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Fluorescence molecular tomography (FMT), as a promising technique for early tumor detection, can non‐invasively visualize the distribution of fluorescent marker probe three‐dimensionally. However, FMT reconstruction is a severely ill‐posed problem, which remains an obstacle to wider application of FMT. In this paper, a two‐step reconstruction framework was proposed for FMT based on the energy statistical probability. First, the tissue structural information obtained from computed tomography (CT) is employed to associate the tissue optical parameters for rough solution in the global region. Then, according to the global‐region reconstruction results, the probability that the target belongs to each region can be calculated. The region with the highest probability is delineated as region of interest to realize accurate and fast source reconstruction. Numerical simulations and in vivo experiments were carried out to evaluate the effectiveness of the proposed framework. The encouraging results demonstrate the significant effectiveness and potential of our method for practical FMT applications. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method that enhances the optimization‐based elastic body solver. The proposed method tackles the element inversion problem, which is prevalent in the prediction‐projection approach for numerical simulation of elastic bodies. At the prediction stage, our method alleviates inversions such that the subsequent projection solver can benefit in stability and efficiency. To prevent excessive suppression of predicted inertial motion when alleviating, we introduce a velocity decomposition method and adapt only the non‐rigid motion while preserving the rigid motion, that is, linear and angular momenta. Thanks to the respected inertial motion in the prediction stage, our method produces lively motions while keeping the entire simulation more stable. The experiments demonstrate that our alleviation method successfully stabilizes the simulation and improves the efficiency particularly when large deformations hamper the solver. [ABSTRACT FROM AUTHOR]

This paper introduces a modified sequential version method for optimizing a linear function over an integer efficient set, as well as a new exact parallel algorithm. The performance of parallel programming in this context is clear and shown through different instances with different sizes. Each procedure builds a finite monotonous sequence of values for the main criterion to be optimized, in a reasonable amount of CPU execution time. This latter remains much better. For the first time, the Algerian IBNBADIS cluster—CERIST—was used with this type of problem. Significant results are obtained by both proposed techniques, particularly with the parallel one. [ABSTRACT FROM AUTHOR]

In this research paper, a well‐performing solar pump at the minimum cost of project life is designed and installed. Initially, the capacity of submersible pumps and discharge have been determined based on the water requirement of the crop and the size of the field. The total number of solar panels, inverter size, and motor pump system have been designed based on the law of conservation of energy. The two optimization techniques genetic algorithm (GA) and response surface methodology (RSM) have been used for analyzing the pump performance parameters and total cost. The GA tool has been used to determine the optimum tilt angle on which responses namely solar flux, solar panel efficiency, exergy, and pump efficiency should be maximum. Moreover, the performance of the solar pump at the optimum tilt angle has been compared with the 28° fixed tilt angle (latitute of location). For the experimental study solar pump experimental setup of 5 hp power has been installed in Faculty of Engineering and Technology, MJP Rohilkhand University at 28.36°N, 79.43°E. The total cost of the solar pump has been optimized with the help of RSM based on the discharge and head of the solar pump. The new optimization approach reduced the levelized cost of electricity (LCOE) from 0.041 to 0.035 $/kWh and the payback period is reduced from 4 to 3 years. The annual increment in average solar flux and overall efficiency has been recorded to be from 606 to 697 W/m2 and 11% to 14% respectively. [ABSTRACT FROM AUTHOR]

Summary: The analysis of spectrum sensing performance of energy detection (ED)‐based wireless cognitive radio sensor network (ED‐WCRSN) with hard‐decision combining (HDC) is presented in this paper. Particularly, several network parameters are derived to estimate the performance of ED‐WCRSN, considering channel errors, noise, and generalized α−μ fading. In the considered network, first, cognitive radio sensor (CRS) senses a primary user (PU), gets sensing data, and then uses an ED to make a local binary decisions about PU's active or inactive status. In both sensing and reporting channels, the channel error probability is also taken into account. Next, HDC technique is used at control center (CC) to combine the locally obtained decisions, and a final decision about the status of the PU is made. To do so, first, the expression for the novel and analytical, which incorporates noise and α−μ fading, detection probability in a CRS is derived and validated using Monte Carlo simulations in MATLAB and using an experimental setup. Then, utilizing derived mathematical expressions, closed‐form expressions of an average error rate (AER), optimal numbers of CRSs, and detection thresholds under noisy and α−μ fading conditions are developed. The substantial influence of channel and network factors is assessed using receiver operating characteristics (ROC), complementary ROC, and AER. Finally, the impacts of channel and network parameters on ED‐WCRSN performance are explored. For numerous parameters of the considered network, the optimal values detection threshold and number of CRSs are also found. [ABSTRACT FROM AUTHOR]

Autonomous driving has the ability to reshape mobility and transportation by reducing road accidents, traffic jams, and air pollution. This can yield energy efficiency, convenience, and more productivity as significant driving time will be gained and used in other activities instead. Autonomous vehicles are complex systems consisting of several modules that perform perception, decision‐making, planning, and control. Control is essential for achieving automatic driving; it is basically divided into longitudinal control that handles speed tracking and lateral control which ensures accurate steering. The latter is primordial in path tracking applications and recent research has witnessed a huge leap in this field. The aim of this paper is to provide a technical survey of the latest research on the lateral control of autonomous vehicles as well as to highlight technical challenges and limits for further developments. [ABSTRACT FROM AUTHOR]

Antenna array synthesis is quite a popular topic in electromagnetics and finding suitable array parameter values is a challenging nonlinear engineering problem in this field. In recent years, it has been realized that optimization algorithms can be used to achieve desired solutions in this area. Besides, improvements in the optimization algorithms make it possible to perform synthesis processes on different array structures and to obtain better results. In this paper, a method based on a combination of ant lion optimizer (ALO) and sequential quadratic programming (SQP) is proposed for the concentric circular antenna array (CCAA) synthesis. Excitation amplitudes of array elements are optimized for CCAAs with low maximum sidelobe level (MSL), narrow first null beamwidth (FNBW), and low dynamic range ratio (DRR). The results of proposed ALO‐SQP method are compared with those of 11 different algorithms: ALO, moth flame optimizer (MFO), SQP, symbiotic organisms search (SOS), biogeography based optimization (BBO), opposition‐based gravitational search algorithm (OGSA), cat swarm optimization (CSO), firefly algorithm (FA), evolutionary programming (EP), backtracking search optimization algorithm (BSA), and seeker optimization algorithm (SOA). The comparisons indicate that the CCAAs synthesis using the proposed method presents good MSLs, FNBWs, and DRRs. [ABSTRACT FROM AUTHOR]

Normalized difference vegetation index (NDVI) is an essential remote measurement for agricultural studies because of its strong correlation with crop growth and yield. Accurate and comprehensive NDVI forecasts thus provide effective future projections of crop yield for precise agricultural planning and budgeting. Previous recurrent neural network (RNN) based forecasting methodologies have only performed single‐pixel or large‐area‐average NDVI predictions. We present an alternative RNN‐based deep‐learning architecture, the convolutional long short‐term memory (ConvLSTM), to supply much more comprehensive and detailed NDVI forecasts. In this paper, a single ConvLSTM is capable of 10,000‐pixel field‐level NDVI predictions, providing a more practical methodology for agricultural producers than single‐pixel studies. We compare our model to the parametric crop growth model (PCGM), another multipixel field‐level NDVI forecasting technique. We test each model over the same set of soybean crop field pixels with the root mean square error (RMSE) metric. The training configuration of each model is defined by the number of seasons of historical data used for weight optimization. When the best training configuration of the model found is used, the ConvLSTM obtains an RMSE of 0.0782, outperforming the PCGM's RMSE of 0.0989 (an improvement of 0.0207 in precision represents a large gain in the accuracy of production volume prediction when projected into large production areas). Finally, by comparing the ConvLSTM predictions with the ground truth data over the entire target region rather than just the soybean crop pixels, we discover that the ConvLSTM can also predict NDVI values over the nonsoybean crop as effectively. [ABSTRACT FROM AUTHOR]

When a wind farm (WF) approaches the end of its life cycle, repowering is another opportunity for wind energy to prove its value. This paper proposes an optimization framework to guide the WF repowering, considering the power generation, the economic cost, and the aesthetic of the WF when various types of new wind turbines (WTs) are added. When calculating the wake deficits inside the WF, a three‐dimensional (3‐D) Gaussian wake model is applied which considers the height differences among the new WTs. A harmony pattern metric is used to assess the visual impact of the rebuilt WF. This optimization problem is formulated as an integer programming (IP) problem and is tackled by the integer particle swarm optimization (IPSO) algorithm. The wind data used for this optimization procedure is predicted by the auto‐regressive (AR) model. The case study on the OWEZ WF verifies the effectiveness of the proposed method. It is also validated that the application of predicted wind data is better than the historical data for WF repowering optimization. [ABSTRACT FROM AUTHOR]

Escherichia coli O157:H7 (STEC) is one of the hazardous foodborne pathogens in milk. Although traditional preservation methods reduce contamination, they are time‐consuming or cause physicochemical changes. Therefore, we optimize STEC inactivation in goat's milk by thermosonication, an alternative to traditional treatments. Different times (1–35 min) and temperatures (45.9–74.1°C) were applied, using a Central Composite Rotatable Design (CCRD). Lipid oxidation was adopted as an optimization limiting factor. Mathematical models described STEC inactivation and lipid oxidation with high performance, considering the high R2adj (0.942 and 0.731), and low mean square error (0.065 and <0.0001) and lack‐of‐fit (0.133 and 0.183). Validation was verified by the accuracy (1.141 and 1.017) and bias (0.992 and 1.006) factors, and the relative error of prediction (0.910 and 1.000). Both variables affected STEC inactivation linearly, enhancing decontamination. Lipid oxidation was affected by time, increasing oxidation products formation. Optimization was achieved around 1–20 min/62–74°C, improving STEC inactivation (6.6 log CFU/ml) with minimal lipid oxidation (0.06 mg MDA/L). Therefore, thermosonication represents a promising technology facing to traditional methods, ensuring bacteriological safety and minimal alterations. Practical Applications: Despite traditional methods for milk decontamination still being considered effective, there are some reports on pasteurized milk and dairy products‐related outbreaks. High‐intensity ultrasound is an emerging non‐thermal technology recently explored as a pathogen reduction method, used individually or combined. However, due to cavitation mechanism and free radicals realizing, some oxidative alterations could occur during processing. The present research paper contributes to provide a better understanding on the combined application of ultrasound and heat (thermosonication) to inactivate Escherichia coli in caprine milk. The findings herein are promising to the industrial utilization of thermosonication to obtaining safety products with minimal oxidative changes. [ABSTRACT FROM AUTHOR]

Wireless sensor networks have proven to be a promising paradigm due to their wide applicability in the real‐world scenarios. Because of the resource constraint, type‐variant and battery‐powered features of the sensor nodes, the key challenge is how to improve the energy usage and network life in the heterogeneous sensor networks. In this paper, the Mahalanobis distance based K‐Means algorithm is integrated with a novel evolutionary approach for clustering called calf search optimization algorithm (K‐CSOA) that creates energy efficient clusters. The routing in the network is performed using a power efficient ant colony optimization algorithm (ACO). The extensive and multiple simulations are performed to validate the effectiveness of the proposed method. It is observed that the running time of the proposed scheme is lowered due to the implementation of hybrid clustering. The results are validated for various performance metrics wherein the proposed method shows 41.6% and 4.3%–12% reduction in energy expenditure and end‐to‐end delay respectively and around 60% enhancement in the throughput of the network when compared with other similar state‐of‐the‐art methods. In addition to this, statistical analysis is also carried out to identify the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a kinematic wave‐based adaptive transit signal priority control (KATC) aiming to minimize average passenger delay at intersection level. The passenger delay minimization problem is formulated as a mixed‐integer non‐linear program (MINLP) with two decision variables of green time and phase sequence. The adoption of the phase sequence in the optimization and not involving the common simplifying assumptions in the delay models are the main contributions of the current study. General traffic and public transportation (PT) vehicle delay are estimated using kinematic wave theory. Genetic algorithm is utilized to solve the MINLP problem at 1‐cycle intervals and for a decision horizon of 3 consecutive cycles. The performance of KATC is evaluated against SYNCHRO and the KATC model without phase sequence optimization, using VISSIM. The results of the experiments indicate superior performance of KATC over the two other models in terms of both average passenger delay and PT passenger delay, especially at low congestion levels. Furthermore, increasing PT passenger occupancy can effectively contribute to higher passenger delay improvements. The adverse impacts on passenger vehicles are restricted to a 3.4% and 2.7% increase in general traffic delay compared to SYNCHRO and the KATC model without phase sequence optimization, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we present tuning rules for PI controllers that represent an effective alternative to the well‐known lambda‐tuning for the load disturbance rejection task. In particular, the integrated absolute error is minimized subject to a constraint on the maximum sensitivity selected. Suitable formulas are given to relate the proposed tuning with the lambda‐tuning, and the improvement obtained is quantified for different process dynamics. Both self‐regulating and non self‐regulating processes are considered. Simulation results are given to illustrate the methodology. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method for simulating hyperelastic solids with Smoothed Particle Hydrodynamics (SPH). The proposed method extends the coverage of the state‐of‐the‐art elastic SPH solid method to include different types of hyperelastic materials, such as the Neo‐Hookean and the St. Venant‐Kirchoff models. To this end, we reformulate an implicit integration scheme for SPH elastic solids into an optimization problem and solve the problem using a general‐purpose quasi‐Newton method. Our experiments show that the Limited‐memory BFGS (L‐BFGS) algorithm can be employed to efficiently solve our optimization problem in the SPH framework and demonstrate its stable and efficient simulations for complex materials in the SPH framework. Thanks to the nature of our unified representation for both solids and fluids, the SPH formulation simplifies coupling between different materials and handling collisions. [ABSTRACT FROM AUTHOR]

In general, it is not easy to simulate an elastic body that undergoes large deformations. Especially when its elements are inverted or tangled, that is, when its vertices penetrate its polygons, simulation often fails. In this paper, we propose a simple yet highly effective method for alleviating the inversion problems of elastic bodies. Our experiments made with typical optimization‐based solvers demonstrate that the proposed method successfully stabilizes the solvers and produces visually plausible motions. We believe that our method can be widely adopted by a variety of state‐of‐the‐art elastic‐body simulators thanks to its simplicity. [ABSTRACT FROM AUTHOR]

Background: Understanding the nature of engineering is important for shaping engineering education, especially precollege education. While much research has established the pedagogical benefits of teaching engineering in kindergarten through 12th grade (K–12), the philosophical foundations of engineering remain under‐examined. Purpose This conceptual paper introduces the honeycomb of engineering framework, which offers an epistemologically justified theoretical position and a pedagogical lens that can be used to examine ways engineering concepts and practices are taught in precollege education. Scope/Method: The honeycomb of engineering was developed as a descriptive framework by examining existing literature over a wide range of related disciplines such as the philosophy of engineering and technology, as well as design thinking and practice. The pedagogical translation of the framework was then developed to examine published precollege engineering curricula. Results: The framework categorizes the multiple goals of engineering using an ontological classification of engineering inquiries anchored in the central practice of negotiating risks and benefits (i.e., trade‐offs). This framework also illustrates the adaptability of design methodology in guiding six inquiries: (1) user‐centered design, (2) design‐build‐test, (3) engineering science, (4) optimization, (5) engineering analysis, and (6) reverse engineering. The published curricula represented these inquiries with varying degrees, with design‐build‐test lessons seeing the most representation followed by user‐centered design. Conclusions: The honeycomb of engineering framework delineates variations in engineering education based on an epistemological explanation. The pedagogical translations offer guidance to educators, researchers, and curriculum designers for differentiating curricular aims and learning outcomes resulting from participation in different engineering inquiries. [ABSTRACT FROM AUTHOR]

Medical images have become omnipresent in diagnosis and therapy. However, they can be affected by various types of noise that reduce image quality and make the final diagnostic decision difficult. The main objective of this research is to effectively remove the noise while preserving the important image characteristics. This paper proposes a novel approach for image denoising based on discrete wavelet transform (DWT) with the selection of the best decomposition level and mother wavelet. Then, the thresholding function is carried out in the detail coefficients. Optimal thresholding is done using new optimization techniques such as the crow search algorithm and social spider optimization techniques. Finally, the inverse of DWT is applied to reconstruct the denoised image. The proposed method is evaluated using peak signal to noise ratio, mean square error, and the structural similarity index measure. The experimental results show the efficiency of the optimization‐based denoising method over standard methods. Interesting results are obtained with all kinds of noise, and improvements about 30 dB can be reached with the Rician noise. [ABSTRACT FROM AUTHOR]

Summary: Resource provisioning in the cloud is the most popular business model for any service provider due to profit that is based on how resources are distributed among users in Industry 4.0. Moreover, much research carried out to provide a better resource provisioning system to service providers; however, efficient resource provisioning may save the environments too. This study presents an extensive analysis of different resource provisioning systems based on concert parameters. More than 250 relative research articles have been considered for this study, out of these 125 articles has been processed for comparative analysis on the basis of different performance metrics. This study highlights the classifications of resource management techniques, objective functions, and open research challenges and issues while analyzing resource management techniques. It also provides the depth knowledge of uses of performance metrics utilization based on its classifications. [ABSTRACT FROM AUTHOR]

Complex systems seen either in general engineering practice or economics are subjected to ever increased uncertainties that are mostly represented as random variables or parameters, and the characteristics of random variables are represented by their probability density functions (PDFs). Controlling their PDFs means to shape their stochastic distributions and in general it would provide a full treatment for system analysis and operational control and optimization. This leads to the development of stochastic distribution control (SDC) systems theory in the past decades, where the original aim of the controller design is to realize a shape control of the distributions of certain random variables in their PDFs sense for some engineering processes. Indeed, once the PDFs of these random variables or parameters are used to describe their distribution characters, the control task is to obtain control signals so that the output PDFs of stochastic systems are made to follow their target PDFs. The subject of SDC was initially originated for non‐Gaussian stochastic control systems design but has found a wide spectrum of applications in general systems in terms of data‐driven modeling, analysis, signal processing (filtering), data mining via multivariable statistics, decision‐making (optimization) for systems subjected to uncertainties and even in economics. In this context, SDC constitutes an effective primer tool for complex system analysis, control and operational optimizations. In this review paper, a detailed survey of the developments on the research of SDC systems will be made together with their wide spectrum applications and future perspectives. [ABSTRACT FROM AUTHOR]

This paper investigates the optimization problem for a class of switched interconnected positive linear systems (SIPLSs), of which each subsystem is composed of several positive interconnected components. Both the continuous‐time and periodic sampling control schemes are considered. Combining with the characteristics of the interconnection and positivity, a novel class of multiple co‐positive Lyapunov functions is constructed. Based on the multiple Lyapunov functions method, a state‐dependent switching law with a dwell time constraint is introduced so that the state is continuously evaluated after the dwell time. Furthermore, the designed switching law is extended to a new sample‐based scenario where the state is periodically evaluated after the dwell time. In both cases, suitable cost functions are selected to estimate the performance of the SIPLSs, and the upper bounds are calculated. Finally, numerical examples are considered to illustrate the effectiveness of the presented results. [ABSTRACT FROM AUTHOR]

Heat exchanger networks (HENs) are a useful method of reducing the energy costs and environmental impact of industrial processes. Therefore, many papers focusing on solving HEN design problems efficiently have been published in the last years and several techniques have been proposed for their solution. The high complexity of the problem has led to an increment in the number of papers that use metaheuristics to solve it. The main reason is the capability of metaheuristics to handle complex problems in a feasible computational time. Additionally, this approach can easily take into account investment costs, and it offers more flexibility in the definition of the objective function and problem restrictions. In this paper, we review the most relevant papers that use metaheuristic techniques to resolve the HEN design problem. We also propose a method for grouping the different analyzed metaheuristics. It is based on a series of characteristics that allows the correct characterization of the different approaches. [ABSTRACT FROM AUTHOR]

Recent years have been characterized by marked progress in industrial instrumentation and mechatronics control technology. This year commemorates the fifth publication year of the IEEJ Journal of Industry Applications (emIEEJ J. IA). Additionally, the Mechatronics Control (MEC) technical committee was formed 3 years ago following a separation from the Industrial Instruments and Control (IIC) technical committee in order to further enhance their respective social contributions. The increased activity of both committees also contributed to the progress of the Journal. This paper discusses the recent advances and outlook in the technical field of industrial instrumentation and mechatronics control based on papers published in the IEEJ J. IA and a few other significant papers, which consider the current activities of the various committees. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Additive manufacturing technologies have been extensively used in the development of medical products, mainly due to its' complex geometry advantages. Orthoses are among the most common medical devices redesigned for additive manufacturing, as patient specific products. Currently, most of these orthoses are thermoformed from plastic. Advantages of custom and topologically optimized orthosis are mentioned by literature. The aim of this paper is to study the possibility of using lattice structures for the design and development of a functional ankle foot orthosis. The mechanical behavior of an ankle foot orthosis is studied, by optimization using lattice structures, for three different materials, to reduce its weight but also to keep its original resistance. The resulted ankle foot orthosis model is loaded with 500 N, to simulate the real‐life value of the force that is applied normally on an actual orthosis. Research results show that the optimum material is PET‐G for both 50% and 100% lattice values. [ABSTRACT FROM AUTHOR]

The regulation of the frequency and line power flow in interconnected power networks is considered to be a key aspect of load frequency control (LFC). This article broaches a modern power network composed of three interconnected control areas including traditional generation units taking into account non‐linearities, also renewable energy sources (RESs) and energy storage (ES) units are involved in the power grid paradigm. Two forms of RESs are included in the analysis, which are photovoltaic (PV) and wind power plants. In addition, the study framework involves three types of ES units, which are batteries of plug‐in electric vehicles (PEVs), flywheel energy storage system (FESS) and capacitive energy storage system (CESS). In this analysis, LFC is accomplished by the use of proportional‐integral‐derivative (PID) controllers in the system control loops. A recent optimization algorithm called Manta Ray Foraging optimization (MRFO) is employed to obtain the optimal gain configuration of the controllers. Real site measurements are imported to the RESs involved in the study aiming to examine the proposed control scheme under realistic conditions. Compared with other rival algorithms, the effectiveness of the MRFO‐based PID controller is validated. Simulation results confirm the efficacy of the proposed control scheme. The findings also ensure the role of ES units in optimizing the time‐domain responses. The main contributions of this paper are applying a new metaheuristic optimization algorithm to solve the LFC problem and introducing a new criteria for judging the system performance in compliance with the harmonic spectrum of the responses in the frequency domain. The results of the simulation are retrieved through a MATLAB model. [ABSTRACT FROM AUTHOR]

Summary: Multiple‐input multiple‐output (MIMO) systems perform well from the energy efficiency (EE) and the spectral efficiency (SE) points of view in fifth generation (5G) communication systems. This paper considers the operation of a MIMO system with a relay. The optimization problem relates to the EE maximization. This problem has two types of limitations, which provide a maximum transmission power and a minimum data rate for users. The encountered objective function is in a fractional form and thus it is a non‐convex function. Besides, the problem is constrained. We utilize a lower bound analysis for the data rates, some properties of the linear programming, and the maximum ratio transmission (MRT) precoding scheme to obtain a convex objective function. Using the Lagrange dual function, we obliterate the constraints of the problem and then it is easy to solve. To improve system performance, users are divided into two groups based on their channel gains, and the maximum transmission power is reasonably divided between them. Two iterative algorithms are proposed to solve the optimization problem numerically, and finally we investigate performance of the proposed method. [ABSTRACT FROM AUTHOR]

Most of the concrete volume in multistorey buildings is cast in solid slabs, which are frequently flat slabs supported on columns. By using two‐way spanning ribbed slabs, concrete consumption could be significantly reduced. However, due to the high costs associated with formwork, such a complex rib configuration is rarely used nowadays. With the advent of technologies for automated formwork fabrication, the material‐saving potential inherent in this structural system could again be exploited. This paper investigates the feasibility of material‐efficient ribbed concrete slabs on a building scale using conventional concrete and steel reinforcing bars cast inside a three‐dimensional‐printed plastic‐based formwork. To that end, the code‐compliant design of ribbed slabs is first discussed, followed by the introduction of a concept for an automated design‐to‐production workflow. The sustainability of this slab system is compared to a solution using conventional formwork in a case study consisting of a multibay office building with slabs spanning 8 m in both directions, revealing that ribbed slabs use 40% less concrete than solid slabs. Several representative structural elements of the case study (ribs, slab‐column transition) were produced at full‐scale and tested until failure to investigate the feasibility of production and structural performance. Three T‐beams with various rib shapes (straight, kinked with diaphragms, curved) were tested in a three‐point bending configuration, showing a ductile behavior with longitudinal reinforcement yielding and indicating the relevance of torsional effects in curved ribs. Punching tests on two slab‐column connections (ribbed, solid) revealed that the optimized ribbed slab could prevent brittle punching failures and achieve an ultimate load 105% higher than the solid reference slab. All specimens' load‐bearing behavior could be predicted using established design formulas, showing the feasibility of producing code‐compliant ribbed slabs with the applied technology. [ABSTRACT FROM AUTHOR]

Night delivery is an approach increasingly used by motor carriers to improve the efficiency of business‐to‐business logistics. Many benefits of night deliveries have been reported in the literature, but in practice, not every carrier is benefitting from night deliveries. In fact, anecdotal evidence suggests that many carriers are losing money from night deliveries. While a limited number of past studies have discussed the disadvantages of night deliveries, in many cases, they cannot explain why carriers are not benefitting from night deliveries. This implies that some disadvantages of night deliveries may still be currently unknown. This paper seeks to identify such "hidden" disadvantages by studying this issue through the lens of transportation economics. Understanding such disadvantages can contribute to both theories and practice of night deliveries, especially for decision making on night‐delivery adoption by carriers, as it can lead to a better understanding of when and where night deliveries might be beneficial or detrimental. [ABSTRACT FROM AUTHOR]

As a result of the poor mechanical properties of most metal–organic frameworks (MOFs), they are liable to dissociate in water and thus cannot maintain immobilized enzyme activity. In this paper, a magnetic porous carbon material (Fe‐Cu‐MPC) with good stability was prepared by high temperature carbonization using a bimetallic Fe‐Cu‐MOF precursor, and used to immobilize laccase by a simple and rapid adsorption‐crosslinking method. Optimized by the response surface method, optimal conditions for the immobilization of laccase on Fe‐Cu‐MPC were obtained as follows: enzyme concentration 1.275 mg mL−1, immobilization time 32 min, and pH 4.7. Under the optimal preparation conditions, the activity of the immobilized laccase obtained was 0.63 U mg−1, with activity recovery of 63.13%. The enzyme loading was 189.03 mg g−1 and the immobilization yield was 74.13%. Compared with free laccase, Fe‐Cu‐MPC@Lac showed stronger tolerance to temperature and pH, and had better thermal stability and storage stability. The removal of BPA by immobilized laccase was studied, showing that the removal effect of Fe‐Cu‐MPC@Lac on BPA was much higher than that of free laccase. Within 5 h, the BPA removal amount of Fe‐Cu‐MPC@Lac (0.34 mmol g−1) was two‐fold that of free laccase (0.14 mmol g−1), and the BPA removal rate reached 41.35% after ten cycles. Finally, based on the intermediates identified by gas chromatography–mass spectrometry, two possible degradation pathways of BPA were proposed. Studies have shown that Fe‐Cu‐MPC is an excellent carrier and Fe‐Cu‐MPC@Lac has great potential in the treatment of BPA containing wastewater. © 2022 Society of Chemical Industry (SCI). [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor network (WSN) is a well‐developed domain suitable in the optimal collection and processing of information needed for the present world. For processing and transmitting the correct data by the network, it is affected by many disrupting factors like interference, battery life, distance between the nodes, and redundant data. There have been many methods proposed in the past. Among all the disrupting factors, routing has been the most studied problem in the WSN literature, whereas packet length sizing has been the most untouched topic compared to routing. Sizing the packet lengths to transmit it through the network is important to get error‐free data and run an energy‐efficient network. In this paper, we propose a sling‐shot spider optimization (S2SO) algorithm for packet length optimization in WSN and Internet of Things (IoT)‐based networks. The S2SO algorithm is developed based on the spider's unique behavior of catching prey. The proposed algorithm is implemented in three types of networks: 1‐hop, 2‐hop, and multi‐hop networks. A mathematical model for the communication channel, energy efficiency, and energy consumption is developed for all three types of networks. The proposed packet length optimization model is simulated in MATLAB software and compared with conventional bio‐inspired algorithms. The results show that the proposed algorithm is very fast in finding the optimal results and transmits optimal packet size with low error rate of 0.2 p.u. and a high efficiency of 98%. [ABSTRACT FROM AUTHOR]

Distribution system planners and operators have increasingly exposed great attention to maximizing the penetration of renewable energy resources (RERs), and electric vehicles (EVs) toward modern microgrids. Accordingly, intensive operational and economic problems are expected in such microgrids. Specifically, the operators need to meet the increased demand for EVs and increase the dependence on RERs. The charging strategy for EVs and the RER penetration level may result in increased power loss, thermal loading, voltage deviation, and overall system cost. To address these concerns, this paper proposed an optimal planning approach for allocating EV charging stations with controllable charging and hybrid RERs within multi‐microgrids, where the charging strategy in the proposed planning approach contributed to improving power quality and overall system cost, where the voltage deviation, energy not supplied, total cost have been reduced to 26.03%, 49.57%, and 70.45%, respectively. The simulation results are compared with different optimization techniques to verify the effectiveness of the proposed algorithm. The proposed simultaneous allocation approach of EV charging stations and RERs can reduce operating costs for RERs and conventional stations while increasing the charging stations' capacity. [ABSTRACT FROM AUTHOR]

Summary: Recently, the virtual data center embedding (VDCE) problem has drawn significant attention because of a growing need for efficient means of data center resource allocation. By ensuring a set of virtual data center (VDC) integration requests coming from his customers, among the main concern of an infrastructure provider is the maximization of the utilization rate of data center resources and benefits. However, existing VDCE solutions mostly focus on consolidating virtual machines in a single physical data center. Therefore, in this work, we improve the consolidated targets techniques, that consider only the virtual machines integration, by the consideration of network devices and fabrics (e.g., switches and paths/links). We consider new unreleased constraints such as multiple virtual nodes of the same request co‐location, and intermediate node requirements when a virtual link is mapped. To address the above problem, in this paper, we propose a binary linear programming‐based model, called BLP‐VDCE, to solve the VDCE problem with network‐aware consideration. This model ensures a simultaneous consolidated embedding of virtual nodes and virtual links. Extensive simulations show that solving the proposed BLP‐VDCE model can efficiently embed VDC requests with a high physical resource utilization rate. [ABSTRACT FROM AUTHOR]

Energy‐efficient train operation (EETO) in high‐speed railways (HSRs) is an extra cost‐effective and flexible means to promote energy‐saving. This paper first examines the energy consumption sources and energy‐saving measures of high‐speed trains (HSTs). Then presents the EETO in HSRs, including three categories: energy‐efficient train control, energy‐efficient train timetabling, and EETO considering train timetabling and driving strategy. Next, the current research status and progress on three aspects of EETO in HSRs, namely optimization algorithm, constraint condition, and oriented scenario, are sorted out. Finally, the research on EETO in HSRs has prospected and proposed directions that can study in depth in the future. By summarizing and reviewing the research on EETO in HSRs, it is hoped to furnish a reference for the railway sector to enhance quality, efficiency, and green, low‐carbon development. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In recent years, 4D printing has allowed the rapid development of new concepts of multifunctional/adaptive structures. The 4D printing technology makes it possible to generate new shapes and/or property‐changing capabilities by combining smart materials, multiphysics stimuli, and additive manufacturing. Hygromorphs constitute a specific class of new smart materials where their properties and morphing capabilities are dependent on the surrounding humidity, which drives actuation. Although multiple efforts have been made to fabricate hygromorph demonstrators, a comprehensive design process to produce hygromorphs by multiple 4D printing techniques is not yet available. The broad aim of this review and concept paper is to i) highlight existing scientific and technology gaps in the field of 4D‐printed hygromorphs, ii) identify tools existing in other research fields for filling those gaps, and iii) discuss a series of guidelines for tackling future challenges and opportunities to develop 4D‐printed composite hygromorph materials and related manufacturing processes. Accordingly, this review describes the materials and additive manufacturing techniques used for hygromorph composite fabrication. Moreover, the relevant parameters that control actuation, the models selection and performance, the design methods and the actuation measurements for customized 4D‐printed hygromorph materials, are discussed. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we propose a novel pilot power allocation method that focuses on the maximization of the energy efficiency. The core algorithm of this method, which is a dynamic approach that takes into account signal‐to‐interference‐plus‐noise ratio (SINR), is called pilot power allocation polarizing SINRs (PS‐PPA). The aim is to maximize the energy efficiency of the system along with the proposed pilot power allocation method using this algorithm in a multi‐cell multi‐user massive multiple‐input multiple‐output (MIMO) system. The algorithm determines difference between average SINR per cell and SINRs of users individually, during the scan of the whole cells sequentially. Therefore, it always updates the allocation for the latest SINR of users in power updates to improve the energy efficiency of the system. In power updates, PS‐PPA calculates weights using an exponential function of the SINR difference. This weighting function is defined for each real number, so it can always result in a specific number. In addition, the weighting function is performed in the [ ρmin,ρmax] range where the power values are predefined. The energy efficiency of the system is measured in a number of simulations by calculating the average SINR per cell. Furthermore, all these performance results are obtained for equal pilot power allocation (EPPA) and water‐filling pilot power allocation (WF‐PPA) schemes. As a result of simulation results, proposed pilot power allocation method has proven to be more superior than EPPA and WF‐PPA methods. [ABSTRACT FROM AUTHOR]

To promote a low‐carbon society, it is urgent to better integrate renewable energies into energy supply systems. This paper examines the impact of solar photovoltaic (PV) integration into the national electrical grid in Burkina Faso on the electricity production cost. The analysis is based on the levelized cost of electricity (LCOE) technique. Several levels of PV integration have been considered namely 20%, 40%, 60%, and 80% of the total installed capacity. First, the results revealed all the configurations with PV integration are more attractive and cost‐effective compared with the conventional diesel standalone electricity system. The sensitivity analysis shows that the configuration with 80% PV is the most attractive when compared to the other ones as it has the lowest LCOE and CO2 emissions compared with the other scenarios. This paper also shows that in the context of rising fuel prices and environmental concern, the electricity production based on diesel standalone system is not a viable solution for Burkina Faso at the moment. Finally, the results revealed that subsidies offered by the government of Burkina Faso to support the electricity production cost will be more effective for a system with PV integration. This paper gives detail highlights of solution for policymakers to make useful investment in solar energy and widen the access to electricity in Burkina Faso. [ABSTRACT FROM AUTHOR]

Given the current expansion in the use of cold‐formed steel, the emergence of increasingly complex cross‐sectional shapes, the continual advances in manufacturing and the increasingly important quest for efficient and sustainable construction solutions, the optimization of cold‐formed steel products is an exceedingly relevant research field. The prolific publication of research papers in this area encountered over the past decade is testament to this. This paper aims to explore the general state‐of‐the art of this research field, as well as present a summary of research conducted at the University of Sheffield over the past five years and place it in a wider context. Further advancements needed in this field are also discussed. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a methodology for the generation of cloud coverage time series correlated on both temporal and spatial domains and the estimation of cloud‐free line‐of‐sight (CFLOS) probability for a single optical ground station (OGS) and a network of OGSs (multiple OGS) for medium earth orbit (MEO) constellation satellite communication systems is presented. Spatial diversity is employed as a mitigation technique against cloud blockage to increase the availability of an OGS network (OGSN). In the second part of the paper, an effective algorithm based on the ant colony optimization (ACO) algorithm is proposed for the optimum selection of OGSs forming an OGSN. The proposed algorithm takes into consideration the spatial correlation between the OGSs. In the simulation results section, a MEO constellation system with 12 MEO satellites has been assumed. The integrated liquid water content (ILWC) statistical parameters that are necessary for the CFLOS time series are taken from ECMWF Re‐Analysis (ERA)‐Interim database, European Centre for Medium‐Range Weather Forecasts (ECMWF). Finally, numerical results for the optimum selection of OGSs using the proposed methodology are exhibited and commented. Interesting conclusions are drawn, and future work with technical challenges is briefly described. [ABSTRACT FROM AUTHOR]

Software vulnerabilities trend over time has been proposed by various researchers and academicians in recent years. But none of them have considered operational coverage function in vulnerability discovery modeling. In this research paper, we have proposed a generalized statistical model that determines the relationship between operational coverage function and the number of expected vulnerabilities. During the operational phase, possible vulnerable sites are covered and vulnerabilities present at a particular site are discovered with some probability. We have assumed that the proposed model follows the nonhomogeneous Poisson process properties; thus, different distributions are used to formulate the model. The numerical illustration shows that the proposed model performs better and has the good fitness to the Google Chrome data. The second focus of this research paper is to evaluate the total cost incurred by the developer after software release and to identify the optimal vulnerability disclosure time through multiobjective utility function. The proposed vulnerability discovery helps in optimization. The optimal time problem depends on the combined effect of cost, risk, and effort. [ABSTRACT FROM AUTHOR]

Abstract: Resource leveling and time–cost tradeoff are among the most challenging optimization problems in project management. These two problems are usually addressed separately because each problem optimizes different objective functions. In this paper, we develop an integrated model that addresses both problems when activities are allowed to split for better utilization of resources. The formulated mixed integer linear program (MILP) model considers the tradeoff between the crashing‐dependent costs; direct and indirect costs, and resource utilization related costs; acquiring, releasing, and splitting costs. The model can be used as a decision tool to determine whether crashing is recommended when decision makers are also concerned with the better utilization of project's resources. A one‐way sensitivity analysis was conducted to assess total cost savings achieved through the integration of time–cost tradeoff and resource leveling problems. Another experimental study was undertaken to evaluate the performance of the MILP runtime. [ABSTRACT FROM AUTHOR]

In this paper, a 3D nitrogen‐doped carbon network with excellent adsorption properties was prepared for bisphenol S (BPS) removal from water. An optimized sample B‐T700‐N3 with high Langmuir specific surface area as well as plentiful heteroatoms was screened out. Benefiting from the synergistic effect of conjugation and hydrogen bonding between the adsorbent and bisphenol S, B‐T700‐N3 demonstrated superior adsorption performance. The maximum adsorption amount (qmax,e) of the B‐T700‐N3 at equilibrium was determined to be up to 91 mg/g, which was comparable or even higher than that of the state‐of‐the‐art reported adsorbents. Experimental results illustrated that this adsorbent could also effectively remove other bisphenols (BPA, BPAF) from water. Overall, this novel adsorbent demonstrated a competitive performance for bisphenols removal in aqueous solution and can be a highly interesting candidate for industrial applications. [ABSTRACT FROM AUTHOR]

This paper aims to enhance the image quality in ultrasound images. The significant difficulties in the ultrasound image are the presence of speckle noise. Speckle is the granular noise, and this kind of noise produces a lot of challenges during medical diagnosis. Also, these kinds of problems degrade image quality. The proposed work overcomes this kind of issue with nonsubsampled contourlet domain‐based cross‐guided bilateral filtering. Initially, additive speckle noise is introduced with the log‐transformed Rayleigh distribution. This additive speckle noise component is to be decomposed through the non‐subsampled contourlet domain transform. Then the decomposed image is despeckled by the cross‐guided bilateral filter, and the cost function of this filter is minimized through adaptive galactic swarm optimization. The proposed filtering technique despeckles the additive noise in the noisy image. Finally, the decomposed image is reconstructed using the inverse transform of the nonsubsampled decomposition. The implementation of the proposed methodology is carried out in MATLAB simulation platform. Also, the performance of the proposed work is measured by few metrics such as structural similarity index matrix, mean structural similarity index matrix, mean square error, peak signal to noise ratio, Bhattacharyya coefficient, and speckle index. The result of cost function optimization provides less distortion when compared to other techniques. [ABSTRACT FROM AUTHOR]

Complex systems typically have a large parameter space and by definition have the potential for strong emergent behavior, especially when operating in a complex environment. A method is needed to design a system that will be resilient in a complex target operating environment. Here, we propose a maximin optimization approach to support the exploration of system design, based on co‐evolutionary system/environment models, which emphasizes the importance of the operating environment in the system evolution, resulting in increased system resilience. In this paper, this method is demonstrated on an air defense system and shows an increase in resilience when compared to the system resulting from the application of a genetic algorithm such as has been previously demonstrated for other systems. For the air defense system used here, the proposed maximin optimization process significantly (p<.001, via a one‐sided paired t‐test) increased the resulting system resilience from 0.64 (the resilience of the system designed by a genetic algorithm) to 0.92 (the resilience of the system designed by maximin optimization). [ABSTRACT FROM AUTHOR]

Baseflow was proven to be the most unpredictable component of streamflow through various research. However, the recent method for estimating baseflow is due to the development of theoretical and computational techniques. This paper attempted to develop a fully automated baseflow separation system based on a recursive digital filter with an optimization algorithm for the single separation. Most of the previous baseflow separation methods use a single set of a parameter and BFImax (the maximum value of baseflow index), which can underestimate or overestimate the baseflow; however, the system developed in this study estimates multiple optimized a parameters using seasonality and flow conditions and uses them for BFImax calculation and baseflow separation. This system derived baseflow results in better understanding of watershed and streamflow tendency characteristics. This study developed a Web‐based Hydrograph Analysis Tool 2020 with a user‐friendly interface and new separation method regarding the seasonality and flow conditions with a fully automated python module to optimize a parameters and BFImax. The application to the two area show diverse parameter sets and different baseflow according to seasonality and flow conditions representing the flow characteristics. This study could be a fundamental tool for detailed watershed management decisions regarding water security in the dry season or environmental water for aquatic ecosystems. [ABSTRACT FROM AUTHOR]

Glass sagging is a subsequent process to the CVD process used for large‐size and high‐purity silica glass synthesis. Physical phenomena taking place in this process are complicated which need an in‐depth understanding for better control. In this paper, a comprehensive study is conducted for the sagging process using a level‐set and enthalpy‐porosity coupled model. With this model, the deforming behavior of glass ingot and evolution of OH uniformly distributed region are well predicted. Then, two performance indices (the effective yield rate and maximum extension radius of OH uniformly distributed region) are proposed based on different applications, and important factors, including geometrical parameters (the ingot initial length, crucible diameter and pedestal height) and operating parameter (the heater power allocation scheme), are explored for their effects on the two indices. The orthogonal test design method is adopted to further determine the collective effects of the four factors. According to the range analysis results, the initial ingot length has the greatest effect, while the crucible diameter has the least effect on the effective yield rate; and for the maximum extension radius, the crucible diameter becomes the major factor, while the pedestal height is the most insensitive factor. The corresponding optimal schemes are proposed for the two indices finally, which are believed to provide useful guidance for improving the sagging process. [ABSTRACT FROM AUTHOR]

In software defined networks (SDN) packet data switches are configured by a limited number of SDN controllers, which respond to queries for packet forwarding decisions from the switches. To enable optimal control of switches in real time the placement of controllers at network nodes must guarantee that the controller‐to‐controller and switch‐to‐controller communications delays are bounded. Apart from the primary controllers that control the switches in the nominal state, separate backup controllers can be introduced that take over when the primary controllers are unavailable, and whose delay bounds are relaxed. In this paper, we present optimization models to jointly optimize the placement of primary and backup controllers in long‐distance SDN networks, aimed at maximizing the network's resilience to node‐targeted attacks. Applying the models to two well‐known network topologies and running a broad numerical study we show that, when compared with the standard approach of using only primary controllers, the use of backup controllers provides significant resilience gains, in particular in case of tight delay bounds. [ABSTRACT FROM AUTHOR]

In this study, we used experimental analysis and numerical simulation to describe and compare the convective drying (CD) of banana slices, without and with pretreatment with ultrasound (US) at 25 kHz. Banana slices, with an average initial thickness of about 6.60 × 10−3 m and an average diameter of about 3.01 × 10−2 m, were subjected to CD at temperatures of 60, 70, and 80°C, with air speed of 1.5 m s−1. Considering such dimensions, the one‐dimensional diffusion equation in Cartesian coordinates was numerically solved by the finite volume method, using a fully implicit formulation (direct problem). A solver with a numerical solution was developed for the direct problem. This solver was coupled to an optimizer to determine the parameters a and b of functions that relate the effective moisture diffusivity (D) with the local moisture ratio, and also to determine the convective mass transfer coefficient (h) (inverse problem), considering the shrinkage. The proposed model was used to describe the data obtained. The results revealed that the drying rate increased in samples that were subjected to pretreatment with US, for each drying temperature. The best‐simulated results were those that related D to the local moisture ratio by means of a bcosh (aMR2) function. It could be observed that pretreatment with US allowed saving of time (and consequently energy) of 28.3%, 16.0%, and 12.4% at drying temperatures of 60, 70, and 80°C, respectively. Practical applications: The main contribution of this paper is to present a solver and an optimizer to determine the mass transfer properties considering the shrinkage during convective drying of banana pieces pretreated with ultrasound by the inverse problem. With the information obtained for the mass transfer properties and the proposed numerical model with a hyperbolic cosine type function for the effective moisture diffusivity, it is possible to more accurately determine the time and, therefore, the energy savings of processing banana chips pre‐treated with ultrasound. [ABSTRACT FROM AUTHOR]

This paper proposes a second‐order modifier adaptation optimization based on the transfer model, which aims to improve the optimization efficiency. Although the traditional modifier adaptation strategy adds a bias to the model to meet the necessary condition of optimality (NCO), approximating only to the first‐order may neglect some key higher‐order information. Making use of as much higher‐order information as possible is an effective way to improve the efficiency of optimization. For this issue, by introducing the second‐order information into the modifier adaptation method to compensate the mismatch of higher‐order information during the optimization, the compensation of the mismatch between model and plant can get accelerated, thus improving the optimization efficiency. To overcome the difficulty of insufficient data for new process modelling, a process transfer model is also used to fit the relationship between manipulated variables and final product quality. The simulation study of the cobalt oxalate synthesis process shows that this strategy has better optimization efficiency. [ABSTRACT FROM AUTHOR]

Microgrid has attracted more and more attention to provide backup power for customers in the case of power grid outages. Microgrid expansion planning is significant to handle the increasing customer demand and to enhance power resilience. Current research about long‐term microgrid expansion planning rarely if ever considered the uncertainties associated with energy storage and power generation units, for example, battery cycle degradation. These factors have important influence on the performance of microgrid expansion planning in reality. In this paper, a long‐term microgrid expansion planning model with multiple energy resource is presented. Deep reinforcement learning method is used to obtain the cost‐effective microgrid expansion policies to enhance power resilience. In the case study, optimal microgrid expansion planning is achieved based on the proposed model. The impacts of battery degradation and resilience constraint on microgrid expansion policy optimization are also investigated. The simulation results prove the effectiveness of the proposed method on economic and resilient microgrid expansion planning. [ABSTRACT FROM AUTHOR]

Response surface methodology (RSM) is a widely used mathematical and statistical technique for modeling and optimizing the process for the extraction of bioactive compounds. This review explains the optimization approach through the use of experimental design and empirical models for response prediction and the utilization of the desirability function for multiple response optimization. This paper also reviews recent studies on the application of RSM to optimize bioactive compound extraction processes such as conventional solvent extraction, microwave‐assisted extraction, supercritical fluid extraction, and ultrasound‐assisted extraction. Finally, the challenges associated with the use of RSM and the efforts made to improve RSM in the extraction process are also highlighted. Overall, this review informs many aspects of RSM that are occasionally ignored or insufficiently discussed with regard to the optimization of bioactive compound extraction processes, and it summarizes significant applications where RSM proved suitable. © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

In this paper, the selective laser sintering process was used to fabricate the TiO2/PA12 nano‐composite parts by considering the parameters of laser power, scanning speed, and TiO2 content. The response surface methodology was used to improve the mechanical properties of TiO2/PA12 nano‐composite parts. The fracture surface characteristics of the specimens were examined using the scanning and transmission electron microscopy. The results indicated that the increase in laser power from 10 to 15 W improved the tensile strength, modulus, and impact strength of the nano‐composite parts because of the fine dispersion of TiO2 nano‐particles. An increase in the scanning speed from 2000 to 3000 mm/s resulted in the reduction of tensile strength and modulus due to lower heat input and consequently incomplete densification of polyamide‐12. In addition, the increase of TiO2 content up to 5 wt% can improve the tensile strength, modulus, and impact strength, but requires increasing the laser power. However, the mechanical properties of the nano‐composite parts were enhanced simultaneously at laser power of 12.4 W, scanning speed of 2000 mm/s and TiO2 content of 1.9 wt%. Moreover, the addition of TiO2 up to 5 wt% showed a slight influence on thermal stability and crystallinity of the sintered specimens. [ABSTRACT FROM AUTHOR]