This paper focuses on the use of AI in various MEMS (Micro-Electro-Mechanical System) biosensor types. Al increases the potential of Micro-Electro-Mechanical System biosensors and opens up new opportunities for automation, consumer electronics, industrial manufacturing, defense, medical equipment, etc. Micro-Electro-Mechanical System microcantilever biosensors are currently making their way into our daily lives and playing a significant role in the advancement of social technology. Micro-Electro-Mechanical System biosensors with microcantilever structures have a number of benefits over conventional biosensors, including small size, high sensitivity, mass production, simple arraying, integration, etc. These advantages have made them one of the development avenues for high-sensitivity sensors. The next generation of sensors will exhibit an intelligent development trajectory and aid people in interacting with other objects in a variety of scenario applications as a result of the active de... [more]

This work focused on the optimization of the ultrasound (US) extraction of polyphenols from sweet cherry pulp by monitoring cyanidin-3O-rutinoside, quercetin-3O-rutinoside, and trans-3-O-coumaroylquinic acid, representing the main anthocyanin, flavonol, and hydroxycinnamate, respectively, identified in the extracts through chromatographic analyses (HPLC-DAD), as output variables. The optimization was performed following a two-level central composite design and the influence of the selected independent variables (i.e., extraction time and solid to solvent ratio) was checked through the response surface methodology. The maximum recovery of the phenolic compounds was obtained at 3 min and 0.25 g/mL in water/ethanol (1:1, v/v) at a set temperature (25 °C), sonication power (100 W), and sonication frequency (37 kHz). Subsequent validation experiments proved the effectiveness and reliability of the gathered mathematical models in defining the best ultrasound-assisted extraction conditions.

In this brief, we consider the mean-field type H− index problem for stochastic Markovian jump systems. A sufficient condition is derived for stochastic Markovian jump systems with (x,u)-dependent noise based on generalized differential Riccati equations. Especially for stochastic Markovian jump systems with only x-dependent noise, a sufficient and necessary condition is developed to characterize H− index larger than some ξ>0. Finally, a numerical example is addressed to verify the effectiveness of our obtained results.

Agricultural productivity plays a vital role in a country’s economy, which can be increased by providing the proper water needed for crops. Proper water provision ensures suitable moisture and appropriate conditions essential for crops, water resource preservation, minimized water wastage, and energy consumption. However, adequate water provision is challenging due to intermittent and uncertain environmental and weather conditions. On this note, a model with uncertain and stochastic conditions (rain, wet, dry, humidity, and moisture) capturing abilities is needed. Thus, a smart-sensors-based solar-powered system is developed for monitoring and controlling the tube well that ensures proper water provision to crops. The developed system properly checks weather and environmental conditions (rain, temperature, irradiance, humidity, etc.), soil conditions (wet or dry), and crop conditions to monitor and regulate water flow accordingly to minimize water and energy consumption wastage. The de... [more]

Identifying combustion regimes is important for understanding combustion phenomena and the structure of flames. This study proposes a combustion regime identification (CRI) method based on rotated principal component analysis (PCA), clustering analysis and the back-propagation neural network (BPNN) method. The methodology is tested with large-eddy simulation (LES) data of two turbulent non-premixed flames. The rotated PCA computes the principal components of instantaneous multivariate data obtained in LES, including temperature, and mass fractions of chemical species. The frame front results detected using the clustering analysis do not rely on any threshold, indicating the quantitative characteristic given by the unsupervised machine learning provides a perspective towards objective and reliable CRI. The training and the subsequent application of the BPNN rely on the clustering results. Five combustion regimes, including environmental air region, co-flow region, combustion zone, prehe... [more]

Both anthropogenic and natural sources of pollution are regionally significant. Therefore, in order to monitor and protect the quality of Langat River from deterioration, we use Artificial Intelligence (AI) to model the river water quality. This study has applied several machine learning models (two support vector machines (SVMs), six regression models, and artificial neural network (ANN)) to predict total suspended solids (TSS), total solids (TS), and dissolved solids (DS)) in Langat River, Malaysia. All of the models have been assessed using root mean square error (RMSE), mean square error (MSE) as well as the determination of coefficient (R2). Based on the model performance metrics, the ANN model outperformed all models, while the GPR and SVM models exhibited the characteristic of over-fitting. The remaining machine learning models exhibited fair to poor performances. Although there are a few researches conducted to predict TDS using ANN, however, there are less to no research condu... [more]

Currently, the concern for achieving and fulfilling the Sustainable Development Goals (SDGs) is a constant in advanced societies. The scientific community and various organisations are working on obtaining an information system that will make it possible to offer the necessary value to this type of sustainability information. The article aims to incorporate criteria on the technology used in the reporting system, specifically in collecting the different types of data and generating other interfaces. The methods described here are carried out on a specific case study, a Smart City, showing the different types of data that exist and the possible interfaces that allow objective monitoring of the achievement of the SDGs. It is, therefore, a descriptive study of a process whose results are the establishment of criteria concerning the different data sources as well as the generation of a set of interfaces that motivate the monitoring that can be carried out in a specific city to observe its... [more]

Countries have started to aggressively undertake energy structure transformation strategies in order to reach the objective of carbon neutrality. Both clean and efficient coal energy use and clean energy use will be crucial to the process of changing the energy structure since the two cannot be totally replaced within a short period of time. In this study, we quantify emotions as an irrational factor, combine them with an evolutionary game using RDEU theory, and build an evolutionary game model between government regulators and energy consumers. We then analyze how low-carbon emotions of decision-makers affect their choice of strategy and the transformation of the energy structure. The findings support that by affecting the relative importance of each strategic choice, emotions have a profound impact on the evolutionary steady state of the system. Appropriate stress and anxiety can increase decision-makers’ feelings of responsibility, while pleasant emotions frequently support strategi... [more]

Hydraulic fracture networks, especially fracture geometry, height growth, and proppant transport within the networks, present a critical influence on productivity evaluation and optimization of fracturing parameters. However, information about hydraulic fracture networks in post-fractured formations is seldom available. In this study, the characteristics (density and orientation) of hydraulic fractures were obtained from field observations of cores taken from conglomerate hydraulic fracturing test site (CHFTS). A large number of fractures were observed in the cores, and systematic fracture description was carried out. The fracture analysis data obtained includes fracture density, fracture depth, fracture orientation, morphology, fracture surface features, apertures, fill, fracture mechanical origin (type), etc. Our results show that 228 hydraulic fractures were intersected in a span of 293.71 m of slant core and composed of irregularly spaced single fractures and fracture swarms. One o... [more]

The objective of this research work was to investigate the potential of control models based on reinforcement learning in the optimization of solar thermal cooling systems (STCS) operation through a case study. In this, the performance of the installation working with a traditional predictive control approach and with a reinforcement learning (RL)-based control approach was analyzed and compared using a specific realistic simulation tool. In order to achieve the proposed objective, a control system module based on the reinforcement learning approach with the capacity for interacting with the aforementioned realistic simulation tool was developed in Python. For the studied period and the STCS operating with a control system based on RL, the following was observed: a 35% reduction in consumption of auxiliary energy, a 17% reduction in the electrical consumption of the pump that feeds the absorption machine and more precise control in the generation of cooling energy regarding the install... [more]

A large number of microfluidic applications are based on effective mixing. In the application of water purification, the contaminated water needs to be effectively mixed with a solution that is loaded with nanoparticles. In this work, the Tesla valve was used as a micromixer device in order to evaluate the effect of this type of geometry on the mixing process of two streams. For this reason, several series of simulations were performed in order to achieve an effective mixing of iron oxide nanoparticles and contaminated water in a duct. In the present work, a stream loaded with Fe3O4 nanoparticles and a stream with contaminated water were numerically studied for various inlet velocity ratios and initial concentrations between the two streams. The Navier−Stokes equations were solved for the water flow and the discrete motion of particles was evaluated by the Lagrangian method. Results indicate that the Tesla valve can be used as a micromixer since mixing efficiency reached up to 63% for... [more]

An electro-hydraulic servo pump control system realizes the basic action of a hydraulic cylinder by controlling the servo motor, which effectively improves the problems of a traditional valve control system such as high energy consumption, low power-to-weight ratio, and poor anti-pollution ability. However, the static accuracy and dynamic performance of an electro-hydraulic servo pump control system are limited due to the electro-hydraulic coupling and flow nonlinearity. Based on this, in this paper, we establish a mathematical model of an electro-hydraulic servo pump control system. Starting from the internal control mechanism of the system, the Simulink simulation model is established to analyze the dynamic response of the system current loop, speed loop, position loop, and pressure loop. The system parameters are obtained by combining the system dynamic analysis and component technology samples. The position/force control model of the electro-hydraulic servo pump control system is b... [more]

The thermal management of electronic devices has become a major problem in recent years. Therefore, there is a growing need for research on many new materials and innovative fluids due to the developing technology and increasing cooling need in electronic systems. In this paper, heat transfer from a plate fin and pin fin type heat sinks that were placed in a water block that are used in electronic systems was investigated. A base fluid (pure water) and 0.1% mass concentration Al2O3-H2O nanofluid were used as cooling fluids. The experiments were carried out for volumetric flow rates varying between 100 and 800 mL/min and heat flux values of 454.54 W/m2 and 1818.18 W/m2. The results demonstrated that the Al2O3-H2O nanofluid on the empty surface provided a maximum improvement of 10.5% in heat transfer compared to the base fluid. In the use of plate finned heat sink, the maximum amount of improvement in heat transfer compared to the empty surface was obtained approximately 64.25% for the b... [more]

Health monitoring and fault diagnosis of liquid rocket engine (LRE) are the most important concerning issue for the safety of rocket’s flying, especially for the man-carried aerospace engineering. Based on the sensor measurement signals of a certain type of hydrogen-oxygen rocket engine, this paper proposed a real-time fault detection approach using a genetic algorithm-based least squares support vector regression (GA-LSSVR) algorithm for the real-time fault detection of the rocket engine. In order to obtain effective training samples, the data is normalized in this paper. Then, the GA-LSSVR algorithm is derived through comprehensive considerations of the advantages of the Support Vector Regression (SVR) algorithm and Least Square Support Vector Regression (LSSVR). What is more, this paper provided the genetic algorithm to search for the optimal LSSVR parameters. In the end, the computational results of the suggested approach using the rocket practical experimental data are given out.... [more]

In process optimization, a process is adjusted so as to optimize a set of parameters while meeting constraints, with the objective to either minimize the total processing time or maximize the throughput. This article focused on the process optimization of a fully automated yogurt and flavor-filling machine developed based on the industrial revolution 4.0 concept. Mathematical models were developed for minimizing the total processing time or maximizing the throughput of an Industry 4.0-based yogurt filling system with two different machine settings called Case-I and Case-II. In Case-I, the yogurt and flavors are filled at two distinct points while Case-II considers the filling of yogurt and flavors at a single point. The models were tested with real data and the results revealed that Case-II is faster than Case-I in processing a set of customer orders. The results were used as inputs for the single-dimension rules to check which one results in more intended outputs. Additionally, differ... [more]

In order to prepare a novel landfill liner material, we used industrial calcium-containing waste (slag, fly ash, and desulfurized gypsum) to solidify municipal sludge. The mechanical and permeability properties of the solidified sludge material (SSM) were evaluated using straight shear, uniaxial compression, and permeability tests. The hydration products, microscopic morphology, and elemental composition of the SSM after the wet and dry cycles were analyzed using a combination of scanning electron microscopy (SEM + EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). The SSM has high strength and low hydraulic conductivity. The values of cohesion c and internal friction angle φ reached 0.45−3.31 MPa and 6.52−36.28°. The SSM exhibited a compressive strength of 0.93−11.67 MPa and hydraulic conductivity of 4.80 × 10−9−1.34 × 10−7 cm/s. Analysis shows that SiO2, Al2O3, and CaO in industrial calcium-containing solid wastes and sludges produce dense bulk and ag... [more]

The chlor-alkali industries produce caustic soda (NaOH), chlorine (Cl2), and hydrogen (H2) as primary products. In 2021, the global chlor-alkali market was valued at $63.2 billion. The article evaluates the global aspects of chlor-alkali industries and prospects for Bangladesh. The current production capacity of NaOH from the chlor-alkali industries in Bangladesh is around 282,150 metric tons/year (MT/y). The by-products, chlorine (Cl2) of 250,470 MT/y and hydrogen (H2) of 7055 MT/y, are produced domestically. The local demand of Cl2 is 68,779 MT/y. However, there are no systematic utilizations of the residual Cl2 and vented H2, which threatens the sustainability of the chlor-alkali industries. The article prefigures that a 150,000 MT/y PVC plant can utilize 45.2 % of residual Cl2 of chlor-alkali plants, which would be an economical and environmental milestone for Bangladesh. The residual Cl2 can earn revenue of 908 million USD/y, which can be utilized to import ethylene. For the susta... [more]

This study investigated the effects of the addition of chitosan (0−1.0%) or glucono-δ-lactone (GDL) (0−60 mM) on the gel properties, microstructure, and texture of pea-based tofu-type product. Following the addition of 0.5% chitosan or 20 mM GDL, we observed a significant decrease in the hardness and cohesiveness of the tofu, resulting in a slightly discontinuous network structure with pores smaller than those in samples without chitosan or GDL. SDS-PAGE analysis revealed the induced aggregation of pea legumin (11S) and vicilin (7S) subunits (30, 34, and 50 kDa), legumin α subunit (40 kDa), and legumin β subunit (20 kDa) by chitosan or GDL. It appears that chitosan and GDL could potentially be used as food additives for the development of texture-modified pea-based tofu-type products.

Erosion wear is a common failure form of slotted screen in service. In this paper, based on CFD software and sand production data of a gas field in the Tarim Basin, the particle velocity and shear force at the slot of the flow field in the sieve tube were studied to determine the maximum area of erosion; at the same time, the velocity, viscosity, particle size and concentration of sand-carrying fluid were analyzed by orthogonal test, and the regression model of multi-factor maximum erosion rate was established. ① Through the analysis of the four factors on the degree of dependent variables, the order of the primary and secondary factors are: sand-carrying liquid flow rate, particle concentration, fluid viscosity, particle diameter, the effect of fluid viscosity and particle diameter on erosion rate is relatively small; ② According to the analysis of variance and range, the combination scheme of minimum erosion generation is obtained, and the calculation model of the erosion rate of the... [more]

In this study, the dual nature of quaternary ammonium ionic liquid−didecyldimethylammonium perchlorate, [DDA][ClO4], was evaluated. A novel and sensitive in situ ionic liquid dispersive liquid−liquid microextraction method (in situ IL-DLLME) combined with magnetic retrieval (MR) was applied to enrich and separate selected organic micro-pollutants, both polar and non-polar. The magnetic support relied on using unmodified magnetic nanoparticles (MNPs) prepared by the co-precipitation of Fe2+/Fe3+ (Fe3O4). The separation technique was on-lined with high-performance liquid chromatography (HPLC−DAD) verified by inverse gas chromatography. An anion exchanger, NaClO4, was added to form an in situ hydrophobic IL. The fine droplets of [DDA][ClO4], molded in aqueous samples, functioned as an extractant for isolating the studied compounds. Then the carrier MNPs were added to separate the IL from the water matrix. The supernatant-free sample was desorbed in acetonitrile (MeCN) and injected into th... [more]

protein-rich seeds must be debittered before consumption. The aim of this research was to assess free phenolic compounds, antioxidant capacity and FT-NIR spectra of flours from debittered seeds of 33 Andean ecotypes of L. mutabilis, and five varieties belonging to L. luteus, L. angustifolius and L. albus, as controls. The free phenolics were quantified by RP-HPLC, while the antioxidant capacity was evaluated spectrophotometrically through the Reducing Power, ABTS, FRAP and DPPH methods. The free phenolics of L. mutabilis were mostly (85.5−99.6%) flavonoids (genistein and genistein derivatives, apigenin, catechin and naringenin). Other compounds, detected in low quantities, were phenylethanoids (tyrosol and tyrosol derivative) and phenolic acids (cinnamic acid derivatives). The highest total free phenolic concentration was observed in H6 INIA BP (1393.32 mg/kg DM), followed by Chacas, Moteado beige, Huánuco and Lircay. The antioxidant capacity of the L. mutabilis ecotypes exceeded that... [more]

The transformation behaviors of Zn during co-pyrolysis of waste tires and coal were studied in a fixed-bed reaction system. The effects of pyrolysis temperature and the Zn content of coal mixture on the Zn distributions in the pyrolytic products (coke, tar and gas) were investigated in detail. It is found that the relative percentages of Zn in the pyrolytic products are closely related to the contents of S and mineral elements (Ca, Al, Si and Fe) in the coal. The thermodynamic equilibrium simulations conducted using FactSage 8.0 show that S, Al and Si can interact with Zn to inhibit the volatilization of Zn from coke. The reaction sequence with Zn is S > Al > Si, and the thermal stability of products is in the order of ZnS > ZnAl2O4 > Zn2SiO4. These results provide insights into the migration characteristics of Zn during co-pyrolysis of coal and waste tires, which is vital to the prevention and control of Zn emissions to reduce the environmental burden.

Biopharmaceutical and pharmaceutical manufacturing are strongly influenced by the process analytical technology initiative (PAT) and quality by design (QbD) methodologies, which are designed to enhance the understanding of more integrated processes [...]

Source term estimation (STE) is crucial for understanding and addressing hazardous gas leakages in the chemical industry. Most existing methods basically use an atmospheric transport and dispersion (ATD) model to predict the concentrations of hazardous gas leakages from different possible sources, compare the predicted results with multi-sensor data, and use the deviations to search and derive information on the real sources of leakages. Although performing well in principle, complicated computations and the associated computer time often make these methods difficult to apply in real time. Recently, many machine learning methods have also been proposed for the purpose of STE. The idea is to build offline a machine-learning-based STE model using data generated with a high-fidelity ATD model and then apply the machine learning model to multi-sensor data to perform STE in real time. The key to the success of a machine-learning-based STE is that the machine-learning-based STE model has to... [more]

A side channel pump is a pump with a high head and a small flow that is widely used in various industrial fields. Many scientists have studied the hydraulic performance, pressure fluctuation characteristics, and gas-liquid mixed transport characteristics of this type of pump. However, these studies mainly focused on the single-stage impeller of the side channel pump, without considering the inter-stage connection channel and the multistage timing effect. These characteristics affect the hydraulic performance and pressure-pulsation characteristics of the side channel pump. Therefore, we carried out a numerical simulation and an experimental comparison on the multistage side channel pump to explore its flow characteristics during the stages. This study focused on the influence of different turbulence models on the numerical simulation of multistage side channel pumps. Shear stress transport (SST), detached eddy simulation (DES), and detached eddy simulation-curvature correction (DES-CC)... [more]