Industrial Systems Research Articles

Microwave-assisted organic acids and green hydrogen production during mixed culture fermentation.

The integration of anaerobic digestion into bio-based industries can create synergies that help render anaerobic digestion self-sustaining. Two-stage digesters with separate acidification stages allow for the production of green hydrogen and short-chain fatty acids, which are promising industrial products. Heat shocks can be used to foster the production of these products, the practical applicability of this treatment is often not addressed sufficiently, and the presented work therefore aims to close this gap. Batch experiments were conducted in 5L double-walled tank reactors incubated at 37°C. Short microwave heat shocks of 25min duration and exposure times of 5-10min at 80°C were performed and compared to oven heat shocks. Pairwise experimental group differences for gas production and chemical parameters were determined using ANOVA and post-hoc tests. High-throughput 16SrRNA gene amplicon sequencing was performed to analyse taxonomic profiles. After heat-shocking the entire seed sludge, the highest hydrogen productivity was observed at a substrate load of 50g/l with 1.09molH2/molhexose. With 1.01molH2/molhexose, microwave-assisted treatment was not significantly different from oven-based treatments. This study emphasised the better repeatability of heat shocks with microwave-assisted experiments, revealing low variation coefficients averaging 29%. The pre-treatment with microwaves results in a high predictability and a stronger microbial community shift to Clostridia compared to the treatment with the oven. The pre-treatment of heat shocks supported the formation of butyric acid up to 10.8g/l on average, with a peak of 24.01g/l at a butyric/acetic acid ratio of 2.0. The results support the suitability of using heat shock for the entire seed sludge rather than just a small inoculum, making the process more relevant for industrial applications. The performed microwave-based treatment has proven to be a promising alternative to oven-based treatments, which ultimately may facilitate their implementation into industrial systems. This approach becomes economically sustainable with high-temperature heat pumps with a coefficient of performance (COP) of 4.3.

Exploration and Construction of Professional Curriculum System in the Field of Intelligent Manufacturing Based on Data Analysis

Intelligent manufacturing is an important means of developing strategic emerging industries and accelerating the formation of a modern industrial system. Currently, many universities are upgrading their related majors or offering new majors such as Intelligent Manufacturing Engineering to provide talent for the field of intelligent manufacturing. Due to the lack of integrated resources between industry and education in the field of intelligent manufacturing, it is difficult for universities to strengthen the correlation between the professional curriculum system and the industry when opening new majors or upgrading majors. With the integration of new generation information technology and manufacturing technology, the country plans to transform traditional enterprises into digital, information-based, and intelligent enterprises, and cultivate innovative, technical, and skilled talents that adapt to the development of intelligent manufacturing. It has become a new development strategy given to vocational colleges by the times. This article first obtains information on professional courses related to intelligent manufacturing and artificial intelligence offered in the region, and then uses Python data analysis technology to conduct statistical analysis on the collected professional courses. The analysis results provide reference and inspiration for universities to offer majors related to intelligent manufacturing.

Evaluating cryptographic vulnerabilities created by quantum computing in industrial control systems

AbstractQuantum computing is expected to eventually be able to break the public‐key cryptography algorithms currently used throughout information technology (IT) infrastructure, undermining foundational tools used to maintain information security across the country's critical infrastructure. As these systems converge, the security posture of operational technology (OT) systems has to adapt to a new threat landscape and adopt some of the same security controls as those used in enterprise IT, especially cryptographic controls that rely on public‐key cryptography, which are ubiquitous in enterprise IT systems. Operators and manufacturers of industrial control systems (ICSs) and OT systems will need to understand and address the unique ways in which these systems will be vulnerable to adversaries equipped with quantum computers. We assessed quantum computing–facilitated cryptographic vulnerabilities in ICSs and OT systems to identify the issues in need of the most‐urgent attention from ICS and OT owners, operators, and manufacturers. Employing a modified consequence‐driven, cyber‐informed engineering process informed by literature review and analysis, we mapped protocols using or enabling cryptographic protections across common ICS network topologies as part of an assessment of how an attacker could cause harm, especially damaging physical consequences resulting from manipulation of cyber–physical systems, through the cryptographic compromise of ICS and OT networks and components. Our evaluation of identified and ranked risks to related control systems was also informed by relevant literature on ICS risk assessment and mitigation, cyber harms, and historical attacks on critical infrastructure. Using our analysis, we assessed the overall difficulty in mitigating risk from each of the identified vulnerability archetypes. The resulting analysis identified vulnerabilities associated with code‐signing processes as the highest priority for attention when updating systems for a postquantum future. This risk was followed by vulnerabilities associated with forged certificates for identification and vulnerabilities associated with forged session keys, identified as lower priorities but still of concern. Informed by our findings, we offer recommendations related to the protection of these vulnerabilities and the improvement of ICS security in developed systems.

Spatial coding metastructure for single-sensor impact region recognition

Abstract The rapid development of aircraft has created a strong demand for structural health monitoring, but current methods that rely on multiple sensor fusion suffer from complex hardware systems. Computational sensing with metastructures provides a promising approach to reduce sensing cost, but the lack of calibrated information makes it challenging to identify impact regions. In this study, we propose a concept of spatial coding metastructure for impact region recognition with a single sensor. Owing to the multi-order local resonance effect, the metastructures are capable of producing multiple vibration modulations over a wide frequency band. We demonstrate that the frequency-dependent vibration modulation effects of the metastructures on different test regions are distinguishable, a characteristic referred to as spatial coding. This characteristic enables impact regions to be accurately recognized with only a single sensor by using machine learning methods. Our work not only presents promising application prospects for condition monitoring of aircraft and other mechanical systems, but also inspires the development of safer and more efficient systems in various industries.

Digital ergonomic assessment to enhance the physical resilience of human-centric manufacturing systems in Industry 5.0

The emergence of Industry 5.0 promotes the creation of human-centric values. To fulfill this objective, Internet of Things (IoT) technologies are increasingly being exploited to digitize the human factor and monitor the ergonomics of manual manufacturing systems. These digital assessments, combined with computational algorithms, contribute to the establishment of socially inclusive workplaces while offering detailed insights to safeguard the health of the aging workforce. In this scenario, this study proposes a digital architecture for evaluating the European Assembly Worksheet (EAWS) in human-centric manufacturing systems. Three distinct enabling technologies are leveraged to acquire heterogeneous data streams. A radio-frequency-based smart glove detects the operator’s interactions with the surrounding environment, while a network of marker-less cameras and a four-channel surface Electromyography (sEMG) system capture body joint movements and muscular contractions of the upper limbs, respectively. The acquired data are processed by computational algorithms to define an EAWS-driven set of Key Risk Indicators (KRIs), embedded in an ergonomic decision support system. These risk metrics highlight operator-driven process weaknesses in musculoskeletal, muscular, and material handling dimensions. Finally, the validity of the proposed digital architecture is demonstrated in an industrial-related pilot environment, where an operator assembles a piece of home furniture.

STUDY OF THE DESIGN OF RAILWAY TRACKS OF INDUSTRIAL ENTERPRISES WITHIN THE AREAS OF SMOOTH TRACK EXPANSION

The goal. Railway sidings of industrial enterprises are the shippers and receivers of goods, which determine their main nomenclature for transportation by mainline rail transport. The length of railway sidings of industrial enterprises varies widely, from a few hundred meters to hundreds of kilometers, including the length of the siding of PJSC ArcelorMittal Kryvyi Rih exceeding 700 km. The combination of factors such as the presence of technological transportation on the sidings, the development of the industrial enterprises' transportation system over time, and the master plan of the main production facilities leads to the need to apply railway transport design standards for severe and especially severe conditions. This is mainly expressed in reducing the radii of curved track sections to the minimum possible values. When using reinforced concrete sleepers of the Sh6 type, it is possible to arrange a track gauge of 1539 mm in curved sections. But currently, there is no approved design for smooth track widening sections on reinforced concrete sleepers in front of curves with radii of less than 300 meters. There is also a reasonable need to increase the track gauge to at least 1540 mm in curves of such radii. Together with the limited service life of wooden sleepers when they are laid in areas of smooth track widening compared to reinforced concrete sleepers, this necessitates the development of a track structure on reinforced concrete sleepers within the area of smooth track widening. Methods. Methods of scientific analysis and synthesis of the track development structure, methods of analytical geometry. Results. Based on the analysis of the design of intermediate fasteners of the KB50 type, the design of a section of smooth track widening using reinforced concrete sleepers of types Sh1-1 and Sh6 and rails R50 is proposed. The track widening from 1520 to 1545 mm is achieved by developing the order of laying sleepers of different types and turning the KB50 substrates. In this case, the length of the section of smooth track widening from 1520 mm to 1545 mm is 2800 mm, and the actual deviation is 8.9‰. Practical significance. The use of the considered structure within the areas of smooth track widening, provided that the results of trial operation and testing of the established procedure are positive, will reduce the operating costs associated with the current maintenance of industrial enterprises' tracks, the parameter of which correspond to severe and especially severe design conditions.

The role of technology in modern industrial processes: a comparative analysis of automated, automatic and mechanical systems

In the modern technological sphere, systems are categorized into various types based on their level of complexity and functional capabilities. The primary types are mechanical, automatic, and automated systems. Each of these types has its unique characteristics and areas of application. Mechanical systems are the simplest of all. They consist primarily of physical components such as gears, levers, and springs, which interact to perform specific tasks. These systems typically lack built-in control or regulation mechanisms, and their operation is based on basic mechanical principles. Examples of mechanical systems include simple clock mechanisms or traditional measuring devices. Automatic systems represent an evolutionary step beyond mechanical systems, as they include elements for automatic control. These may be electrical or electronic components that enable the system to perform certain operations without direct human intervention. For example, automatic doors or thermostats that regulate room temperature are examples of such systems. They can respond to changing conditions and perform tasks based on predefined parameters. Automated systems, in turn, are the most complex and integrated. They combine automatic control with software and advanced management systems, allowing them to adapt to changing environmental conditions and make decisions independently. Automated systems may include elements of artificial intelligence and machine learning, enabling them to perform complex tasks such as data processing or optimizing production processes. Examples include industrial robotic lines or management systems in distribution networks. Thus, the main differences between these systems lie in their level of complexity and functional capabilities: mechanical systems are based on simple physical principles, automatic systems contain elements of automatic control, and automated systems provide a high level of integration and autonomy.

Double-Layer Distributed and Integrated Fault Detection Strategy for Non-Gaussian Dynamic Industrial Systems.

Currently, with the increasing scale of industrial systems, multisensor monitoring data exhibit large-scale dynamic Gaussian and non-Gaussian concurrent complex characteristics. However, the traditional principal component analysis method is based on Gaussian distribution and uncorrelated assumptions, which are greatly limited in practice. Therefore, developing a new fault detection method for large-scale Gaussian and non-Gaussian concurrent dynamic systems is one of the urgent challenges to be addressed. To this end, a double-layer distributed and integrated data-driven strategy based on Laplacian score weighting and integrated Bayesian inference is proposed. Specifically, in the first layer of the distributed strategy, we design a Jarque-Bera test module to divide all multisensor monitoring variables into Gaussian and non-Gaussian blocks, successfully solving the problem of different data distributions. In the second layer of the distributed strategy, we design a dynamic augmentation module to solve dynamic problems, a K-means clustering module to mine local similarity information of variables, and a Laplace scoring module to quantitatively evaluate the structural retention ability of variables. Therefore, this double-layer distributed strategy can simultaneously combine the different distribution characteristics, dynamism, local similarity, and importance of variables, comprehensively mining the local information of the multisensor data. In addition, we develop an integrated Bayesian inference strategy based on detection performance weighting, which can emphasize the differential contribution of local models. Finally, the fault detection results for the Tennessee Eastman production system and a diesel engine working system validate the superiority of the proposed method.

PVC Dechlorination for Facilitating Plastic Chemical Recycling: A Systematic Literature Review of Technical Advances, Modeling and Assessment

Polyvinyl chloride (PVC) resins are widely used in modern society due to their acid and alkali resistance, low cost, and strong insulation properties. However, the high chlorine (Cl) content in PVC poses significant challenges for its recycling. This study reviews the treatment processes, model construction, and economic and environmental assessments to construct a methodological framework for the sustainable development of emerging dechlorination technologies. In terms of treatment processes, this study summarizes three types of processes, pretreatment, simultaneous dechlorination during chemical recycling, product purification, and emphasizes the necessity of dechlorination treatment from a systematic perspective. Additionally, the construction of models for dechlorination processes is investigated from the laboratory to the industrial production system to macro-scale material, in order to evaluate the potential inventory data and material metabolism behaviors. This review also summarized the methodology framework of Techno-Economic Analysis (TEA) and Life Cycle Assessment (LCA), which can be applied for evaluation of the economic and environmental performance of the dechlorination processes. Overall, this review provides readers with a comprehensive perspective on the state-of-the-art for PVC dechlorination technologies, meanwhile offering sustainable guidance for future research and industrial applications of chemical recycling of PVC waste.

A Review of the Energy-Saving Potential of Phase Change Material-Based Cascaded Refrigeration Systems in Chinese Food Cold Chain Industry

As the global demand for food increases, the efficiency and environmental sustainability of refrigeration systems have become increasingly critical issues. Cascaded refrigeration systems (CRSs) are widely used in the Chinese food cold chain due to their capacity to meet a wide range of temperature requirements. However, energy consumption of these systems is always high. If phase change materials (PCMs) are combined with the refrigeration systems, the energy-saving effect is remarkable. The paper reviews the integration of PCMs within CRS, focusing on their potential to reduce energy consumption, thereby improving food safety and reducing reliance on conventional, electricity-intensive refrigeration methods. The study categorizes and explores the low-temperature applications of PCMs in CRS, providing novel insights into enhancing energy efficiency in food cold chain logistics. Despite most PCM research focusing on single-stage systems, this review innovates by introducing PCM integration in multistage cascade systems, which is particularly relevant for low-temperature requirements. The discussion encompasses the structure, working fluids, and applications of CRSs in the cold chain, emphasizing the role of PCMs in sustainable cold chain management. The review concludes by highlighting the need for further research on PCMs in CRS, especially regarding their economic viability and large-scale implementation potential.

High recovery design of reverse osmosis process with high permeate water quality and low wastewater discharge for ultra-pure water production

Ultra-pure water (UPW) for electronic industry is produced via many unit processes including reverse osmosis (RO), pretreatments, membrane degasifier, and ion exchange processes. Generally, 2-pass RO system is adopted in UPW production process to remove ionic and organic matters to meet water quality requirements of post-treatments. Since RO concentrate occupies most of wastewater discharged from UPW production process, high recovery design is beneficial to reduce wastewater discharge. According to the solution-diffusion model, permeate concentrations increase at higher feed concentrations, which may limit to increase RO recovery. Interestingly, the bench-scale 2-pass RO test using five commercial membrane modules revealed permeate concentrations were not affected by feed concentrations below a critical value (35 mg/L as NaCl in this work). This means the first-pass RO recovery can be increased without decreasing permeate water quality as far as second-pass RO feed concentrations are below the critical values. Various 2-pass UPW-RO system designs (250 mg/L as NaCl of feed concentration) were analyzed using an industrial RO system simulator to investigate the effect of the first- and second-pass recovery. The simulation works found that increasing the first- and second-pass recovery decreased wastewater discharge, energy consumption, and the number of membrane modules without degrading permeate water quality.

Anomaly Detection Method for Industrial Control System Operation Data Based on Time-Frequency Fusion Feature Attention Encoding.

Anomaly detection in industrial control system (ICS) data is one of the key technologies for ensuring the security monitoring of ICSs. ICS data are characterized as complex, multi-dimensional, and long-sequence time-series data that embody ICS business logic. Due to its complex and varying periodic characteristics, as well as the presence of long-distance and misaligned temporal associations among features, current anomaly detection methods in ICS are insufficient for feature extraction. This paper proposes an anomaly detection method named TFANet, based on time-frequency fusion feature attention encoding. Considering that periodic variations are more concentrated in the frequency domain, this method first transforms the time-domain data into the frequency domain, obtaining both amplitude and phase data. Then, these data, together with the original time-series data, are used to extract features from two perspectives: long-term temporal changes and long-distance associations. Finally, the six features learned from both the time and frequency domains are fused, and the feature weights are calculated using an attention mechanism to complete the anomaly classification. In multi-classification tasks on three ICS datasets, the proposed method outperforms three popular time-series models-iTransformer, Crossformer, and TimesNet-across five metrics: accuracy, precision, recall, F1 score, and AUC-ROC, with average improvements of approximately 19%, 37%, 31%, 35%, and 22%, respectively.

INDUSTRIAL DEVICE CONTROL USING WI-FI MODULE

This paper presents a design and prototype implementation of new industrial automation system that uses Wi-Fi technology as a network infrastructure connecting its parts. The proposed system is better from the scalability and flexibility point of view than the commercially available industrial automation systems. In Industry we have different types of loads at different locations. We can control all loads at a same time from one place (control room) without connecting any physical wire between loads and control room, in this paper we are using WI-FI module, IOT, relay, voltage sensor, current sensor, speed sensor. In this paper Wi-Fi is being used by phone and the loads are operated with it. In this paper we should not connect AC loads directly to microcontroller since AC may enter into controller due to this our controller may bedestroyed. To avoid such type of drawback we need some drivers. In this paper weare using relay as load controller. Key word: Sensor, Microcontroller, IOT, Motor, Relay

CFD-DEM coupled study of erosion resistance characteristics of ribbed walls

Industrial bulk material transfer systems are exposed to high erosion risk due to prolonged scouring by particle flow. In order to improve the erosion resistance of the system components, this study proposes a wear-resistant improvement scheme by adding square and triangular ribs on the wall surface. A coupled CFD-DEM method was used to analyse the abrasion characteristics of particle flow hitting the flat and ribbed wall surfaces at different particle incidence angles, particle velocities and particle volume fractions. The results show that square ribbed plate is more targeted to reduce the erosion ratio of the groove surface and transfer the risk to the ribs, whereas triangular ribbed plate provides an optimal balance between sacrificial velocity and erosion resistance of the ribbed structure; moreover, square ribbed plate is slightly more capable of transferring the maximum wear to the ribs to reduce the risk of perforation of the wall surface. As the particle velocity increased from 5 m/s to 25 m/s, the triangular ribbed plate reduced the erosion ratio by up to 45 %; both square and triangular ribbed plate groove surfaces reduced the maximum wear rate by about 65 % and 35 %, respectively. With the increase of particle volume fraction from 0.025 % to 0.125 %, the erosion ratios of the square and triangular ribbed plates decreased rapidly by up to 16 % and 73 %, respectively; the groove surface of the square ribbed plate decreased by about 63 % of the maximum wear rate, while the groove surface of the triangular ribbed plate decreased by up to 48 % of the maximum wear rate.

Optimizing multivariate alarm systems: A study on joint false alarm rate, and joint missed alarm rate using linear programming technique

In modern complex industrial systems, multiple process variables interact with one another. The role of alarm systems in ensuring the safety of these systems is of utmost importance. Consequently, there is an increasing value placed on the assessment of the performance of multivariate alarm systems. As the dimensions of the system and the number of variables grow, designing optimal parameters for the multivariate alarm system using traditional approaches such as probability density function estimation becomes increasingly convoluted. In this paper, an approximate method is proposed for calculating two indices known as the Joint False Alarm Rate (JFAR) and Joint Missed Alarm Rate (JMAR), which are used to evaluate the performance of multivariate alarm systems. These indices are computed using the multivariate Markov chain method. The Markov chain is constructed by solving an optimal Linear Programming (LP) problem. Subsequently, joint indices are defined based on steady state estimations of a multivariate Markov chain. To validate the theoretical results obtained on the JFAR and JMAR and to demonstrate the proposed performance assessment and alarm system design procedures, numerical example and an industrial case study are provided.

Evaluation of heat transfer for unsteady thin film flow of mono and hybrid nanomaterials with five different shape features

Recent advancement in nanotechnology brings the idea of hybrid nanomaterials which offer distinguish applications in thermal reservoirs, cooling systems, energy applications, chemical engineering, vehicle engines etc. The understating of shape features for hybrid nanomaterials is quite essential as such consequences highly influenced various thermal properties like viscosity, thermal conductivity, optical properties, stability etc. The objective of current work is to examine heat transfer analysis due to thin film unsteady flow of hybrid nanofluid. The properties of hybrid nanofluid are justified for entertaining the copper (Cu), aluminium oxide (Al2O3) nanoparticles with water (H2O) base fluid. Additionally, applications of viscous dissipation, heat source and nonlinear radiated effects are attributed to current flow problem. The thermal properties of nanoparticles are examined in presence of five shape features consisting of blades, platelets, cylinders, bricks and spheres. Numerical simulations of problem are performed via Runge-Kutta-Fehlberg method. Comparative heat transfer is performed for mono nanofluid (Cu/H2O) and hybrid nanofluid (Cu−Al2O3)//H2O. It has been observed that heat transfer enhancement is more stable for cylindrical particles as compared to spherical nanoparticles. The skin friction enhances due to Hartmann number for both mono nanofluid (MNF) and hybrid nanofluid (HNF). Current results claim applications in coating thin films, lubrication systems, improving the thermal efficiency in thermal and industrial systems, heat exchangers, cooling systems etc.

Ranking guidance actions to support engineers in fulfilling process constraints

AbstractIn safety‐critical systems engineering, regulations such as Automotive SPICE, ISO26262, or ED‐109A mandate software quality assurance measures to provide evidence that the developed system is high quality. The constraints that define quality assurance conditions during the engineering life cycle are often non‐trivial. This paper addresses the challenges, engineers face who are unfamiliar with the precise constraints of various projects (e.g., when newly joining a company or switching between departments). Understanding how to fulfill a constraint is a time‐consuming and challenging task as an engineer needs to determine the most suitable option (out of potentially many) to fulfill a constraint violation. To this end, we propose a guidance action ranking framework to provide engineers with the most relevant guidance actions. Our primary ranking algorithm analyzes in the background the actions that engineers have made in the past to resolve a constraint violation without requiring explicit feedback from them. We evaluated our framework on two real‐world data sets: an open‐source drone management and an industrial air traffic control software system. Concretely, we replay past engineering activities and measured whether, in the case of a constraint violation, our suggested guidance actions were indeed selected by the engineer. The evaluation results revealed that learning from prior guidance actions effectively identifies the most appropriate guidance actions (ranked top 1 or 2) when compared to ranking algorithms based on action simplicity and artifact property change frequency. Specifically, we achieve a median MRR of 0.95 for the first case study and 0.94 for the second case study: an improvement of 80% and 100% over the baseline. Additionally, we observed that the simplicity of a guidance action does not reliably indicate its suitability for fulfilling a constraint, whereas learning from prior change operation property out‐performed simplicity‐based ranking but did not surpass guidance frequency‐based ranking.

Generic FPGA Pre-Processing Image Library for Industrial Vision Systems.

Currently, there is a demand for an increase in the diversity and quality of new products reaching the consumer market. This fact imposes new challenges for different industrial sectors, including processes that integrate machine vision. Hardware acceleration and improvements in processing efficiency are becoming crucial for vision-based algorithms to follow the complexity growth of future industrial systems. This article presents a generic library of pre-processing filters for execution in field-programmable gate arrays (FPGAs) to reduce the overall image processing time in vision systems. An experimental setup based on the Zybo Z7 Pcam 5C Demo project was developed and used to validate the filters described in VHDL (VHSIC hardware description language). Finally, a comparison of the execution times using GPU and CPU platforms was performed as well as an evaluation of the integration of the current work in an industrial application. The results showed a decrease in the pre-processing time from milliseconds to nanoseconds when using FPGAs.

Optimized CRISPR Interference System for Investigating Pseudomonas alloputida Genes Involved in Rhizosphere Microbiome Assembly.

Pseudomonas alloputida KT2440 (formerly P. putida) has become both a well-known chassis organism for synthetic biology and a model organism for rhizosphere colonization. Here, we describe a CRISPR interference (CRISPRi) system in KT2440 for exploring microbe-microbe interactions in the rhizosphere and for use in industrial systems. Our CRISPRi system features three different promoter systems (XylS/Pm, LacI/Plac, and AraC/PBAD) and a dCas9 codon-optimized for Pseudomonads, all located on a mini-Tn7-based transposon that inserts into a neutral site in the genome. It also includes a suite of pSEVA-derived sgRNA expression vectors, where the expression is driven by synthetic promoters varying in strength. We compare the three promoter systems in terms of how well they can precisely modulate gene expression, and we discuss the impact of environmental factors, such as media choice, on the success of CRISPRi. We demonstrate that CRISPRi is functional in bacteria colonizing the rhizosphere, with repression of essential genes leading to a 10-100-fold reduction in P. alloputida cells per root. Finally, we show that CRISPRi can be used to modulate microbe-microbe interactions. When the gene pvdH is repressed and P. alloputida is unable to produce pyoverdine, it loses its ability to inhibit other microbes in vitro. Moreover, our design is amendable for future CRISPRi-seq studies and in multispecies microbial communities, with the different promoter systems providing a means to control the level of gene expression in many different environments.

Research on the path of industrial revitalization to promote rural revitalization

Industrial revitalization is the premise, foundation and key to achieving the rural revitalization strategy. Industrial revitalization is the primary task and central issue of the rural revitalization strategy. The Chinese medicinal materials industry covers the primary, secondary and tertiary industries, with a long industrial chain, high added value and strong driving force, and plays an important role in promoting rural economic and social development. Bozhou City is rich in Chinese medicinal resources, has a good foundation for the Chinese medicinal materials industry and distinctive characteristics. It is a dominant and characteristic industry and a people-enriching industry in Bozhou City and even Anhui Province. This paper investigates the development status of the rural Chinese medicinal materials industry in three counties and one district in Bozhou City, analyzes the advantages, disadvantages, opportunities and challenges of the Chinese medicinal materials industry in Bozhou City in promoting rural industrial revitalization. On this basis, a systematic and specific implementation path and guarantee system for the Chinese medicinal materials industry in Bozhou City to help rural industrial revitalization are designed, including top-level design, improving infrastructure construction, cultivating modern business organizations, integrating the development of Chinese medicinal materials industry, and strengthening the construction of various industrial chains of rural Chinese medicinal materials production, processing, warehousing and logistics, and brand marketing, etc., and building a guarantee system in four aspects: organizational coordination, financial support, talent training, and scientific and technological support.