays. In this paper, 24 mix designs of polymer modified concrete as the repair overlay containing two different types of modifier polymers (Styrene Butadiene Resin (SBR)-based and Acrylic-based polymers) with different replacement percentages and various amounts of silica fume was considered to investigate the effect of type and amount of polymers and also properties of the mentioned overlays on their bonding strength to the substrate concrete. Two different methods for bonding assessment had been used and compared with each other. In both polymer modifiers, maximum bonding occurred in presence of polymer with 20% of cement weight. SBR-based PMC showed stronger bonding than other type of modified concrete. According to the results, with aid of linear regression analysis and Fuzzy Logic method the bonding strengths are predicted with acceptable accuracy.
How does wiring specificity of neural maps emerge during development? Formation of the adult
olfactory glomerular map begins with the patterning of projection neuron (PN) dendrites at the early pupal ...stage. To better understand the origin of wiring specificity of this map, we created genetic tools to systematically characterize dendrite patterning across development at PN type-specific resolution. We find that PNs use lineage and birth order combinatorially to build the initial dendritic map. Specifically, birth order directs dendrite targeting in rotating and binary manners for PNs of the anterodorsal and lateral lineages, respectively. Two-photon- and adaptive optical lattice light-sheet microscope-based time-lapse imaging reveals that PN dendrites initiate active targeting with direction-dependent branch stabilization on the timescale of seconds. Moreover, PNs that are used in both the larval and adult olfactory circuits prune their larval-specific dendrites and re-extend new dendrites simultaneously to facilitate timely olfactory map organization. Our work highlights the power and necessity of type-specific neuronal access and time-lapse imaging in identifying wiring mechanisms that underlie complex patterns of functional neural maps.
Assessing the reliability of systems plays an effective role in the constellation design. Genetic Algorithm can be applied for the optimization design of satellite constellation, which are imperative ...in various fields like communication, surveillance and navigation. Opposite goals, such as optimizing performance and reducing the number of satellites in constellations along with low cost of construction and launch, have been analyzed in this paper. In the design of constellations, launching and replacing unhealthy satellites to avoid breakdown, and the time costing has a major impact on the level of system reliability performance. A method to design hybrid constellation for communication and navigation is proposed in this paper, it takes coverage capability and precession into consideration. According to LEO constellation, The issue of optimizing the number of satellites and other effective panels in constellation design has been discussed. The genetic algorithm is designed to the hybrid LEO constellations design by using a methodology of coverage constellation. It provides the optimal solutions for enhancing capability of communication and navigation. The simulation results confirm the performance of the proposed algorithm and indicates that it is feasible and effective Accordingly, in this paper, after designing the constellations using the genetic algorithm, we draw the final constellation diagram block and evaluating the conspicuous performance and reliability at the time of request.
An electrostatic discharge (ESD) event can cause a medical device to fail and pose a threat to patients'safety. This paper presents the data mining analysis of ESD failures in medical devices, over ...the last ten years, using the U.S. FDA's manufacturer and user facility device experience database. The most frequent failure modes and activities resulting in ESD events were identified and correlated with key environmental factors. Recommendations are then presented to medical device manufacturers and hospitals.
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