High Degree Of Automation Research Articles

Noncontact visualization of multiscale defects in CFRP composites using eddy current testing with T-R probe

Carbon fiber reinforced polymer (CFRP) is widely used in modern industries, and damages may occur from manufacturing to utilization, highlighting the importance of CFRP detection. As being a multi-phase structural material, the CFRP's mesostructural features contained in eddy current signals can obscure macroscopic defect characteristics. Phase rotation is a common method for eddy current signal processing, but the specific criteria for evaluation of processing effect are lacking. This paper proposes three reliable criteria for assessment of the phase rotation processing effects of Transmitter-Receiver (T-R) probe signals, namely: signal overlap ratio (SOR), signal-to-noise ratio (SNR), and image average gradient (IAG). To begin, the SOR serves as a crucial indicator for assessing signal similarity and the degree of overlap, with a low SOR indicating the method's effectiveness in distinguishing defect characteristics. Subsequently, by comparing the SNRs of images, the clarity of defects under different rotation angles can be effectively quantified. Finally, a novel criterion, i.e. the IAG, is introduced. What distinguishes this criterion is its higher degree of automation, facilitating a comprehensive evaluation of processing effects without excessive subjective intervention. After analyzing these criteria, it is clear that the IAG criterion excels in automation and objectivity for evaluating eddy current signal processing effects.

Enhancing tensile properties of MIG welded AA6061 joints: Effect of pulse mode and post-weld heat treatment

Metal-Inert Gas (MIG) welding is one of the most important welding technologies commonly used in the manufacturing industry due to its high degree of automation and welding adaptability. However, softening is prone to occur in fusion zone (FZ) and heat affected zone (HAZ) of AA6061 MIG welded joint, which limits its application. In this work, AA6061 was welded by MIG welding with different pulse modes, and the post-welding heat treatment was carried out. The results show that the dual pulse MIG (DP-MIG) and PWHT can significantly improve the mechanical properties of AA6061 butt joint, and its ultimate tensile strength (UTS) is 331.3 MPa, even more than 90% of the base material (BM). In this paper, the microstructure of welded joints under different pulse conditions before and after PWHT was compared, and the relationship between the welding process, microstructure, and mechanical properties was established Furthermore, the influence mechanisms of pulse mode and PWHT on the mechanical properties of welded joints were explained in detail.

The Doppler wind, temperature, and aerosol RMR lidar system at Kühlungsborn, Germany – Part 1: Technical specifications and capabilities

Abstract. This paper describes the technical specifications of the extensions made to the middle-atmospheric lidar facility at the Leibniz Institute of Atmospheric Physics in Kühlungsborn, Germany (54.12° N, 11.77° E). The upgrade complements the existing daylight-capable Rayleigh–Mie–Raman (RMR) temperature lidar with a nighttime-only RMR wind–temperature lidar. The new system comprises an independent lidar with laser, telescopes, and detectors, which is synchronized with and adapted to the (old) temperature lidar. As a result, with the combination of RMR lidars the atmosphere is probed with three (vertical and tilted) beams. This work intends to highlight the recent innovations in the construction of a Doppler–Rayleigh lidar system using the single-edge iodine-cell technique, which allows for the simultaneous measurement of wind, temperature, and aerosols. We will detail supporting subsystems that allow for a high degree of lidar automation and concisely provide key technical information about the system that will support readers in the development of additional RMR wind–temperature lidar systems. We show an example of time-resolved temperature and wind soundings reaching up to ∼ 90 km. These data agree well with ECMWF-IFS profiles between 35 and ∼ 50 km but show a much larger variability above. In the companion article, we will present the algorithm design and uncertainty budgets associated with the data processing chain.

Beyond conventional bounds: Surpassing system limits for stereotactic ablative (SAbR) lung radiotherapy using CBCT-based adaptive planning system.

Online adaptive radiotherapy relies on a high degree of automation to enable rapid planning procedures. The Varian Ethos intelligent optimization engine (IOE) was originally designed for conventional treatments so it is crucial to provide clear guidance for lung SAbR plans. This study investigates using the Ethos IOE together with adaptive-specific optimization tuning structures we designed and templated within Ethos to mitigate inter-planner variability in meeting RTOG metrics for both online-adaptive and offline SAbR plans. We developed a planning strategy to automate the generation of tuning structures and optimization. This was validated by retrospective analysis of 35 lung SAbR cases (total 105 fractions) treated on Ethos. The effectiveness of our planning strategy was evaluated by comparing plan quality with-and-without auto-generated tuning structures. Internal target volume (ITV) contour was compared between that drawn from CT simulation and from cone-beam CT (CBCT) at time of treatment to verify CBCT image quality and treatment effectiveness. Planning strategy robustness for lung SAbR was quantified by frequency of plans meeting reference plan RTOG constraints. Our planning strategy creates a gradient within the ITV with maximum dose in the core and improves intermediate dose conformality on average by 2%. ITV size showed no significant difference between those contoured from CT simulation and first fraction, and also trended towards decreasing over course of treatment. Compared to non-adaptive plans, adaptive plans better meet reference plan goals (37%vs. 100% PTV coverage compliance, for scheduled and adapted plans) while improving plan quality (improved GI (gradient index) by 3.8%, CI (conformity index) by 1.7%). We developed a robust and readily shareable planning strategy for the treatment of adaptive lung SAbR on the Ethos system. We validated that automatic online plan re-optimization along with the formulated adaptive tuning structures can ensure consistent plan quality. With the proposed planning strategy, highly ablative treatments are feasible on Ethos.

ForCEPSS—A framework for cardiac electrophysiology simulations standardization

Background and Objective:Simulation of cardiac electrophysiology (CEP) is an important research tool that is increasingly being adopted in industrial and clinical applications. Typical workflows for CEP simulation consist of a sequence of processing stages starting with building an anatomical model and then calibrating its electrophysiological properties to match observable data. While the calibration stages are common and generalizable, most CEP studies re-implement these steps in complex and highly variable workflows. This lack of standardization renders the execution of computational CEP studies in an efficient, robust, and reproducible manner a significant challenge. Here, we propose ForCEPSS as an efficient and robust, yet flexible, software framework for standardizing CEP simulation studies. Methods and Results:Key processing stages of CEP simulation studies are identified and implemented in a standardized workflow that builds on openCARP11https://opencarp.org/. Plank et al. (2021) and the Python-based carputils22https://git.opencarp.org/openCARP/carputils. framework. Stages include (i) the definition and initialization of action potential phenotypes, (ii) the tissue scale calibration of conduction properties, (iii) the functional initialization to approximate a limit cycle corresponding to the dynamic reference state according to an experimental protocol, and, (iv) the execution of the CEP study where the electrophysiological response to a perturbation of the limit cycle is probed. As an exemplar application, we employ ForCEPSS to prepare a CEP study according to the Virtual Arrhythmia Risk Prediction protocol used for investigating the arrhythmogenic risk of developing infarct-related ventricular tachycardia (VT) in ischemic cardiomyopathy patients. We demonstrate that ForCEPSS enables a fully automated execution of all stages of this complex protocol. Conclusion:ForCEPSS offers a novel comprehensive, standardized, and automated CEP simulation workflow. The high degree of automation accelerates the execution of CEP simulation studies, reduces errors, improves robustness, and makes CEP studies reproducible. Verification of simulation studies within the CEP modeling community is thus possible. As such, ForCEPSS makes an important contribution towards increasing transparency, standardization, and reproducibility of in silico CEP experiments.

The first detection of mpox virus DNA from wastewater in China

Wastewater monitoring may be a valuable early surveillance tool for studying mpox virus (MPXV) circulation in China, a country with high population density and very few mpox patients. To evaluate the effectiveness of wastewater monitoring for MPXV in detecting local hidden transmission of the epidemic in the early period, the Chinese Center for Disease Control and Prevention initiated a wastewater monitoring program for MPXV in China in July 2023. To enhance the monitoring sensitivity of the program, an MPXV monitoring point was established in a gathering place of high-risk mpox population. Three different concentration methods, PEG precipitation, ultrafiltration, and magnetic beads method were evaluated and compared. Due to its high recovery efficiency, low limit of detection, and high degree of automation, the magnetic beads method was selected for the daily surveillance of MPXV in wastewater. On September 5, 2023, MPXV DNA was detected at the MPXV monitoring point in Zibo City, marking the first instance of MPXV detection of MPXV in wastewater in China. Next-generation sequencing was conducted on the MPXV genome obtained from the positive wastewater, positive environmental samples, and the single case of mpox in Zibo in September. The results showed that the genotypes of these three genomes were different but all belong to the IIb branch of the C.1 lineage, indicating a probably hidden transmission of mpox. Wastewater monitoring is potentially an effective early surveillance tool for tracking the spread of MPXV in areas with high population density and very few mpox patients.

Effect of electron beam irradiation on raw goat milk: microbiological, physicochemical and protein structural analysis.

Goat milk is considered a nutritionally superior resource, owing to its advantageous nutritional attributes. Nevertheless, it is susceptible to spoilage and the persistence of pathogens. Electron beam irradiation stands as a promising non-thermal processing technique capable of prolonging shelf life with minimal residue and a high degree of automation. The effects of electron beam irradiation (2, 3, 5, and 7 kGy) on microorganisms, physicochemical properties, and protein structure of goat milk compared with conventional pasteurized goat milk (PGM) was evaluated. It was found that a 2 kGy electron beam irradiation reduces the total microbial count of goat milk by 6-logs, and the irradiated goat milk protein secondary structure showed a significant decrease in ɑ-helix content. Low irradiation doses led to microaggregation and crosslinking. In contrast, high doses (≥ 5 kGy) slightly disrupted the aggregates and decreased the particle size, disrupting the microscopic surface structure of goat milk, verified by scanning electron microscopy and confocal laser scanning microscopy. The irradiation of goat milk with a 2 kGy electron beam may effectively inactivate harmful microorganisms in the milk and maintain/or improve the physicochemical quality and protein structure of goat milk compared to thermal pasteurization. © 2024 Society of Chemical Industry.

Accuracy enhancement and joint calibration method of multi-station triangulation network based on absolute ranging

Precision measurement methods and technologies for large-scale three-dimensional coordinates are in high demand in advanced equipment manufacturing. The multi-station triangulation network represented by the rotary-laser scanning measurement system has the advantages of having high precision, having multitask parallel measurement capability, and having a high degree of automation. It is widely used in the docking of large components, quality control of key points, and collaborative positioning of production equipment. Nevertheless, due to the limitations in the measurement principle, the positioning accuracy along the depth direction is notably lower when compared to other directions. This difference becomes more pronounced with increasing distance. This paper proposes a method to address this issue by integrating a distance measurement station into the network. A novel, to the best of our knowledge, cooperative target, coupled with a high-dynamic beam guidance mechanism, is designed to achieve fast absolute distance measurement to the target. The weighted fusion of the distance and angle observations effectively enhances the measurement accuracy while preserving the advantages of highly automated measurement. Additionally, we introduce a joint calibration method for extrinsic parameters of multi-type stations. High-precision absolute distances are utilized to establish optical scale bars, complemented by the incorporation of physical scale bars, thereby obviating the necessity for using external reference instruments such as laser trackers. Finally, a series of experimental verifications demonstrate the effectiveness of calibration and measurement methods. The root mean square error of all measured points drop to 42.6% of that the triangulation method measures.

Morphosyntactic prediction in automatic neural processing of spoken language: EEG evidence

Automatic parsing of syntactic information by the human brain is a well-established phenomenon, but its mechanisms remain poorly understood. Its best-known neurophysiological reflection is the so-called early left-anterior negativity (ELAN) component of event-related potentials (ERPs), with two alternative hypotheses for its origin: (1) error detection, or (2) morphosyntactic prediction/priming. To test these alternatives, we conducted two experiments using a non-attend passive design with visual distraction and recorded ERPs to spoken pronoun-verb phrases with/without agreement violations and to the same critical verbs presented in isolation without preceding pronouns. The results revealed an ELAN at ∼130-220 ms for pronoun-verb gender agreement violations, confirming a high degree of automaticity in early morphosyntactic parsing. Critically, the strongest ELAN was elicited by verbs outside phrasal context, which suggests that the typical ELAN pattern is underpinned by a reduction of ERP amplitudes for felicitous combinations, reflecting syntactic priming/predictability between related words/morphemes (potentially mediated by associative links formed during previous linguistic experience) rather than specialised error-detection processes.

AutoEFT: Automated operator construction for effective field theories

The program AutoEFT is described. It allows one to generate Effective Field Theories (EFTs) from a given set of fields and symmetries. Allowed fields include scalars, spinors, gauge bosons, and gravitons. The symmetries can be local or global Lie groups based on U(1) and SU(N). The mass dimension of the EFT is limited only by the available computing resources. The operators are stored in a compact, human and machine-readable format. Aside from the program itself, we provide input files for EFTs based on the Standard Model and a number of its extensions. These include additional particles and symmetries, EFTs with minimal flavor violation, and gravitons. Program summaryProgram title:AutoEFTCPC Library link to program files:https://doi.org/10.17632/z8xm2hpbsp.1Developer's repository link:https://gitlab.com/auto_eft/autoeftLicensing provisions: MIT licenseProgramming language:PythonNature of problem: The bottom-up construction of an Effective Field Theory (EFT) which describes physics below a certain energy scale Λ requires obtaining a set of operators, composed of fields with mass m≪Λ, that are invariant under certain symmetries. One is primarily interested in complete sets of independent operators, called operator bases. Their construction for a given mass dimension of the operators is nontrivial due to algebraic and kinematic relations that may render different operators redundant. Except for the lowest mass dimensions, the number of operators is so large that the task of constructing an explicit EFT operator basis requires a high degree of automation on a computer. In addition, an automated approach will allow one to immediately take into account newly postulated or discovered light particles beyond the Standard Model.Solution method: Based on the group theoretical techniques and concepts established in Refs. [1–9] and in particular Refs. [10,11], we developed the program AutoEFT, capable of constructing a non-redundant on-shell operator basis for general EFTs and arbitrary mass dimension. Provided a suitable model file, the respective operator basis is generated explicitly, including contractions of the symmetry group indices, in a fully automated fashion. Due to the generality of the algorithm, it can be applied to a variety of low-energy scenarios. The underlying low-energy theory is encoded in a model file which defines the symmetries and the field content. The fairly simple format enables the user to compose their own model files and to construct the respective operator basis with minimal effort.Additional comments including restrictions and unusual features: In its current form, AutoEFT is restricted to theories including particles with spin 0, 1/2, 1, and 2, where the latter two are considered massless. In addition, AutoEFT only constructs operators that mediate proper interactions, meaning that any operator must be composed of at least three fields. The internal symmetries must be given as factors of U(1) and SU(N) groups. In principle, operator bases can be generated for any mass dimension, which is, however, limited by the available computing resources.

A Comparative Study on the Operational Efficiency of Joystick and Touch Screen Control Methods for Sugarcane Harvesters

Reducing cumbersome mechanical control components is one of the trends of modern agricultural machinery towards a high degree of automation. Whether the control components of sugarcane harvesters can gradually be replaced by central control screens, similar to car cabins, is an unresolved question. At the level of human machine interaction, this involves comparing the efficiency between joystick and touch screen control. This paper conducts a simulated experiment to compare and study the efficiency and user experience of joystick and touch screen control in adjusting the topper and base cutter heights of sugarcane harvesters, aiming to provide a reasonable basis for the design of control interfaces in sugarcane harvester cabins. The electromyographic signals, experiment duration, and subjective cognitive evaluations of participants in both the topper and base cutter groups were analyzed. The results showed that the efficiency, learnability, and ease of use of different control methods varied under different operational tasks. For the topper that corresponds to the operating behavior and height transformation in real time, joystick control demonstrated superior ease of use and operational efficiency compared to touch screen control, with weaker learnability. There was no discernible difference in muscle activation levels between the two control methods. Consequently, joystick control is deemed more suitable for the height adjustment of the topper. Regarding the base cutter with non-real-time mapping of operating behavior and height changes, no significant disparity in ease of use and learnability was observed between the two control methods. Touch screen control yielded lower muscle activation levels and garners higher overall subjective cognitive scale ratings. Thus, touch screen control is considered more suitable for base cutter height adjustment. Lastly, the paper proposes the optimal combination of software and hardware for control components in sugarcane harvester cabins, and provides an objective and multidimensional experimental analysis method for future research on similar human machine interaction interfaces.

Digital Twin Technology of Human–Machine Integration in Cross-Belt Sorting System

The Chinese express delivery industry processes nearly 110 billion items in 2022, averaging an annual growth rate of 200%. Among the various types of sorting systems used for handling express items, cross-belt sorting systems stand out as the most crucial. However, despite their high degree of automation, the workload for operators has intensified owing to the surging volume of express items. In the era of Industry 5.0, it is imperative to adopt new technologies that not only enhance worker welfare but also improve the efficiency of cross-belt systems. Striking a balance between efficiency in handling express items and operator well-being is challenging. Digital twin technology offers a promising solution in this respect. A realization method of a human–machine integrated digital twin is proposed in this study, enabling the interaction of biological human bodies, virtual human bodies, virtual equipment, and logistics equipment in a closed loop, thus setting an operating framework. Key technologies in the proposed framework include a collection of heterogeneous data from multiple sources, construction of the relationship between operator fatigue and operation efficiency based on physiological measurements, virtual model construction, and an online optimization module based on real-time simulation. The feasibility of the proposed method was verified in an express distribution center.

Determination of six halogenated solvent residues in olive oil by headspace gas chromatography

The residual amount of halogenated solvents in olive oil is an important indicator of its quality. The National Olive Oil Quality Standard GB/T 23347-2021 states that the residual amount of individual halogenated solvents in olive oil should be ≤0.1 mg/kg and that the total residual amount of halogenated solvents should be ≤0.2 mg/kg. COI/T.20/Doc. No. 8-1990, which was published by the International Olive Council, describes the standard method used for the determination of halogenated solvents in olive oil. Unfortunately, this method is cumbersome, has poor repeatability and low automation, and is unsuitable for the detection and analysis of residual halogenated solvents in large quantities of olive oil. At present, no national standard method for determining residual halogenated solvents in olive oil is available in China. Thus, developing simple, efficient, accurate, and stable methods for the determination of residual halogenated solvents in olive oil is imperative. In this paper, a method based on automatic headspace gas chromatography was established for the determination of residual halogenated solvents, namely, chloroform, carbon tetrachloride, 1,1,1-trichloroethane, dibromochloromethane, tetrachloroethylene, and bromoform, in olive oil. The samples were processed as follows. After mixing, 2.00 g (accurate to 0.01 g) of the olive oil sample was added into a 20 mL headspace injection bottle and immediately sealed for headspace gas chromatography analysis. Blank virgin olive oil was used to prepare a standard working solution and the external standard method for quantification. The solvents used in the preparation of halogenated solvent standard intermediates were investigated and methanol was selected as a replacement for N,N-dimethylacetamide to prepare a halogenated solvent standard intermediate owing to its safety. The effects of different injection times (1, 2, 3, 4, 5, 6 s), equilibration temperatures (60, 70, 80, 90, 100, 110, 120 ℃), and equilibration times (4, 5, 8, 10, 20, 30, 40 min) of the headspace sampler on the detection of the residual amounts of the six halogenated solvents were investigated. The optimal injection time and equilibration temperature were 3 s and 90 ℃, respectively. The method demonstrated good analytical performance for the six halogenated solvents when the equilibration time was 30 min. A methodological study was conducted on the optimized method, and the results showed that the six halogenated solvents exhibited good linear relationships in the range of 0.002-0.200 mg/kg, with correlation coefficients of ≥0.9991. The limits of detection (LODs) and quantification (LOQs) of 1,1,1-trichloroethane and bromoform were 0.0006 and 0.002 mg/kg, respectively. The LODs and LOQs of chloroform, carbon tetrachloride, dibromochloromethane, and tetrachloroethylene were 0.0003 and 0.001 mg/kg, respectively. The average recoveries under different spiked levels were 85.53%-115.93%, and the relative standard deviations (n=6) were 1.11%-8.48%. The established method was used to analyze 13 olive oil samples available in the market. Although no halogenated solvents were detected in these samples, a limited number of samples does not represent all olive oils. Hence, monitoring residual halogenated solvents in olive oil remains necessary for its safe consumption. The LOQs of the method for the six halogenated solvents were significantly lower than that of the COI/T.20/Doc. No. 8-1990 standard method (0.02 mg/kg). In addition, the developed method can be conducted under short operation times with high precision and degree of automation as well as good accuracy. Thus, the proposed method is suitable for the determination and analysis of the residues of the six halogenated solvents in large batches of olive oil samples.

Automated compliance checking for BIM models based on Chinese-NLP and knowledge graph: an integrative conceptual framework

PurposeThe compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information carried by BIM models have made compliance checking more challenging, and manual methods are prone to errors. Therefore, this study aims to propose an integrative conceptual framework for automated compliance checking of BIM models, allowing for the identification of errors within BIM models.Design/methodology/approachThis study first analyzed the typical building standards in the field of architecture and fire protection, and then the ontology of these elements is developed. Based on this, a building standard corpus is built, and deep learning models are trained to automatically label the building standard texts. The Neo4j is utilized for knowledge graph construction and storage, and a data extraction method based on the Dynamo is designed to obtain checking data files. After that, a matching algorithm is devised to express the logical rules of knowledge graph triples, resulting in automated compliance checking for BIM models.FindingsCase validation results showed that this theoretical framework can achieve the automatic construction of domain knowledge graphs and automatic checking of BIM model compliance. Compared with traditional methods, this method has a higher degree of automation and portability.Originality/valueThis study introduces knowledge graphs and natural language processing technology into the field of BIM model checking and completes the automated process of constructing domain knowledge graphs and checking BIM model data. The validation of its functionality and usability through two case studies on a self-developed BIM checking platform.

Design of PLC Electrical Control System

With the continuous expansion and development of factory enterprise scale, the development of automatic batching control system has also been accelerated. Batching mixing control system is a kind of raw materials mixed together according to a certain proportion, processing to produce a certain product process. This paper mainly designs and realizes the batching mixing control system of programmable logic controller (PLC). By precisely controlling the proportion of batching and the mixing time, the system is widely used in chemical, pharmaceutical, food and other fields to improve production efficiency and product quality. PLC system is a flexible, programmable electrical control equipment, because of its powerful, easy to use, high reliability characteristics, often used as the field data acquisition and equipment control. This paper mainly introduces the automatic control of liquid mixing system by Siemens PLC. The control object, hardware composition, software design and system function of the PLC based mixing, automatic mixing and automatic discharging system for two kinds of ingredients can simulate and display the whole working process of the liquid mixing system. The hardware of the system is mainly composed of S7-300 programmable controller, keys, stirring motor, frequency converter, solenoid valve and pump, etc. The programming software adopts Siemens programming software STEP7. The system transmits the collected field data to PLC through the weighing sensor, and after the PLC processes the field data logically, the corresponding control command is issued to complete the automatic control of the system. Finally, the system uses the communication interface to connect with the host computer to realize the communication between PLC and computer. The system has high degree of automation, strong flexibility, and can meet different production process requirements.

A systematic approach for simulation-based dimensioning of production systems during the concept phase of factory planning

Due to increasing globalization, market penetration, and technological progress, more products are becoming highly standardized and interchangeable. This has led to fierce price competition, forcing companies to compete for declining margins. To remain competitive in the long term, it is essential to consider both changeability and profitability during the early planning phases. The article proposes an approach for simulation studies using discrete-event simulation during the concept phase of factory planning. This approach aims to systematically dimension production resources while considering alternative scaling options, such as a higher degree of automation. By doing so, the approach facilitates the demand-oriented deployment of resources during the ramp-up phase, which helps to control and reduce manufacturing costs. The simulation experiments yield scaling paths that indicate the timing and quantity of resources required to meet changing demands. These paths form the basis for subsequent factory planning steps. For instance, the layout can incorporate the necessary space for a future automation solution that will be profitable, enabling faster adaptation to demand changes and securing competitive advantages. This is demonstrated in a use case where the approach was applied to the factory planning of a new production system for a sensor product family.

U2-Net and ResNet50-Based Automatic Pipeline for Bacterial Colony Counting.

In this paper, an automatic colony counting system based on an improved image preprocessing algorithm and convolutional neural network (CNN)-assisted automatic counting method was developed. Firstly, we assembled an LED backlighting illumination platform as an image capturing system to obtain photographs of laboratory cultures. Consequently, a dataset was introduced consisting of 390 photos of agar plate cultures, which included 8 microorganisms. Secondly, we implemented a new algorithm for image preprocessing based on light intensity correction, which facilitated clearer differentiation between colony and media areas. Thirdly, a U2-Net was used to predict the probability distribution of the edge of the Petri dish in images to locate region of interest (ROI), and then threshold segmentation was applied to separate it. This U2-Net achieved an F1 score of 99.5% and a mean absolute error (MAE) of 0.0033 on the validation set. Then, another U2-Net was used to separate the colony region within the ROI. This U2-Net achieved an F1 score of 96.5% and an MAE of 0.005 on the validation set. After that, the colony area was segmented into multiple components containing single or adhesive colonies. Finally, the colony components (CC) were innovatively rotated and the image crops were resized as the input (with 14,921 image crops in the training set and 4281 image crops in the validation set) for the ResNet50 network to automatically count the number of colonies. Our method achieved an overall recovery of 97.82% for colony counting and exhibited excellent performance in adhesion classification. To the best of our knowledge, the proposed "light intensity correction-based image preprocessing→U2-Net segmentation for Petri dish edge→U2-Net segmentation for colony region→ResNet50-based counting" scheme represents a new attempt and demonstrates a high degree of automation and accuracy in recognizing and counting single-colony and multi-colony targets.

МЕТОДИКА ОЦЕНКИ УРОВНЯ КОМФОРТНОСТИ ПАССАЖИРА В ЗАВИСИМОСТИ ОТ НАПОЛНЕНИЯ САЛОНА

The article discusses a technique for obtaining a quantitative assessment of the level of passenger comfort depending on the filling of the cabin. Within the framework of the presented research, an overview of various indicators of comfort and levels of passenger service is made, depending on the filling of the cabin. A formula for calculating the comfort of an individual passenger and the total comfort of passengers of a single passenger vehicle is proposed. The rationale for using the proposed calculation for dispatching control of passenger vehicles with a high degree of au-tomation is given.

Simultaneous determination of six nitroaromatic compounds and three anions in environmental matrices using a liquid chromatography-ion chromatography coupled system

Nitroaromatic compounds are used extensively in various fields such as dyes, pesticides, spices, pharmaceuticals, and explosives. However, the residual raw materials of these compounds accumulate in the environment and pose serious risks to human health. Chronic exposure to low concentrations of nitroaromatic compounds can cause anemia, cancer, and organ damage. Currently, Fenton oxidation and natural bioremediation are the processes most often used to eliminate nitroaromatic compounds from environmental water and soil. According to previous research, the presence of inorganic anions such as chloride, nitrite, and nitrate ions in the environmental matrix exerts an inhibitory effect on the biodegradation of nitroaromatic compounds. Furthermore, high nitrate levels in drinking water can lead to the production of nitrosamine carcinogens, which affect ecological safety and human health, in water bodies. Thus, the simultaneous determination of nitroaromatic compounds and chloride, nitrite, and nitrate ions in environmental soil and water matrices is critical for selecting appropriate nitroaromatic compound degradation methods and monitoring surface water quality. Traditional detection methods require two sample pretreatment steps and two instrumental analytical techniques to determine nitroaromatic compounds and inorganic anions in environmental matrices; moreover, these methods are time consuming, labor intensive, and error prone. Therefore, in this study, a method that combines high performance liquid chromatography (HPLC) and ion chromatography (IC) was developed to simultaneously detect nitroaromatic compounds and anions in environmental matrices. In this method, sample enrichment was achieved through bulk injection and enrichment column collection, which greatly simplified the pretreatment process. The HPLC instrument was connected to the IC instrument using two six-way valves and an enrichment column. The system operation can be divided into four stages: (A) sample loading to the quantitative ring, (B) separation of nitroaromatic compounds and anions, (C) enrichment of anions in an AG20 column, and (D) simultaneous determination of nitroaromatic compounds and anions by HPLC and IC, respectively. The time of the anions flowing out of the C18 column was determined by directly connecting the C18 column to a conductivity detector. Based on the retention times of the anions, the switching time of the six-way valve was optimized to ensure that the anions completely entered the IC column, thereby ensuring the accuracy of the method. During the chromatographic analysis stage, nitroaromatic compounds were separated and analyzed by HPLC system with a mobile phase composed of potassium phosphate buffer (pH 7.0) and acetonitrile (60∶40, v/v) at a flow rate of 1.0 mL/min; in the IC system, the anions were separated and analyzed using a 20 mmol/L sodium hydroxide aqueous solution as the mobile phase under a suppression current of 50 mA. Both anions and nitroaromatic compounds exhibited strong linear correlations within certain concentration ranges, with correlation coefficients greater than 0.993. The recoveries of the nitroaromatic compounds and anions ranged from 88.20% to 105.38% at three spiked levels, with relative standard deviations ranging from 2.0% to 11.5%. The contents of six nitroaromatic compounds and three anions in five surface water and five soil samples were determined using the developed method. Although no nitroaromatic compounds were detected in these samples, the three anions were detected at contents ranging from 0.41 to 55.3 mg/L in surface water samples, and 0.56 to 30.2 mg/kg in soil samples. Methodological validation and actual sample detection demonstrated that the proposed method has a high degree of automation, simple operation, good repeatability, high accuracy, wide applicability, and high sensitivity. Thus, this method is suitable for the rapid determination of chloride, nitrite, nitrate ions and nitroaromatic compounds in soil and water and can be extended to the simultaneous determination of inorganic ions and organic matters in other samples.

Simultaneous reaction- and analytical model building using dynamic flow experiments to accelerate process development.

In modern pharmaceutical research, the demand for expeditious development of synthetic routes to active pharmaceutical ingredients (APIs) has led to a paradigm shift towards data-rich process development. Conventional methodologies encompass prolonged timelines for the development of both a reaction model and analytical models. The development of both methods are often separated into different departments and can require an iterative optimization process. Addressing this issue, we introduce an innovative dual modeling approach, combining the development of a Process Analytical Technology (PAT) strategy with reaction optimization. This integrated approach is exemplified in diverse amidation reactions and the synthesis of the API benznidazole. The platform, characterized by a high degree of automation and minimal operator involvement, achieves PAT calibration through a "standard addition" approach. Dynamic experiments are executed to screen a broad process space and gather data for fitting kinetic parameters. Employing an open-source software program facilitates rapid kinetic parameter fitting and additional in silico optimization within minutes. This highly automated workflow not only expedites the understanding and optimization of chemical processes, but also holds significant promise for time and resource savings within the pharmaceutical industry.