Peach is a fruit highly appreciated by consumers; however, it is highly perishable, so drying is an alternative to preserve its physical and chemical properties. In this study, the effect of drying in natural and forced convection at three different temperatures (40 °C, 45 °C and 50 °C) and solar drying with two air velocities (1 m/s and 3 m/s) on the color, texture, total phenol content and antioxidant capacity of peach (Prunus persica (L.) Batsch), were evaluated. The experimental data of the drying kinetics were adjusted to five different mathematical models (Page, Logarithmic, Two-term exponential, Wang and Singh, and Verma et al.). The model that best represented the experimental data in natural convection was the Wang and Singh model (r2 > 0.998; RMSE < 0.016; χ2 < 2.85 × 10−4); in forced convection (45 °C and 50 °C), it was the Verma et al. model (r2 > 0.997; RMSE < 0.025; χ2 < 8.12 × 10−4); and finally, for solar drying, it was the Logarithmic model at 3 m/s (r2 = 0.99... [more]

Perovskite is of burgeoning interest in catalysis, principally due to such material having high thermal stability, modifiable variability, ferromagnetism, and excellent catalytic performance in peroxomonosulfate (PMS) activation. In this study, the SrCoMn1−xO3 perovskites with different Mn doping were synthesized by a facile sol-gel method for peroxymonosulfate (PMS) activation to degrade Rhodamine B. The obtained SrCo0.5Mn0.5O3 perovskite exhibited the best catalytic efficiency, as Rhodamine B (40 mg/L) was removed completely within 30 min. In the system of SrCo0.5Mn0.5O3−PMS, several reactive species were produced, among which sulfate radicals and the singlet oxygen mainly contributed to Rhodamine B degradation. The relatively high catalytic performance could be attributed to the coupled redox cycle between Mn and Co, and the abundant oxygen vacancies. Moreover, the SrCo0.5Mn0.5O3 catalyst showed excellent stability and reusability, maintaining a high catalytic activity after several... [more]

Multiple Automated Guided Vehicles promise to be an effective solution for executing tasks such as material transportation and inspection in industrial parks. In particular, system stability is the key to maintaining connectivity among multiple agents. In this paper, we build the stability model of multi-agent system (MAS) under the background of swarm robots transporting materials in an industrial park, and propose a network topology optimization method to improve the stability of MAS. In concrete, we first analyze the effect of channel environment on network topology, and the communication delay is analyzed. Then considering the communication delay and artificial potential field, we establish the stability analysis model of MAS and obtain the stability condition of the MAS by using Lyapunov correlation theorem. Finally, we formulate the network topology optimization problem of MAS by maximizing the second smallest eigenvalue of the Laplacian and get the optimal solutions. Analysis an... [more]

The extract of P. amygdalus var. amara is known for its health benefits, which include lowering diabetes and heart disease risks. In eight human tumor cell lines, P. amygdalus var. amara demonstrated potent anti-cancer activity, including NB4, Huh-7, A-549, SKOV-3, PC-3, T-24, U937, and Hep-2. There was a notable change in the morphology of nearly all cancer cell lines, and cancer cells continued to exist. Incubation for 12 h, 24 h, 48 h, or 72 h resulted in the lowest viable cell concentration at 48 h, which was 34.65% lower than that of the non-treated cells. During exposure to the extract, the majority of cells lost their typical morphology and shrank in size. According to the cell viability data, the P. amygdalus var. amara treatment significantly decreased the cancer cells’ growth in most cancer cell lines when doses and time were taken into consideration.

Using nanoindentation technology to analyze the hardness and elastic modulus distributions of the local microzones within materials, it can be determined that the case-carburized specimen is a composite of the carburized case and the pseudo-carburized material in the core. The overall mechanical behavior of the case-carburized material is much closer to that of the completely carburized material, indicating that the carburized case dominates the case-carburized material. Stress fatigue tests conducted on carburized tubular specimens, pseudo-carburized solid specimens, and case-carburized solid specimens showed that the fatigue performance of the completely carburized material is slightly lower than that of the pseudo-carburized specimens due to lower plasticity. However, the fatigue performance of the case-carburized specimens is significantly better than that of the two homogeneous materials. This could be attributed to the graded material behavior and the larger compressive residual... [more]

With the arrival of Industry 4.0, interoperability has become a major subject for companies worldwide. It is a crucial asset that enables new technologies and possibilities (Industrial Internet of Things, predictive maintenance or traceability solutions). With the increasing importance of data in business use cases, companies are faced with a choice between two interoperability approaches to deal with the challenge of reconciling different domains: standardization and mediation. This paper presents an analysis of each approach and proposes a decision-making methodology based on the Analytic Hierarchy Process (AHP) that aims to help companies in choosing the most suitable solution to resolve interoperability challenges.

The growing sensitivity toward sustainability is being demonstrated by an increase in sales of natural wines. Natural wines are obtained using exclusively native vines, indigenous yeasts, absence of additives, irregular temperature control during fermentation, and smaller quantities of sulfites even compared to organic wines. In this work, natural wines were obtained from Fiano grape, a historical cultivar of Irpinia (Campania, Italy). The main objective of this study was to compare the chemical and sensory characteristics of natural wines produced using different vessels (10 HL): Test A: stainless steel; Test B: earthenware amphora; Test C: mulberry wood barrel; and Test D: cherry wood barrel without the use of starter yeasts and chemical additives, including sulfites. Our results show a greater concentration of higher alcohols and esters in wines obtained in amphora and wooden barrels. The results of this work reveal that the type of container influences the composition of wine to an... [more]

The objective of this study was to compare the quality of low-acid vegetables conventionally thermal processed with those subjected to modified thermal processing following acidification to pH < 4.6. For conventional processing, a process lethality (Fo value) equivalent of 5 min at 121.1 °C (commercially sterilization) was used, while those that are acidified were pasteurized, such as acidic foods, to a lethality value of 10 min at 90 °C. Acidification was performed with citric acid by immersion of vegetables in an ultrasonic bath. The quality of raw, blanched, acidified, pasteurized and sterilized products were compared for color and textural characteristics. The acidified thermal processing yielded significantly better retained color and textural properties, almost similar to blanched vegetables, while those subjected to the conventional processing resulted in significant texture loss. The process temperatures were significantly lower, and corresponding process intensities were si... [more]

This paper investigates common (slack) due-date assignment single-machine scheduling with controllable processing times within a group technology environment. Under linear and convex resource allocation functions, the cost function minimizes scheduling (including the weighted sum of earliness, tardiness, and due-date assignment, where the weights are position-dependent) and resource-allocation costs. Given some optimal properties of the problem, if the size of jobs in each group is identical, the optimal group sequence can be obtained via an assignment problem. We then illustrate that the problem is polynomially solvable in O(℘3) time, where ℘ is the number of jobs.

The conventional V2O5 preparation processes include ion exchange, chemical precipitation, solvent extraction, and other processes. Given the long process and complex operation nature of traditional V2O5 production methods, we herein developed a short-process, low-temperature, and convenient operation method of isolating vanadium (in the form of V2O5) from shale acid leaching solution. The acid leaching solution was oxidized with NaClO3 and pH-adjusted with NaOH to form a vanadium-containing precipitate, which was mixed with AlCl3 (V:AlCl3 = 1:5, mol/mol) and roasted for 120 min at 170 °C to afford vanadium oxytrichloride (VOCl3) with a purity of 99.59%. In addition, the vanadium-containing precipitate was mixed with AlCl3 and NaCl (V:AlCl3:NaCl = 3:12:8, mol/mol/mol) and roasted for 120 min at 170 °C to afford VOCl3 with a purity of 99.94%. VOCl3 (purity of 99.94%) was dissolved in ultrapure water, and the solution (32 gvanadium/L) was treated with NH3·H2O (NH3:V = 1.34, mol/mol) at 50... [more]

The detection of coal and gangue is an essential part of intelligent sorting. A lightweight coal and gangue detection algorithm based on You Only Look Once version 5s (Yolov5s) is proposed for the current coal and gangue target detection algorithm with the low accuracy of small target detection, high model complexity, and sizeable computational memory consumption. Firstly, we build a new convolutional block based on the Funnel Rectified Linear Unit (FReLU) activation function and apply it to the original Yolov5s network so that the model adaptively captures local contextual information of the image. Secondly, the neck of the original network is redesigned to improve the detection accuracy of small samples by adding a small target detection head to achieve multi-scale feature fusion. Next, some of the standard convolution modules in the original network are replaced with Depthwise Convolution (DWC) and Ghost Shuffle Convolution (GSC) modules to build a lightweight feature extraction net... [more]

Using a high proportion of new energy is becoming the development trend of the modern power industry, with broad application prospects and potential threats to power system operation safety. This paper proposes a hybrid adaptive velocity update relaxation particle swarm optimization algorithm (AVURPSO) and recursive least square (RLS) method to quickly estimate the DSSR boundary using hyper-plane expression. Firstly, the operating point data in the high-dimension nodal injection space are analyzed using the AVURPSO algorithm to identify the key generators, equivalent search space, and critical points, which have relatively great effects on transient angle stability. The hyper-plane expression of the DSSR boundary, which matches the critical points best, is finally fitted by the RLS approach. Hence, the adopted algorithm is applied to rapidly approximate the DSSR boundary by hyper-plane expression in power injection spaces. Finally, the proposed algorithm is validated using a simulation... [more]

This feasibility study utilized regression models to predict makespan robustness in dynamic production processes with uncertain processing times. Previous methods for robustness determination were computationally intensive (Monte Carlo experiments) or inaccurate (surrogate measures). However, calculating robustness efficiently is crucial for field-synchronous scheduling techniques. Regression models with multiple input features considering uncertain processing times on the critical path outperform traditional surrogate measures. Well-trained regression models internalize the behavior of a dynamic simulation and can quickly predict accurate robustness (correlation: r>0.98). The proposed method was successfully applied to a permutation flow shop scheduling problem, balancing makespan and robustness. Integrating regression models into a metaheuristic model, schedules could be generated that have a similar quality to using Monte Carlo experiments. These results suggest that employing machi... [more]

The rapid growth of the world’s population has put significant pressure on agriculture to meet the increasing demand for food. In this context, agriculture faces multiple challenges, one of which is weed management. While herbicides have traditionally been used to control weed growth, their excessive and random use can lead to environmental pollution and herbicide resistance. To address these challenges, in the agricultural industry, deep learning models have become a possible tool for decision-making by using massive amounts of information collected from smart farm sensors. However, agriculture’s varied environments pose a challenge to testing and adopting new technology effectively. This study reviews recent advances in deep learning models and methods for detecting and classifying weeds to improve the sustainability of agricultural crops. The study compares performance metrics such as recall, accuracy, F1-Score, and precision, and highlights the adoption of novel techniques, such as... [more]

In this paper, the effect of nano-particles along with EGR rates was experimentally assessed on the performance and emission of a DI diesel engine fueled by biodiesel and ethanol. For this purpose, three levels of TiO2 nanoparticles (0, 40, and 60 ppm) were added to biodiesel/diesel blends in the proportions of 0, 10, and 20% biodiesel with ethanol at levels of 0, 4, and 6%. EGR rates were used at 0, 20, and 30%. A total of 31 fuel samples with different ethanol, biodiesel, TiO2 nano-additives, and EGR rates were tested at different speeds. The equation for this combination is BxEy + EGRw + TiO2z, where x, y, w, and z are the percentages of biodiesel, ethanol, EGR, and TiO2. The results showed that the mixture of B10E4 + EGR20 + TiO260, reduced the amount of NOx, CO, and HC by 10, 12.4, and 17%. Moreover, due to the significant reduction of emissions and performance improvement, the combinatory method of EGR−TiO2 nano-additives can be used as an effective formula for diesel engines fue... [more]

Manganese is a vital element in determining the mechanical properties of submerged arc welded metal. To ensure a reliable weld, the equilibrium model has been used for decades to predict and control the manganese content, particularly when MnO-bearing fluxes are applied. However, the equilibrium model only considers chemical interactions within the weld pool zone, leading to significant inaccuracies. To address this limitation, we propose a multi-zone model that accounts for all of the essential reaction zones in the submerged arc process via the Calphad technique. The model’s accuracy is verified by predicting the manganese content, the flux oxygen potential, and the neutral point location for the typical MnO-bearing fluxes covering acidic, neutral, and basic fluxes. The results indicate that the multi-zone model offers superior accuracy compared to the equilibrium model, which neglects significant oxygen improvement and alloy evaporation in the droplet zone. Further analysis of therm... [more]

The content of this research paper is focused on the applications of selected operation research methods in the field of rescue services. The first theoretical part aims at identifying the most important aspects of the real system, which should be taken into account whenever a rescue system is to be redesigned or optimized. It also contains an in-depth description of system performance. Based on the found criteria, a mathematical model for a new system design is proposed. The second part of this paper is practically oriented. A short case study performed with real data on the rescue service system in Slovakia is reported herein, and the obtained results are compared with current fire brigade deployment. We concentrate on improving the most important criteria of the real system. If the suggested mathematical model proves to be hard to solve with common optimization tools, we will develop an efficient solving algorithm. From a general point of view, the main scientific goal of this resea... [more]

Although many biofuel blends have been proposed recently, comparisons of such blends are rarely investigated. Currently, it is extremely difficult to recommend one biofuel blend over another since comparisons are not carried out under the same engine conditions. In the current study, different biofuel blends in dual and ternary issues are compared together, as well as with conventional gasoline under the same engine conditions. Five different biofuel blends are considered, i-butanol (iB), n-butanol (nB), bio-ethanol (E), n-butanol−bio-ethanol (nBE), and i-butanol−bio-ethanol−gasoline (iBE) blends, at two different engine speeds (2500 and 3500 rpm/min). Additionally, the blends are compared in the average bases through wide engine speeds. The comparisons of blends are carried out via engine performance and emissions. The performance includes engine power, torque, and volumetric efficiency, while the emissions include CO, CO2, and UHC. Results showed that the E blends presented higher pe... [more]

Restrictions on competitive fishing activities due to the depletion of living marine resources and the monitoring of fish resources for the purpose of marine ecosystem research are supported by statistics on the protection of fish resources and ecosystem research, which are gathered through existing observer monitoring systems. However, in the case of deep-sea fishing vessels and special-purpose fishing vessels, some matters, such as collusive transactions with shipping companies and shipowners and threats toward the observer, are problematic, as observers are always active on board. Therefore, through the present study we would like to discuss the methodology and directions for research on the independent role of the observer and the methods for improving the reliability of data through systems that automate the monitoring of the acquisition of fish resources, which is expected to be a continuing problem. After an analysis of research trends for each issue related to the electronic mo... [more]

Plasma electrolytic oxidation (PEO) was used to establish a porous metal oxide layer on various titanium and zirconium workpieces in the form of wires, porous tubes, and 3D-printed structures. The ultimate goal of the work was to create a layer with the desired characteristics over a catalyst support or metal membrane structures to improve the performance of the targeted high-temperature catalytic conversion or separation applications. In doing so, it was ensured that the PEO-treated layer could provide the desired morphology, thickness, and porosity needed for the final processing step, which is usually a conventional coating method. This addresses the limitations of ceramic structures, including their mechanical resistance, thermal resistance, and conductivity, and their potential for being functionalized and utilized for high-temperature applications. The entire experimental run was carried out using a 2 kilowatt (maximum output) AC-power source with a maximum current limit of 6.5 A... [more]

Due to today’s technological development and information progress, an increasing number of physical systems have become interconnected and linked together through communication networks, thus resulting in Cyber-Physical Systems (CPSs). Continuous manufacturing, which involves the manufacture of products without interruption, has become increasingly important in many industries, including the pharmaceutical and chemical industries. CPSs can be used to control and monitor the production process, which is essential in enabling continuous manufacturing. This paper is focused on the modeling and control of physical systems required in tablet production using dry granulation. Tablets are a type of oral dosage form that is commonly used in the pharmaceutical industry. They are solid, compressed forms of medication that are formulated to release the active ingredients in a manner that allows for optimal absorption and efficacy. Thus, a model predictive control (MPC) strategy is applied to a pl... [more]

Natural gas pipeline leaks under the sea will have a significant negative effect on the marine ecosystem, result in significant financial losses, and possibly even harm marine floating objects. The VOF (Volume of Fluid) multi-phase flow model is used to numerically simulate and study the diffusion process of porous leakage in submarine gas pipelines. Experiments confirmed the model’s correctness and dependability. Based on this, the coupling effect and the porous effect of the leakage velocity, the size of the leaked pore, and water velocity of the natural gas pipelines on the diffusion of porous leakage in the submarine gas pipelines are analyzed with the test scheme designed by the orthogonal test method. The similarity principle is used to connect the leakage model with the actual application. The results show that three factors, namely, the leakage velocity, the size of leaked pore, and the water velocity, influence the shape of the air mass, the time when the gas reaches the sea s... [more]

The petrochemical industry is a pillar industry for the development of the national economy affecting people’s daily living standards. Crude distillation process is the core and leading unit of the petrochemical industry. Its energy consumption accounts for more than 20% of the total energy consumption of the whole plant, which is the highest energy consumption link. A model based on the long short-term memory network (LSTM) is proposed in this paper to predict and analyze energy efficiency. This model extracts the complex relationship between many process variables and predicts the energy efficiency of the crude distillation process. Firstly, the process simulation of crude distillation is carried out. By adding random disturbance, the data set in different working conditions is obtained, and the difference between the working conditions is expressed with the distance-coded heat map. Secondly, the Savitzky−Golay (SG) filter is used to smooth the data, which preserves the original char... [more]

The demand for critical metals for net-zero technologies, including electric vehicles and wind/solar energy, puts pressure on extraction and recycling processes. As the treatment of solutions is becoming more and more complex and associated with the decreasing concentration of critical metals and the concentration of contaminants increasing, the development of separation techniques is required. Among them, membrane separation has been evaluated for hydrometallurgical processes with similar results to traditional techniques. This work aimed at reviewing the literature on membrane applications to obtain critical metals—lithium (Li), cobalt (Co), and rare earth elements (scandium—Sc, yttrium—Y, lanthanum—La, and neodymium—Nd). The main novelty is that this literature review focuses on the application of membrane techniques in industrial processes, not only water and wastewater treatment. For this, we searched a scientific database for different keywords, and the bibliometric analysis demo... [more]

Wireless mesh networks (WMN) promise to be an effective way to solve the “last mile” access problem on the Internet of Things (IoT) and the key to next-generation wireless networks. The current routing algorithms of WMN are difficult to adapt to complex environments and guarantee the reliable transmission of services. Therefore, this paper proposes a reliable routing algorithm that combines the improved breadth-first search and a graph neural network, namely GraphSAGE. The algorithm consists of two parts: (1) A multi-path routing algorithm based on the improved breadth-first search. This algorithm can continuously iterate link information based on network topology and output all shortest paths. (2) A GraphSAGE-based performance optimization algorithm. This algorithm creates a method to generate network labels for supervised training of GraphSAGE. Then, the network labels and GraphSAGE are used to learn graph features to obtain the value of network performance for each shortest path. Fi... [more]