Unrelated cord blood transplantation (CBT) for Diamond−Blackfan anemia (DBA), a systemic ribosomopathy affecting the disposition of conditioning agents, has resulted in outcomes inferior to those by transplantations from matched donors. We report the experience of the pharmacokinetics-guided myeloablative unrelated CBT in a DBA patient with a germline RPL11 mutation. The conditioning consisted of individualized dosing of fludarabine (based on weight and renal function with a target area under the curve (AUC) of 17.5 mg·h/L) and busulfan (based on therapeutic drug monitoring with a target AUC of 90 mg·h/L), as well as dosing and timing of thymoglobulin (based on body weight and pre-dose lymphocyte count to target pre-CBT AUC of 30.7 AU·day/mL and post-CBT AUC of 4.3 AU·day/mL, respectively). The pharmacokinetic measures resulted in a 27.5% reduction in busulfan and a 35% increase in fludarabine, as well as an over three-fold increase in thymoglobulin dosage with the start time changed t... [more]

In recent years, several high-performance nature-inspired metaheuristic algorithms have been proposed. It is important to study and compare the convergence, computational burden and statistical significance of these metaheuristics to aid future developments. This study focuses on six recent metaheuristics, namely, ant lion optimization (ALO), arithmetic optimization algorithm (AOA), dragonfly algorithm (DA), grey wolf optimizer (GWO), salp swarm algorithm (SSA) and whale optimization algorithm (WOA). Optimization of an industrial machining application is tackled in this paper. The optimal machining parameters (peak current, duty factor, wire tension and water pressure) of WEDM are predicted using the six aforementioned metaheuristics. The objective functions of the optimization study are to maximize the material removal rate (MRR) and minimize the wear ratio (WR) and surface roughness (SR). All of the current algorithms have been seen to surpass existing results, thereby indicating the... [more]

The optimization of industrial processes is a critical task for leveraging profitability and sustainability. To ensure the selection of optimum process parameter levels in any industrial process, numerous metaheuristic algorithms have been proposed so far. However, many algorithms are either computationally too expensive or become trapped in the pit of local optima. To counter these challenges, in this paper, a hybrid metaheuristic called PSO-GSA is employed that works by combining the iterative improvement capability of particle swarm optimization (PSO) and gravitational search algorithm (GSA). A binary PSO is also fused with GSA to develop a BPSO-GSA algorithm. Both the hybrid algorithms i.e., PSO-GSA and BPSO-GSA, are compared against traditional algorithms, such as tabu search (TS), genetic algorithm (GA), differential evolution (DE), GSA and PSO algorithms. Moreover, another popular hybrid algorithm DE-GA is also used for comparison. Since earlier works have already studied the pe... [more]

Chemical absorbents with low-energy requirements have become the primary focus of the research on CO2 capture from flue gas in power plants. To verify the absorption performance of the NICE absorbent developed by the National Institute of Clean-and-Low-Carbon Energy in China, a performance optimization test was conducted in Zhejiang University’s pilot-scale platform, and the effects of the liquid−gas ratio, regeneration pressure, rich liquid fractional flow, and interstage cooling on the absorption performance and regeneration energy consumption were investigated. The results showed that in the CO2 pilot test, the optimized minimum regeneration energy consumption was 2.85 GJ/t CO2, and the corresponding process parameters were as follows: a liquid−gas ratio of 1.82 L/m3, regeneration pressure of 191 kPa, an interstage cooling temperature of 40 °C, and a rich liquid fractional flow ratio of 0.18. This study preliminarily verified the low-energy consumption performance of the NICE absorb... [more]

With the increasing demand for high-efficient continuous casting, parameter optimization during high-speed continuous casting is critical. To clarify the changes in flow characteristics in a multistrand tundish and the optimization principles for the diversion wall, a numerical investigation of an eight-strand tundish during continuous casting of billet was carried out in this paper. The simulation results were validated with the physical results of a 1:3 water model experiment. The results show that, for a tundish with the same flow control device, the average residence time and the maximum residence time difference of liquid steel in different strands are significantly reduced with higher casting speed. At different casting speeds, the effect of the hole diameter and deflection angle of diversion wall on the average residence time and the dead region proportion is very minor, while that on the maximum residence time difference of liquid steel in different strands is significant. For... [more]

Profitably managing inventories is always a big challenge for retailers in the current context of transparent and competitive business. A general retailer always needs to handle both deteriorating and non-deteriorating products simultaneously to run a business. Deterioration of products sometimes impacts a retailer’s profits badly—a situation which can be alleviated by implementing proper preservation technology. In addition, to improve profits and minimize costs, a retailer always seeks some credit facilities (e.g., advance payment, trade credit facilities, etc.) from the supplier to continue the business smoothly with minimum investment. Advance payment is renowned for preventing the possibility of business orders being canceled and helping the retailer to minimize the risk of investing significant amounts at a single time. The foremost objective of this research is to analyze the facilities of advance payment and preservation technology investment and concurrent attempts to deal wit... [more]

Based on the chaos algorithm and immune algorithm theory, an adaptive chaotic immune optimization algorithm (ACIOA) with a mutative scale was proposed and subsequently validated by the experiment result in this paper, and then the adaptive chaotic immune optimization algorithm with mutative scale was applied to investigate the performance characteristics of the medium-frequency induction furnace. The obtained results include the effects on the performance characteristics of a medium-frequency induction furnace of the diameter of the heated cylindrical material, the thickness of the crucible wall, the fullness degree of the induction coil, the ratio of diameter to current penetration depth, and the power frequency. The results showed that the optimization algorithm could continuously modify the variable search space and take the optimal number of cycles as the control index to carry out the search. In addition, the suitable ratio of diameter to current penetration depth was between 3.5... [more]

This study proposes a virgin structure of Fuzzy Logic Control (FLC) for Load Frequency Control (LFC) in a dual-area interconnected electrical power system. This configuration benefits from the advantages of fuzzy control and the merits of Fractional Order theory in traditional PID control. The proposed design is based on Fuzzy Cascade Fractional Order Proportional-Integral and Fractional Order Proportional-Derivative (FC FOPI-FOPD). It includes two controllers, namely FOPI and FOPD connected in cascade in addition to the fuzzy controller and its input scaling factor gains. To boost the performance of this controller, a simple and powerful optimization method called the Particle Swarm Optimization (PSO) algorithm is employed to attain the best possible values of the suggested controller’s parameters. This task is accomplished by reducing the Integral Time Absolute Error (ITAE) of the deviation in frequency and tie line power. Furthermore, to authenticate the excellence of the proposed F... [more]

Recovering energy from waste is a positive element in the operation of a waste incineration plant. Hazardous waste is a very diverse group, including in terms of its fuel properties. Carrying out the thermal process in this case is associated with the difficulty in maintaining stable conditions. This may translate into the efficiency of energy recovery from waste. The article presents a tool supporting the work of hazardous waste incineration plant operators, the aim of which is to select waste for a batch of input material in a manner that ensures process stability and efficient energy recovery. The tool is an application in which the bee algorithm is implemented. It selects the optimal solution to the problem, in accordance with the assumed parameters. The application tests in laboratory conditions were satisfactory and indicated compliance with the assumptions and stability of the solution.

Pharmaceutical products in water, also known as personal pharmaceutical products or PCPPs, are developing contaminants that have the potential to impair human health and the environment in a variety of ecosystems. In this work, waste date stones, a waste product obtained from the seedless dates manufacturing industry, were used to make acid-activated carbon. This material has been utilized to extract the medicinal component ibuprofen from water, with a high adsorption capacity of 126 mg ibuprofen per g of waste date stone-generated activated carbon. A design study was conducted to minimize the amount of activated carbon required, utilizing a two-stage batch adsorption system to optimize the usage of the activated carbon. To test the model and compare the quantities of adsorbent required in the two-stage and single-stage systems under various conditions, several variables were entered into the design model.

In this work, the emulsification of oil-in-water two-phase systems with three emulsifiers (PEG1500, 6000 and 20000) was studied in a batch macro system and in a continuously operated microfluidic system. The effect of emulsifier concentration, oil concentration and mixing rate on zeta potential and average Feret diameter was analyzed for the macro-batch system, while the effect of emulsifier concentration, oil concentration and total flow rate on zeta potential and average Feret diameter was analyzed for the microfluidic system. The emulsions prepared in batch system were more stable, had smaller droplet diameter but higher values of polydispersity index (PDI) compared to those prepared by continuous method. In both cases, batch and continuous, the use of PEG with higher molecular weight resulted in emulsions with lower zeta potential values. In batch emulsification, all three optimization parameters (emulsifier concentration, oil concentration and mixing rate) had a significant influe... [more]

For the study of the transition strategies of continuous chemical processes, both continuity and dynamic characteristics in the physical sense are critical. The continuous transition strategy has a higher information density and can describe the real situation as closely as possible. In addition, the accuracy of the dynamic characteristics is necessary because the process transition is the study of the dynamic system processes. However, existing transition strategies have certain shortcomings. Dynamic optimization can obtain transition strategies with different characteristics but no physical meaning and a frequency domain-based analytical approach can acquire a continuous transition strategy with physical meaning, but its dynamic characteristics are the same. Therefore, by integrating the advantages of the existing strategies, a new transition strategy has been presented, which possesses different dynamic characteristics and continuity synchronous with physical significance. When proc... [more]

In active noise control (ANC) headphones, the audio signal is modified together with the primary noise if a feedback controller is used. Although this problem can be alleviated with an FIR model of the secondary path, practical implementations are usually restricted by its computational complexity. In this paper, cascade biquad filters are used to compensate for the modification of the audio system. Instead of using classical identification methods with an IIR model, the audio compensation problem is fixed through an optimization process. An objective function evaluating the comprehensive compensation performance is proposed, whose minimum value is obtained using the differential evolution (DE) algorithm. Simulations and experiments are carried out, whose results validate the effectiveness and efficiency of the proposed optimization method. The averaged compensation error can be reduced to about 0.5 dB with only two to five biquad filters.

The use of wind power generation can reduce the pollution in the environment and solve the problem of power shortages on offshore islands, grasslands, pastoral areas, mountain areas, and highlands. Wind speed forecasting plays a significant role in wind farms. It can improve economic and social benefits and make an operation schedule for wind turbines on large wind farms. This paper proposes a combined model based on the existing artificial neural network algorithms for wind speed forecasting at different heights. We first use the wavelet threshold method with the original wind speed dataset for noise reduction. After that, the three artificial neural networks, extreme learning machine (ELM), Elman neural network, and Long Short-term Memory (LSTM) neural network, are applied for wind speed forecasting. In addition, the variance reciprocal method and social cognitive optimization (SCO) algorithm are used to optimize the weight coefficients of the combined model. In order to evaluate the... [more]

The heat integration feasibility of the proton exchange membrane fuel cell (PEMFC) coupled with the solar-heated direct contact membrane distillation (DCMD) module is evaluated in this study. The additional waste heat from the PEMFC increases the DCMD system’s ability to produce fresh water and electricity. Two systems units to be assessed mainly include a flat plate solar collector, a heat storage tank with an internal heat exchanger, and the DCMD module with and without the PEMFC module. The importance of daily operation continuity is emphasized through a preliminary dynamic simulation and proper sizing of the solar-heated DCMD distillation. Sensitivity analysis is implemented to analyze the relationship between the essential variables and the daily freshwater production. The design variables of both configurations are rigorously optimized in terms of minimum unit production cost (UPC). The proposed heat integration feasibility is evaluated to obtain critical insights on the design s... [more]

Production and business enterprises are aiming to improve their logistics activities in order to increase competitiveness. Therefore, the criteria and decision support models for selecting logistics service providers are significant to businesses. Fuzzy theory has been applied to almost all industrial engineering fields, such as decision making, operations research, quality control, project scheduling and many more. In this research, the authors combined fuzzy theory and a Multicriteria Decision Making (MCDM) model for the evaluation and selection of potential third-party logistics (3PL) providers. The goal is to take the advantages of these approaches and allow for more accurate and balanced (symmetric) decision making through their integration. The main contribution of this study is that it develops a complete approach to assessing the quality of the logistics service industry. The combined method of the SERVQUAL and FAHP−TOPSIS models not only provides reasonable results, but it als... [more]

This study introduces an integrated decision-making methodology to choose the best “waste-to-energy (WTE)” technology for “municipal solid waste (MSW)” treatment under the “interval-valued Pythagorean fuzzy sets (IPFSs)”. In this line, first, a new similarity measure is developed for IPFSs. To show the utility of the developed similarity measure, a comparison is presented with some extant similarity measures. Next, a weighting procedure based on the presented similarity measures is proposed to obtain the criteria weight. Second, an integrated approach called the “interval-valued Pythagorean fuzzy-complex proportional assessment (IPF-COPRAS)” is introduced using the similarity measure, linear programming model and the “complex proportional assessment (COPRAS)” method. Furthermore, a case study of WTE technologies selection for MSW treatment is taken to illustrate the applicability and usefulness of the presented IPF-COPRAS method. The comparative study is made to show the strength and s... [more]

An important requirement of wastewater treatment plants (WWTPs) is compliance with the local regulations on effluent discharge, which are going to become more stringent in the future. The operation of WWTPs exhibits a trade-off between operational cost and effluent quality, which provides a scope for optimization. Process optimization is usually done by optimizing a model of the process. However, due to inevitable plant−model mismatch, the computed optimal solution is usually not optimal for the plant. This study represents the first attempt to handle plant−model mismatch via constraint adaptation (CA) for the real-time optimization of WWTPs. In this simulation study, the “plant” is a model adopted from the BSM1 benchmark, while a reduced-order “model” is used for making predictions and computing the optimal inputs. A first implementation uses steady-state measurements of the plant constraints to adjust the model in the optimization framework. A fast CA technique is also proposed, whic... [more]

One of the consequences of the widespread automation of manufacturing operations has been the proliferation and availability of historical databases that can be exploited by analytical methods to improve process understanding. Data science tools such as dimension reduction and clustering are among many such approaches that can aid in the identification of unique process features and patterns that can be associated with faulty states. However, determining the number of such states still requires significant engineering knowledge and insight. In this study, a new unsupervised method is proposed that reveals the number of classes in a data set. The method utilizes a variety of dimension reduction techniques to create projections of a data set and performs multiple clustering operations on the lower-dimensional data as well as the original data. The relevant internal clustering metrics are incorporated into a multi-objective optimization problem to determine the solutions that simultaneous... [more]

In a world overwhelmed with unstructured information, logistics companies increasingly depend on their websites to acquire new customers and maintain existing ones. Following this rationale, a series of technical elements may set the ground for differentiating one logistics website from another. Nevertheless, a suitable digital marketing strategy should be adopted in order to build competitive advantage. In this paper, the authors attempt to respond by implementing an innovative methodology building on web analytics and big data. The first phase of the research collects data for 180 days from 7 world-leading logistics companies. The second phase presents the statistical analysis of the gathered data, including regression, correlations, and descriptive statistics. Subsequently, Fuzzy Cognitive Mapping (FCM) was employed to illustrate the cause-and-effect links among the metrics in question. Finally, a predictive simulation model is developed to show the intercorrelation among the metric... [more]

Focused on the troubles and defects introduced by the traditional single form of electric vehicle transmission, this paper proposes an electro-hydraulic power coupled electric vehicle based on the working principle of an electro-hydraulic power integrated drive system for light-duty cargo vehicles. The integration of the planetary row into the drive system allows the interconversion of mechanical, electrical, and hydraulic energy. By describing the system structure and composition, several working conditions during automobile driving are proposed, and the working principle of every circumstance is introduced. Simultaneously, the article determines the preliminary optimal ratio with the battery’s state of charge (SOC) as the constraint. Then, the orthogonal test matrix of electro-hydraulic ratios and speed thresholds for each operating condition is established according to Taguchi’s method. The impact of each optimized parameter on the motor torque and hydraulic torque as well as the SO... [more]

In the era of Industry 4.0, numerous AI technologies have been widely applied. However, implementation of the AI technology requires observation, analysis, and pre-processing of the obtained data, which takes up 60−90% of total time after data collection. Next, sensors and features are selected. Finally, the AI algorithms are used for clustering or classification. Despite the completion of data pre-processing, the subsequent feature selection and hyperparameter tuning in the AI model affect the sensitivity, accuracy, and robustness of the system. In this study, two novel approaches of sensor and feature selecting system, and hyperparameter tuning mechanisms are proposed. In the sensor and feature selecting system, the Shapley Additive ExPlanations model is used to calculate the contribution of individual features or sensors and to make the black-box AI model transparent, whereas, in the hyperparameter tuning mechanism, Hyperopt is used for tuning to improve model performance. Implement... [more]

Background: While there is evidence on the effectiveness of optimized treatment processes for patients receiving hip and knee endoprostheses, feasibility in various settings has not been adequately investigated. The multicenter PROMISE Trial (Process optimization by interdisciplinary and cross-sectoral care using the example of patients with hip and knee prostheses) was set up to fill this gap. Methods: A complex optimized process was implemented in three German hospitals offering different levels of care and five cooperating rehabilitation centers. For the feasibility question, data on 19 parameters characterizing the defined process were collected. The extent of cross-sectoral collaboration was a special focus. Results: The data show, for almost all parameters in all facilities, an implementation rate of more than 80% with missing data below 5%, n = 1887 study participants. A total of 96.8% attended a rehabilitation program, and for 29.2% rehabilitation took place in a PROMISE-collab... [more]

A selection of suitable sustainability management systems (SMS) is a major part of supply chain strategies to create a competitive advantage, reduce total costs, and manage long-term sustainability. A framework and method for prioritizing supply chain SMSs are presented in this research. Analytic hierarchy process (AHP) is the most common method for alternative selection in multi-criteria decision-making (MCDM). However, complex information is mixed with ambiguity and uncertainty, which makes decision makers unable to use precise or crisp numbers, so fuzzy numbers are presented to remedy this difficulty. Therefore, this research proposes a fuzzy additive preference programming (FAPP) to select the optimum SMS for a supply chain. FAPP method can produce the unique normalized optimal priority vector of fuzzy pairwise comparison matrices for SMS selection effectively with linear constraints. The additive linear constraints can eliminate the weaknesses of existing methods and equalize the... [more]

As an important combustion aid for aerospace vehicles, subcooled liquid oxygen of high density can be used to increase loading capacity of a spacecraft. Providing a large amount of cryogenic propellant in a short time with a strict energy consumption limitation is a challenge in the design of the fuel filling system. The authors proposed a vacuumed subcooling system combined with an ejector and liquid ring pump to vacuum a liquid oxygen tank and obtain subcooled liquid oxygen. After the liquid oxygen tank is vacuumed to an intermediate pressure by the ejector, it is further vacuumed to 10 kPa using the liquid ring pump. The infinitesimal method was used to simulate the thermodynamic processes involved. Taking the ejector working fluid mass flow rate, jet pressure, intermediate pressure, initial tank liquid level, and liquid ring pump speed as optimizing variables, optimization was conducted to determine the optimal vacuuming time, remaining liquid level in the tank, pumping speed diffe... [more]