Sequential Operations Research Articles

Estimation and Control of WRRF Biogas Production

The development of resource-efficient digital technologies is a critical challenge in the wastewater sector. This industrial case study, conducted in collaboration with the Veas Water Resource Recovery Facility in Norway, focused on creating data pre-processing methods and resource-efficient control strategies. Using data from the Veas biogas plant, dynamic models were developed to compare control outcomes. The primary objective was to maximize biogas production and hot water usage while maintaining optimal temperature and hydraulic retention time by adjusting inlet sludge and hot water flow rates. Sequential operations were approximated as continuous operations using a 30-min moving minimum/maximum for bimodal data and a 2-h moving average for noisy data. The data-driven dynamic models achieved an accuracy of up to R2 of 0.85. The control strategy, which included one feedback controller, one ratio controller, and flow rate restrictions, was compared to real production data (baseline) and tested across six scenarios. The best improvement over the baseline scenario resulted in a 3% increase in total biogas production, a 6% increase in total organic loading, a 13% increase in hot water use, and a one-day reduction in hydraulic retention time. Future work should focus on control studies using extended datasets and nonlinear models.

Autonomous online optimization of a closed-circuit reverse osmosis system

As freshwater becomes increasingly scarce, many industrial and municipal water utilities look at premise-scale water treatment and reuse to meet water demand. Closed-circuit reverse osmosis (CCRO) has been proposed as a promising process design to do so. This sequencing batch process enables operation at higher brine salinity levels by means of a recycle flow. Optimal operation requires that the maximum salinity level at the membrane surface represents an optimal trade-off between brine disposal costs and energy efficiency. This maximum salinity level may change over time as the feed water composition changes and electricity markets fluctuate. In this article, we present the results of the experimental evaluation of an automatic technique for continuous online optimization, known as extremum seeking control. This technique has a long history in the process control community but has received little traction so far in the water industry. We modify this technique to enable its use for online optimization of CCRO, specifically to account for its sequential batch operation. We challenge the optimization schemes through several experimental tests and illustrate the advantages and drawbacks of extremum-seeking control.

Realization of quasi-steady-state piled smouldering using sequential operation chambers for industrial treatment of biomass wastes.

Piled smouldering has great potential for treatment and utilization of biomass wastes. However, its unsteady-state nature limits its industrial utilization, as well as treatment of smoke. This article addresses this issue by proposing the sequential operation of numerous smouldering chambers to realize steady- or quasi-steady-state piled smouldering. The superposition characteristics of sequential unsteady-state curves were analysed theoretically, and a code was developed to determine an appropriate number of piled chambers at an allowance oscillation percentage. Smouldering experiments were performed on a single mini chamber (length × width × height: 340 × 140 × 140 mm3) containing piled wood pellets mixed with wood powder. The superposition of sequential burning rate curves was demonstrated using the code based on the mass loss data of experiments. Analysis shows that the perfect-steady state is possible given the superposition value of the burning rate curve is a constant in this proposed system. Experiments show that the molar ratio of CO/CO2 in smoke is almost a constant around 0.5 during densely piled smouldering, showing the great potential for self-sustained burning out the smoke. Based on the experimental results, the calculation results show that the relative oscillation range of burning rate (OSC) decreases from 75% to 3% while increasing the number of chambers from 2 to 7. This work provides a novel technology to enable quasi-steady-state smouldering for industrial utilization.

Technology of production of aluminosilicate refractories for units processing fluorinated waste

The aluminium production process through the electrolysis of cryolite-alumina melts involves a series of interconnected, sequential, and parallel technological operations, each defined by a specific level of engineering and technological advancement. The development of the modern aluminum industry is closely tied to the adoption of resource-efficient and environmentally friendly technologies, which focus on recycling secondary materials and industrial waste. Fluorinated carbon-based materials release fluorine into the gas phase at relatively low temperatures when heated, and in thermal units processing fluorinated waste, this fluorine, along with alkali metals, will remain in the gas phase. To enhance the durability of furnace linings against the corrosive atmosphere, refractories with the highest possible density (low porosity) and a high concentration of mullite in the matrix (the finely ground component of the batch) are required. These properties can only be achieved in refractory products produced by the semi-dry pressing method, which ensures high grain packing density and leads to the formation of a ceramic mullite bond after firing.

Structure and Properties of the Electroexplosive Coating of the TiB2-Ag System after Electron Beam Treatment

A coating of the TiB2-Ag system was formed through the use of sequential operations of electroexplosive spraying and electron beam processing. The values of electrical conductivity (62.0 MS/m), Vickers microhardness (0.251-0.265 GPa at the point of measurement on a silver matrix and 25-32 GPa at the point of measurement at inclusions of boride phases), nanohardness (4.48 ± 0.76 GPa) were determined), Young’s modulus (116±29 GPa), wear parameter under dry friction-sliding conditions (1.2 mm3/N • m) and friction coefficient (0.5). Switching wear resistance during accelerated tests was 7000 on and off cycles with an electrical resistance of 10.01 - 11.76 LiOhm. The thickness of the coatings is 100 microns. The coatings are formed by a silver matrix with inclusions of titanium borides located in it with three types of sizes: nanocrystalline, submicrocrystalline and microcrystalline. Quantitatively, in the structural composition among titanium borides, titanium diboride and silver (56 wt. %) are formed predominantly (41 wt. %), while other titanium borides account for 3 wt. %. Structural transformations are described using complementary methods of X-ray phase analysis, scanning and transmission electron microscopy.

Закладка виноградника на основе принципов энерго-ресурсосбережения

Abstract. The article contains materials that form the basis of a feasibility study (FS) for laying a vineyard (from planting to fructification), developed according to the principle of energy and resource conservation provided for in the project assignment. The project documentation is being developed in order to optimize the complex of sequential technological operations and production processes aimed at creating a sustainably functioning viticultural economy. The general principles of energy and resource conservation include: the latest achievements of science and best practices in the field of viticulture, rational use of land funds, thanks to preliminary soil surveys, optimized varietal composition, design of plantings and compact placement of arrays with the prospect of irrigation, reduction of energy losses to the level of operationally unavoidable, the use of highly concentrated, complex agrochemicals and methods of their application, the availability of appropriate infrastructure, design estimates optimized with the prospect of improvement and modernization (energy and resource-saving object estimates), planned economic productivity of plantations, measures to maintain the economic fertility of soils corresponding to the biological requirements of grape culture, which determines the stability and productivity of perennial plantations. Methodological approaches and current methods, publications of a recommendatory nature used for the development of a feasibility study are indicated. The successive stages of the development of project documentation are considered, the techniques that contribute to reducing the costs of production processes are outlined. The recommended regionalized and promising assortment of grapes for the formation of highly productive stable ampelocenoses ensuring stable highly profitable functioning of enterprises of the grape-growing industry in the Krasnodar region is presented and justified. The recommended current varietal composition of plantings is compiled taking into account the edaphoclimatic conditions of the design object, the agrobiological characteristics of grape varieties, as well as taking into account current global trends in the organization of a sustainably functioning highly efficient industrial enterprise for the production of viticulture products. Keywords: ampelocenosis, project assignment, long-term planning, varietal policy, energy and resource conservation

Pilot microbial electrolysis cell closes the hydrogen loop for hydrothermal wet waste conversion to jet fuel

The global shift toward net-zero emissions necessitates resource recovery from wet waste. In this study, we demonstrate the first feasibility of combining pilot-scale microbial electrolytic cells (MECs) with hydrothermal liquefaction (HTL) for simultaneous post-hydrothermal liquefaction wastewater (PHW) treatment and efficient hydrogen (H₂) production to meet biocrude upgrading requirements. Long-term single reactor operation revealed that fixed anode potential enabled rapid startup, and low catholyte pH and high salinity were effective in suppression of cathodic methanogenesis and acetogenesis – resulting in high current density of 16.6 A m−2 and 9.3 A m−2 when feeding synthetic wastewater and PHW respectively. Additionally, the anode biofilm exhibited spatial variations in response to local environmental conditions. Onsite parallel or serial operations of multiple MECs showed good performance using actual PHW with a record-high H2 production rate of 0.5 L LR day−1 for MEC over 10 liters scale, and the optimal chemical oxygen demand (COD)-to-H2 yield reached 0.127 kg-H2 per kg-COD, supporting a self-sufficient, closed-loop upgrade to jet fuel.

ACU-TransNet: Attention and convolution-augmented UNet-transformer network for polyp segmentation.

UNet has achieved great success in medical image segmentation. However, due to the inherent locality of convolution operations, UNet is deficient in capturing global features and long-range dependencies of polyps, resulting in less accurate polyp recognition for complex morphologies and backgrounds. Transformers, with their sequential operations, are better at perceiving global features but lack low-level details, leading to limited localization ability. If the advantages of both architectures can be effectively combined, the accuracy of polyp segmentation can be further improved. In this paper, we propose an attention and convolution-augmented UNet-Transformer Network (ACU-TransNet) for polyp segmentation. This network is composed of the comprehensive attention UNet and the Transformer head, sequentially connected by the bridge layer. On the one hand, the comprehensive attention UNet enhances specific feature extraction through deformable convolution and channel attention in the first layer of the encoder and achieves more accurate shape extraction through spatial attention and channel attention in the decoder. On the other hand, the Transformer head supplements fine-grained information through convolutional attention and acquires hierarchical global characteristics from the feature maps. mcU-TransNet could comprehensively learn dataset features and enhance colonoscopy interpretability for polyp detection. Experimental results on the CVC-ClinicDB and Kvasir-SEG datasets demonstrate that mcU-TransNet outperforms existing state-of-the-art methods, showcasing its robustness.

Valved Microwell Array Platforms for Stepwise Liquid Dispensing.

The fabrication of microarray chips and the precise dispensing of nanoliter to microliter liquids are fundamental for high-throughput parallel biochemical testing. Conventional microwells, typically featuring a uniform cross section, fill completely in a single operation, complicating the introduction of multiple reagents for stepwise and combinatorial analyses. To overcome this limitation, we developed an innovative valved microwell array. Using ultraviolet (UV)-curing resin three-dimensional (3D) printing, these multilayer configurations can be rapidly fabricated through direct template printing and polydimethylsiloxane (PDMS) casting. Each microwell incorporates a microvalve structure, truncating fluids within the upper metering well and allowing transfer to the bottom reservoir well under centrifugal force. Sequential operations enable the introduction of multiple reagents, facilitating orthogonal combinations for complex assays. We explored four types of valving methods: DeepWell, Expansion, Bottleneck, and Membrane valve, each offering varying degrees of design complexity, operational efficiency, robustness, and precision. These methods constitute a versatile toolkit to accommodate a broad spectrum of analytical requirements. Our innovative approach redefines microwell architecture, direct manufacturing techniques, and stepwise fluid dispensation in microarrays.

Memristive Crossbar Array-Based Probabilistic Graph Modeling.

Modern graph datasets with structural complexity and uncertainties due to incomplete information or data variability require advanced modeling techniques beyond conventional graph models. This study introduces a memristive crossbar array (CBA)-based probabilistic graph model (C-PGM) utilizing Cu0.3Te0.7/HfO2/Pt memristors, which exhibit probabilistic switching, self-rectifying, and memory characteristics. C-PGM addresses the complexities and uncertainties inherent in structural graph data across various domains, leveraging the probabilistic nature of memristors. C-PGM relies on the device-to-device variation across multiple memristive CBAs, overcoming the limitations of previous approaches that rely on sequential operations, which are slower and have a reliability concern due to repeated switching. This new approach enables the fast processing and massive implementation of probabilistic units at the expense of chip area. In this study, the hardware-based C-PGM feasibly expresses small-scale probabilistic graphs and shows minimal error in aggregate probability calculations. The probability calculation capabilities of C-PGM are applied to steady-state estimation and the PageRank algorithm, which is implemented on a simulated large-scale C-PGM. The C-PGM-based steady-state estimation and PageRank algorithm demonstrate comparable accuracy to conventional methods while significantly reducing computational costs.

A Study on the Importance of Sequential Medical Property Development and Operation - focusing on location characteristics -

A Study on the Importance of Sequential Medical Property Development and Operation - focusing on location characteristics -

CTRNet: An Automatic Modulation Recognition Based on Transformer-CNN Neural Network

Deep learning (DL) has brought new perspectives and methods to automatic modulation recognition (AMR), enabling AMR systems to operate more efficiently and reliably in modern wireless communication environments through its powerful feature learning and complex pattern recognition capabilities. However, convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which are used for sequence recognition tasks, face two main challenges, respectively: the ineffective utilization of global information and slow processing speeds due to sequential operations. To address these issues, this paper introduces CTRNet, a novel automatic modulation recognition network that combines a CNN with Transformer. This combination leverages Transformer’s ability to adequately capture the long-distance dependencies between global sequences and its advantages in sequence modeling, along with the CNN’s capability to extract features from local feature regions of signals. During the data preprocessing stage, the original IQ-modulated signals undergo sliding-window processing. By selecting the appropriate window sizes and strides, multiple subsequences are formed, enabling the network to effectively handle complex modulation patterns. In the embedding module, token vectors are designed to integrate information from multiple samples within each window, enhancing the model’s understanding and modeling ability of global information. In the feedforward neural network, a more effective Bilinear layer is employed for processing to capture the higher-order relationship between input features, thereby enhancing the ability of the model to capture complex patterns. Experiments conducted on the RML2016.10A public dataset demonstrate that compared with the existing algorithms, the proposed algorithm not only exhibits significant advantages in terms of parameter efficiency but also achieves higher recognition accuracy under various signal-to-noise ratio (SNR) conditions. In particular, it performs relatively well in terms of accuracy, precision, recall, and F1-score, with clearer classification of higher-order modulations and notable overall accuracy improvement.

PENINGKATAN PEMAHAMAN PENJUMLAHAN DENGAN TEKNIK MENYIMPAN MENGGUNAKAN ALAT PERAGA DI KELAS II SD NEGERI 218/LIMBUR BARU

ABSTRACT The research problem is the lack of understanding of the material for calculating sequential additions. The aim of this research is to improve understanding of compound addition material by storing techniques through the use of number value racks. Class II students at SD Negeri 218 Limbur who have mild intellectual disabilities will benefit from a better understanding of the concept of multilevel addition operations. This type of research is called Classroom Action Research (PTK). This research was carried out in two cycles, each cycle being carried out in three meetings. Each cycle has four interrelated phases: observation, reflection, action implementation, planning phase, and reflection. The research subjects were four students of SD Negeri 218 Limbur class II. Data was collected through test and observation methods. Quantitative analysis was carried out on the data, and a table was presented showing student learning outcomes. Based on the results of research conducted in cycle I and cycle II, the results of data analysis and reflection show that cycle I research has not met the expected indicators of success, namely better understanding of mathematical concepts because it shows learning outcomes and students' abilities in understanding and carrying out sequential addition operations. using the saving technique, then the average result in cycle II was 62.5%. By using the saving technique, students were able to understand the concept of sequential addition, which not only achieved the desired goal but also improved. This shows that the use of the number value rack display tool can improve students' understanding of the addition material using storing techniques. Keywords : stacked addition, rack of number values.

Adaptive Workflows of Machine Learning Illuminate the Sequential Operation Mechanism of the TAK1's Allosteric Network.

Allostery is a fundamental mechanism driving biomolecular processes that holds significant therapeutic concern. Our study rigorously investigates how two distinct machine-learning algorithms uniquely classify two already close-to-active DFG-in states of TAK1, differing just by the presence or absence of its allosteric activator TAB1, from an ensemble mixture of conformations (obtained from 2.4 μs molecular dynamics (MD) simulations). The novelty, however, lies in understanding the deeper algorithmic potentials to systematically derive a diverse set of differential residue connectivity features that reconstruct the essential mechanistic architecture for TAK1-TAB1 allostery in such a close-to-active biochemical scenario. While the recursive, random forest-based workflow displays the potential of conducting discretized, hierarchical derivation of allosteric features, a multilayer perceptron-based approach gains considerable efficacy in revealing fluid connected patterns of features when hybridized with mutual information scoring. Interestingly, both pipelines benchmark similar directions of functional conformational changes for TAK1's activation. The findings significantly advance the depth of mechanistic understanding by highlighting crucial activation signatures along a directed C-lobe → activation loop → ATP pocket channel of information flow, including (1) the αF-αE biterminal alignments and (2) the "catalytic" drift of the activation loop toward kinase active site. Besides, some novel allosteric hotspots (K253, Y206, N189, etc.) are further recognized as TAB1 sensors, transducers, and responders, including a benchmark E70 mutation site, precisely mapping the important structural segments for sequential allosteric execution. Hence, our work demonstrates how to navigate through greater structural depths and dimensions of dynamic allosteric machineries just by leveraging standard ML methods in suitable streamlined workflows adaptive to the specific system and objectives.

Customs services and ways to improve their quality in the context of digitalisation

This article is devoted to problems of the process of rendering services in the field of customs during digitalisation of the economy. The observed mechanism of rendering state customs services, as well as improving their quality, naturally affect the entire service sector and the development of the country’s economy as a whole. The main purposes of the article are to analyse the mechanism of rendering services in the field of customs and to search for effective methods of assessing their quality. The relevance of the article is determined by the need to improve the operations performed to be able to manage the quality of provided customs services. The main objective of this article is to propose possible ways to reduce time costs without losing the quality of customs control in the process of providing the services. The article used both theoretical (analysis of the current legislation) and empirical research methods (giving practical examples of improving the efficiency of customs operations and the quality of customs services). The results of the study are the following: development of sequential operations performed by customs authorities in the process of rendering services in the field of customs; proposal of possible criteria for assessing their quality; formulation of options for managing this quality.

Development of a feasible and scalable manufacturing method for PTFE-based solvent-free lithium-ion battery electrodes

Conventional wet-electrode manufacturing encounters challenges in producing thicker electrodes due to issues related to solvent evaporation. This study introduces a novel method for fabricating solvent-free dry electrodes using polytetrafluoroethylene (PTFE) as a binder, representing a significant advancement in electrode manufacturing processes. By eliminating the use of solvents, this method not only addresses these challenges but also offers a scalable and practical solution for mass production. The process is meticulously structured into sequential unit operations, each specifically tailored for a distinct function, utilizing the distinctive fibrillation properties of PTFE. Intermediate product specifications for each phase are clearly defined, accompanied by a comprehensive analysis of both physical and electrochemical performances. This analysis highlights the influence of varying PTFE contents and properties on the microstructure of the dry electrode. Notably, the study achieves a significant breakthrough with an electrode formulation of NCM811/PTFE/carbon black (CB)/carbon nanotube (CNT) = 96/2.0/1.8/0.2, which demonstrates exceptional discharge rate capability of 80 % at a 0.5 C-rate (5 mA/cm2) under the demanding parameters of 10 mAh/cm2 and 3.8 g/cc. This approach not only enhances the microstructural properties of dry electrodes but also paves the way for environmentally friendly and efficient electrode manufacturing for future energy storage applications.

Purification and fractionation of cellooligosaccharides synthesized from controlled cellulose hydrolysis by sulfuric acid using nanofiltration

Cellooligosaccharides (COS) as potential prebiotics have drawn increasing attention. They can be synthesized from cellulose via controlled hydrolysis by sulfuric acid (SA). However, it is challenging to efficiently separate COS from the hydrolysate. In this study, nanofiltration (NF) with commercial membranes was investigated to separate COS from cellulose hydrolysate by removing SA and non-prebiotic sugars (e.g., glucose) and further fractionating COS by size. Based on water permeability, pore size, and acid stability, two membranes (Trisep® XN45 and Synder® NFG) were selected from four candidates. The effects of operation conditions (membrane and applied pressure) and feed concentrations (sugars and SA) on the COS purification and fractionation were studied. It was found that the XN45 membrane with an estimated average pore size of 0.61 nm was efficient in removing SA and glucose from COS, while NFG with a larger pore size of 0.84 nm can be used to fractionate and further purify COS based on size (degree of polymerization, DP). Four sequential batch NF operations of cellulose hydrolysate through XN45 (×3) and NFG (×1) membranes recovered 80 % of the total COS in the hydrolysate and removed 99 % of SA and 95 % of glucose. NFG membrane can roughly separate COS into two fractions, one (retentate) with more larger COS (DP ≥ 9) and another (permeate) with more smaller COS (DP 2–8). This study successfully demonstrated the feasibility of NF to purify and fractionate COS from cellulose hydrolysate.

Air tightness detection method in parallel for aerospace: mechanical design, system modeling and optimum control

To address the problems of high cost, complex operation, and low efficiency of existing equipment for aerospace, a simple but efficient multichannel air tightness detection device is designed. A physical system model is constructed for the process of inflation, deflation, and inflation with leakage. The expression between the inflation/deflation rate and the valve area is obtained. Through modeling the intersection and rotation of spatial curves, the relationship between the valve area and the valve core angle is derived, and the optimal valve core angle calculation method is proposed to achieve precise rate control of inflation and deflation. Simulation experiments and numerical analysis demonstrate the superiority of the proposed system scheme, the effectiveness of the control method, as well as the accuracy of the mathematical model. For the tested object of 0.3 L, the target pressure of 400 KPa, and the inflation and deflation rate of 75 Kpa/min, by using four channels with a 10 s interval for sequential operation and adjusting valves every 60 s, the efficiency of inflation and deflation is more than 3.5 times that of a single device with a single circuit. Its performance is not much different from real-time automatic control equipment, but the economy is greatly improved.

A sequential bioconversion-purification process to produce high purity xylo-oligosaccharides (XOS) from Nothophagus pumilio sawdust wastes

Xylo-oligosaccharide (XOS) production from lignocellulosic biomass (LCB) is an ongoing technology in which the best raw material, catalyst, and reaction conditions remain unclear. This study proposed a three-step sequential operation to produce prebiotic Xylo-oligosaccharide (XOS) from lignocellulosic biomass (LCB) Nothophagus pumillio sawdust. First, a commercial (Enzeco Xylanase S) and recombinant (GtXyl10A) xylanase were evaluated in XOS production from pre-extracted xylan. Then, the effect of auxiliary enzyme addition (α-glucuronidase) was evaluated in xylan hydrolysis, and finally, XOS were purified by three steps of membrane filtrations: an ultrafiltration (UF) followed by two nanofiltrations (NF). From the above, XOS production yield reach 333 [mgxos∙gxylan−1] of highly purified XOS (95 %) when the process was carried out without auxiliary enzyme addition and 473 [mgxos∙gxylan−1] of 96 % purified XOS when auxiliary enzyme was added, resulting in an improvement of the XOS production yield in 42 %.This shows the feasibility to produce high purity prebiotics from sawdust wastes of the forestry industry.

MODEL OF FUNCTIONING LOGISTICS FOR SUPPLY OF SPECIALISED VEHICLES IN CONTAINERS FROM NORTH AMERICAN COMPANIES TO UKRAINE

The article analyses the current state and prospects for developing logistics for supplying various types of cargo in international traffic to be transported in containers. It allowed us to formulate the purpose of the study in this development. This topic is relevant since the efficient organisation of containerised supply logistics can improve the functioning of transport systems. An effective way to reduce the cost of supplying a cargo unit is efficient resource use (railway stations, ports, warehouses, wagons, vehicles, containers). The study paid considerable attention to developing the relevant infrastructure, solving specific problems of efficient use of all types of resources, using digital technologies, and building reliable models of logistics supply systems. The article builds a structural model based on the principles of logistics interaction of possible participants in the supply process, representing the interaction of subsystems that significantly affect the quality of the relevant operations. We formed five schemes of interaction between logistics participants for supplying specialised vehicles in containers with the participation of automobile, railway, and sea transport and the relevant infrastructure. These schemes identify the main ports of departure in the United States (New York and Houston) and ports of destination in Europe (Klaipeda (Lithuania), Constanta (Romania)), and take into account the possibility of using road and rail transport resources in European countries and Ukraine. We developed a mathematical model of logistics functioning for the supply of specialised vehicles in containers from North American enterprises to Ukraine, which accounts for the specifics of sequential operations and the peculiarities of determining the performance indicators of each supply chain operation. The prospect of using these models is to build a simulation model of logistics for the supply of specialised vehicles in containers from North American companies to Ukraine, conduct simulations using a software environment, and determine the rational option under the established conditions. Keywords: model, logistics, supply, vehicles, international transportation.