The remote sensing ecological index (RSEI) has been widely used in the rapid monitoring and evaluation of the regional ecological environment; however, the research on the main factors that cause changes in RSEI and the impact of human activities in the mining area on RSEI is not often explored. To this end, this paper selected the Landsat (TM/OLI) series of remote sensing images from 1986 to 2022; extracted the four important indicators of the normalized difference vegetation index (NDVI), the wetness component of the tasseled cap transformation (WET), normalized difference built-up and soil index (NDBSI), and land surface temperature (LST); calculated the remote sensing ecological index (RSEI) based on the principal component analysis method; monitored and evaluated the ecological environment changes in the Shendong Mining Area for a period of 36 years; and analyzed the driving forces that cause these ecological environment changes. The results show the following: (1) The ecological... [more]

When designing a new type of power plants operating on pulsed detonations of gaseous or liquid fuels, the concept of fast deflagration-to-detonation transition (FDDT) is used. According to the concept, a flame arising from a weak ignition source must accelerate so fast as to form an intense shock wave at a minimum distance from the ignition source so that the intensity of the shock wave is sufficient for fast shock-to-detonation transition by some additional arrangements. Hence, the FDDT concept implies the use of special means for flame acceleration and shock wave amplification. In this work, we study the FDDT using a pulsed detonation tube comprising a Shchelkin spiral and a helical tube section with ten coils as the means for flame acceleration and shock amplification (focusing), respectively. To attain the FDDT at the shortest distances for fuels of significantly different detonability, the diameter of the pulsed detonation tube is taken close to the limiting diameter of detonation... [more]

Machine learning assists with food process optimization techniques by developing a model to predict the optimal solution for given input data. Machine learning includes unsupervised and supervised learning, data pre-processing, feature engineering, model selection, assessment, and optimization methods. Various problems with food processing optimization could be resolved using these techniques. Machine learning is increasingly being used in the food industry to improve production efficiency, reduce waste, and create personalized customer experiences. Machine learning may be used to improve ingredient utilization and save costs, automate operations such as packing and labeling, and even forecast consumer preferences to develop personalized products. Machine learning is also being used to identify food safety hazards before they reach the consumer, such as contaminants or spoiled food. The usage of machine learning in the food sector is predicted to rise in the near future as more busines... [more]

The development and optimization of lipid nanoparticle (LNP) formulations through hydrodynamic mixing is critical for ensuring the efficient and cost-effective supply of vaccines. Continuous LNP formation through microfluidic mixing can overcome manufacturing bottlenecks and enable the production of nucleic acid vaccines and therapeutics. Predictive process models developed within a QbD Biopharma 4.0 approach can ensure the quality and consistency of the manufacturing process. This study highlights the importance of continuous LNP formation through microfluidic mixing in ensuring high-quality, in-specification production. Both empty and nucleic acid-loaded LNPs are characterized, followed by a TFF/buffer exchange to obtain process parameters for the envisioned continuous SPTFF. It is shown that LNP generation by pipetting leads to a less preferable product when compared to continuous mixing due to the heterogeneity and large particle size of the resulting LNPs (86−104 nm). Particle siz... [more]

Pharmaceutical manufacturing processes are moving towards automation and real-time process monitoring with the help of process analytical technologies (PATs) and predictive process models representing the real system. In this paper, we present a digital twin developed for an adjuvant manufacturing process involving a microfluidic formation of lipid particles. The twin uses a hybrid model for estimating the current state of the process and predicting system behavior in real time. The twin is used to control the adjuvant particle size, a critical quality attribute, by varying process parameters such as the temperature and inlet flow rates. We describe steps in the design and implementation of the twin, starting from the conception of the mechanistic model, up to the generation of its surrogate model used as state estimator, PATs and the setup of the information technology—Operational technology architecture. We demonstrate the performance of the twin by introducing different disturbances... [more]

For tunnel-support engineering, the bed separation of surrounding rock has a great influence on the support performance of bolts. In order to reveal the mechanical properties of the full-grouted prestressed bolt under the influence of bed separation, three typical working conditions of single-separation, multi-separation and different separation positions were set up, and theoretical models and numerical models were established. Furthermore, the characteristics of bolt axial force and anchorage−interface shear stress were analyzed by numerical method, and the sensitivity based on an orthogonal test was studied by means of range analysis and variance analysis. The results showed that: (1) under the single-separation condition, the separation value has a significant effect on the mechanical properties of the bolt, and with the increase in the separation value, the sliding failure unit of the bolt increases; (2) for multi-separation conditions, if the total separation value is the same, t... [more]

Humankind has been unknowingly utilizing food fermentations since the first creation of bread, cheese, and other basic foods. Since the beginning of the last century, microbial fermentation has been extensively utilized for production of commodity chemicals. It has also gained substantial interest in recent decades due to its underlying applications in the preparation of natural and safe food ingredients including enzymes, antimicrobial agents, vitamins, organic acids, sweeteners, stabilizers, emulsifiers, oligosaccharides, amino acids, and thickening agents. In addition, some novel food ingredients that were conventionally made from some other sources such as plant tissue cultures or animals are now being introduced in the industry as ‘fermentation products.’ Some examples of such novel fermentation food ingredients include flavonoids, cultured meat products, food colorants, antioxidants, lipids, and fatty acids. This review summarizes some of the most prominent food ingredients and n... [more]

Thermoelectric technology is an effective strategy to convert low−grade waste heat to electrical energy directly. Thermoelectric generators (TEGs) have been extensively studied in various waste heat scenarios, such as vehicle exhaust, metal casting processes and more. However, industrial pipelines also possess high levels of heat and wide distribution, yet there is limited research on TEGs for use in these pipes. The challenge in designing a TEG lies in the heat collector, which is complicated by the distinct structural differences between pipe and plate−shaped TEMs. Ultimately, we propose an arch bridge−shaped heat collector for the pipe to recover wasted thermal energy. The effects of some key factors, such as topology of TEMs, heat source temperature, cooling water temperature and velocity, on the generating performance are studied. The TEG achieved a temperature difference of 65.98 °C across the two ends of the TEM, resulting in an output power of 17.89 W at an open−circuit voltage... [more]

In this paper, the effect of changes in the thermal conductivity of porous electrodes in three coordinate directions on the capability of proton exchange membrane fuel cells is investigated on the basis of current density versus voltammetry curves, and the temperature distribution and water-carrying capacity distribution of the membrane. The results show that when the cell discharge voltage of the PEMFC is 0.3 V, the thermal conductivity in the Z-direction of the porous electrode has a greater effect on the performance of the PEMFC than in the other directions, with the thermal conductivity in the X- and Y-directions of the porous electrode having less than a 5% effect on the performance of the PEMFC, which can therefore be neglected. When the thermal conductivity of the porous electrode in the Z-direction of the PEMFC is 500 W/(m·K) and 1000 W/(m·K), the performance of the PEMFC is improved by 5.78% and 5.87%, respectively, and when the thermal conductivity of the porous electrode in... [more]

Five-phase induction motors have the characteristics of high torque density, low torque ripple, and flexible control, making them suitable for medium- and low-voltage power supply situations. However, with the expansion of application scenarios, five-phase motors need to cope with increasingly complex operating conditions. Five-phase motors for propeller propulsion will face various complex sea conditions during actual use, and five-phase motors for electric vehicles will also face various complex road conditions and operating requirements during use. Therefore, as a propulsion motor, its speed control system must have strong robustness and anti-disturbance performance. The use of traditional PI algorithms has problems, such as poor adaptability and inability to adapt to various complex working conditions, but the use of an active disturbance rejection controller (ADRC) can effectively solve these problems. However, due to the significant coupling between the variables of induction mot... [more]

Mushrooms have a long history of use as food and medicine. They are rich in various nutrients and bioactive compounds, particularly phenolic compounds. In this study, ten mushroom species were selected, and solvent extraction using 80% ethanol was used to extract phenolic compounds. Total phenolic content (TPC), total flavonoid content (TFC) and total condensed tannin content (TCT) were measured to evaluate phenolic content in different mushroom varieties. In the mushroom varieties tested, brown portobello mushroom had the highest TPC (396.78 ± 3.12 µg GAE/g), white cup mushroom exhibited the highest TFC (275.17 ± 9.40 μg CE/g), and shiitake mushroom presented the highest TCT (13.80 ± 0.21 µg QE/g). Antioxidant capacity was evaluated using 2,2-diphenyl-1-picrylhydrazyl (DPPH), ferric reducing antioxidant power (FRAP), 2,2′-azino-bis-3ethylbenzothiazoline-6-sulfonic acid (ABTS) and total antioxidant capacity (TAC) assays. The highest DPPH free radical scavenging ability was found in whi... [more]

Murals are a significant cultural heritage of humanity, and one of the conservation studies is to control the growth of microorganisms. General biocide agents can be used to preserve murals while also providing new organic carbon sources and increasing environmental pollution. In recent years, radiation technology has shown promising prospects for use in heritage protection. Five microorganisms often found in murals were irradiated with an electron beam in this study, and six mineral pigments were tested for color change, Raman spectra and pigment layer cohesion after irradiation. The result showed that irradiation at 20 kGy can basically eliminate Pseudomonas citronellolis, Bacillus sporothermodurans, Streptomyces vinaceus, and Streptomyces griseolus from the culture medium, but only inhibited the growth of Penicillium flavigenum. Lead white pigment showed a color difference of 5.56 (∆E*97) after irradiation, but lead tetroxide, azurite, malachite, ferrous oxide, and cinnabar showed n... [more]

The Fullbore Formation Micro Imager (FMI) represents a proficient method for examining subterranean oil and gas deposits. Despite its effectiveness, due to the inherent configuration of the borehole and the logging apparatus, the micro-resistivity imaging tool cannot achieve complete coverage. This limitation manifests as blank regions on the resulting micro-resistivity logging images, thus posing a challenge to obtaining a comprehensive analysis. In order to ensure the accuracy of subsequent interpretation, it is necessary to fill these blank strips. Traditional inpainting methods can only capture surface features of an image, and can only repair simple structures effectively. However, they often fail to produce satisfactory results when it comes to filling in complex images, such as carbonate formations. In order to address the aforementioned issues, we propose a multiscale generative adversarial network-based image inpainting method using U-Net. Firstly, in order to better fill the... [more]

This paper concerns the design of a generalized functional observer for Takagi−Sugeno descriptor systems. Furthermore, a generalized structure is herein introduced for purposes of estimating linear functions of the states of descriptor nonlinear systems represented into a Takagi−Sugeno descriptor form. The originality of the functional generalized observer structure is that it provides additional degrees of freedom in the observer design, which allows for improvements in the estimation against parametric uncertainties. The effectiveness of the developed design is illustrated by a nonlinear model of a single link robotic arm with a flexible link. A comparison between the functional generalized observer and the functional proportional observer is given to demonstrate the observer performances.

A novel neural network (NN)-based parallel model predictive control (PMPC) method is proposed to deal with the tracking problem of the quadrotor unmanned aerial vehicles (Q-UAVs) system in this article. It is well known that the dynamics of Q-UAVs are changeable while the system is operating in some specific environments. In this case, traditional NN-based MPC methods are not applicable because their model networks are pre-trained and kept constant throughout the process. To solve this problem, we propose the PMPC algorithm, which introduces parallel control structure and experience pool replay technology into the MPC method. In this algorithm, an NN-based artificial system runs in parallel with the UAV system to reconstruct its dynamics model. Furthermore, the experience replay technology is used to maintain the accuracy of the reconstructed model, so as to ensure the effectiveness of the model prediction algorithm. Furthermore, a convergence proof of the artificial system is also giv... [more]

We present five new sorbents for the evaluation of the pre-concentration of L-carnitine. The sorbents were obtained from copolymerization between butylmethacrylate (BuMA) and ethylene dimethacrylate (EDMA), which were physically modified on their surface by each one of the five synthetized resorcinarenes of variable chain length studied, with long-chain resorcinarenes exhibiting better fixation on the copolymer. The characterization of the synthesized resorcinarenes was done using FTIR-ATR, 1H NMR, 13C NMR, and mass spectrometry, while characterization of the sorbents was done using FTIR-ATR and scanning electron micrography (SEM). The molecular interaction between L-carnitine and the synthesized resorcinarenes was studied in DMSO via 1H-NMR spectroscopy and, in the gas phase, via electrospray ionization-mass spectrometry (ESI-MS). The results showed that the short-chain resorcinarenes underwent a stable interaction with the neurotransmitter. Once the sorption of resorcinarenes on the... [more]

Femtosecond laser machining, characterized by a small heat-affected zone, high precision, and non-contact operation, is ideal for processing metallic glasses. In this study, we employed a simulation method that combines the two-temperature model with molecular dynamics to investigate the effects of fluence and pulse duration on the femtosecond laser ablation of Cu50Zr50 metallic glass. Our results showed that the ablation threshold of the target material was 84 mJ/cm2 at a pulse duration of 100 fs. As the pulse durations increased, the maximum electron temperature at the same position on the target surface decreased, while the electron−lattice temperature coupling time showed no significant difference. As the absorbed fluence increased, the maximum electron temperature at the same position on the target surface increased, while the electron−lattice temperature coupling time became shorter. The surface ablation of the target material was mainly induced by phenomena such as melting, spal... [more]

The concept of digital twinning is essential for smart manufacturing and cyber-physical systems to be connected to the Metaverse. These digital representations of physical objects can be used for real-time analysis, simulations, and predictive maintenance. A combination of smart manufacturing, Industry 4.0, and the Metaverse can lead to sustainable productivity in industries. This paper presents a practical approach to implementing digital twins of a magnetic forging holder that was designed and manufactured in this project. Thus, this paper makes two important contributions: the first contribution is the manufacturing of the holder, and the second significant contribution is the creation of its digital twin. The holder benefits from a special design and implementation, making it a user-friendly and powerful tool in materials research. More specifically, it can be employed for the thermomechanical influencing of the structure and, hence, the final properties of the materials under deve... [more]

Grinding chatter is a kind of self-excited vibration in which the grinding system continuously absorbs energy from the grinding machine, increasing the mechanical energy of the system. Grinding chatter can damage the surface of the workpiece and accelerate the abrasion of the grinding wheel. The theoretical analysis of the grinding chatter for the beam surface was launched based on the behavior of a single abrasive grain, whose cutting thickness is a key factor affecting grinding stability. The dynamic grinding force model has been developed, which is the interaction interface between the grinding wheel and the workpiece. In this paper, rail beam grinding was taken as an example. The vibration performance of the rail beam was described with the Timoshenko beam. The characteristics of the frequency domain of the grinding wheel-workpiece system were observed, and the condition of the stability at any position in the longitudinal direction of the beam was gained, which could be quantitati... [more]

The influence of oligosaccharides (α-cyclodextrin, β-cyclodextrin and γ-cyclodextrin), and a polysaccharide, sodium hyaluronate (NaHy), on the diffusion of aqueous solutions of cobalt and chromium chlorides has been investigated. Cobalt and chromium are constituents of metal alloys for biomedical use, including dental prostheses. Thus, the release of these ions in the human body can lead to harmful biological effects. The interaction of metal ions with saccharides might have information on the role of mouthwashes in preventing these effects. This interaction has been assessed by measuring multicomponent intermolecular diffusion coefficients at 298.15 K. It has been found that β-cyclodextrin has the highest interaction towards cobalt and chromium ions. This work will contribute to unveiling the mechanisms responsible for transport by diffusion in aqueous solutions, and, therefore, mitigating the potential toxicity inherent to those metal ions.

Gas prevention and control have always been the focus of coal mine safety. The pore structure characteristics and gas adsorption characteristics of coal seams are the key factors affecting gas adsorption and diffusion in coal seams. Lvjiatuo Mine has the characteristics of a high gas content when it enters deep mining. In order to clarify the influence of the pore-fracture structure characteristics of main coal seams in the research area on coal seam gas adsorption and diffusion, and to study the differences in gas adsorption and diffusion ability in different coal seams, low-temperature nitrogen adsorption (LT-N2GA), high-pressure mercury intrusion (MIP) and computerized tomography (μ-CT) were used as characterization methods, and methane isothermal adsorption experiments were carried out to systematically study the pore structure characteristics of five groups of coal samples, and the pore-fracture structure characteristics and gas adsorption characteristics of each main coal seam we... [more]

Most industrial processes have nonlinear and time-delay characteristics leading to difficulty in prediction modeling. In addition, the working conditions of most industrial processes are complex, which results in multiple modes. Testing and modeling for each mode is a waste of time and resources. Therefore, it is urgent to complete model migration between different modes. In this work, a new prediction model, a nonlinear autoregressive model with exogenous inputs and back propagation neural network (NARX-BP), is proposed for the nonlinear and time-delay processes, where the input data order of the model is determined by the feedforward neural network (FNN) method, and the nonlinear relation is realized by the BP neural network. For the multi-mode characteristic, a new migration optimization algorithm, input−output slope/bias correction and differential evolution (IOSBC-DE), is provided for using a small amount of data under a new mode to correct the slope and bias of the relationship b... [more]

This study investigates pneumatic conveying of four different biomass materials, namely cottonseeds, wood pellets, wood chips, and wheat straw. The performance of a previously proposed model for predicting pressure drop is evaluated using biomass materials. Results indicate that the model can predict pressure with an error range of 30 percent. To minimize the number of trial tests required, an optimization algorithm is proposed. The findings show that with a combination of three trial tests, there is a 60 percent probability of selecting the right subset for accurately predicting pressure drop for the entire range of tests. Further investigation of different training subsets suggests that increasing the number of tests from 3 to 7 can improve the probability from 60% to 90%. Moreover, thorough analysis of all three-element subsets in the entire series of tests reveals that when considering air mass flow rate as the input, having air mass flow rates that are not only closer in value but... [more]

This study introduces a novel methodology to evaluate the behaviour of biomass material by examining the ratio of aeration and deaeration time constants. To this end, a series of tests were conducted on four different materials, namely, cottonseed, wood chips, wood pellets, and wheat straw, in order to investigate their aeration and deaeration behaviours. The study derives the aeration and deaeration pressure drop equations, and discusses the corresponding time constant expression. Subsequently, the four materials were conveyed in 12 m long batch-fed and continuous pneumatic conveying pipelines to examine their behaviour in longer pipelines. The results indicate that the aeration and deaeration time constants increased with an increase in air superficial velocity. However, the ratio of the aeration and deaeration time constants was identified as a unique number, where a value close to 1 indicates a higher likelihood of plug flow. On the basis of the results, cottonseed, with the lowest... [more]

When transplanting the gas−solid fluidized bed technology to the offshore floating platform, the gas−solid flow characteristics in the bed will be affected by the rolling of the platform. In this paper, the flow field, especially the dynamic variation characteristics of the particles, in a two-dimensional rolling fluidized bed, is investigated using the numerical simulation method. The results show that when the bed is in an inclined position, the gas/particle phases gather in the upper/lower wall region of the inclined bed. During the rolling process of the bed, this behavior results in a periodic change in the gas−solid flow state near the wall region, forming an overall particle internal circulation flow mode of ‘upward flow rate in the upper wall region and downward flow rate in the lower wall region’. The solid holdup in the lower wall region fluctuates at a low amplitude around high values, with a corresponding downward solid flow rate. Meanwhile, the upper wall region has a high... [more]