Automatic Program Research Articles

Case Studies of Robots and Automation as Health/Safety Interventions in Small Manufacturing Enterprises.

This paper reviews the experiences of 63 case studies of small businesses (< 250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (n = 17), computer numerical control (CNC) machining (n = 29), or other programmable automation systems (n = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were: CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: Snack Foods; Photographic Film, Paper, Plate, and Chemical; Machine Shops; Leather Good and Allied Products; Plastic Products; and Iron and Steel Forging. This review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors and improved process productivity in most cases.

Quality Evaluation Method of Automatic Software Repair Using Syntax Distance Metrics

In recent years, test-based automatic program repair has attracted widespread attention. However, the test suites in practice are not perfect ways to guarantee the correctness of patches generated by repair tools, and weak test suites lead to a large number of incorrect patches produced by the existing repair tool. To reduce the number of incorrect patches generated by repair tools, we propose a patch quality evaluation method based on syntax distance metrics, which measures the syntax distance of patches through four evaluation features—variable, expression, structure, and repair location. By fusing the distance values of the four features, the quality of a patch can be evaluated. Our method evaluates 368 patches from multiple famous repair tools, such as jKali, Nopol, SimFix, DynaMoth, and CapGen; 95% of the correct patches were ranked in the top one of the plausible patches for each defect, which indicates our method can find high-quality patches.

Efficient and accurate diagnosis of otomycosis using an ensemble deep-learning model.

Otomycosis accounts for over 15% of cases of external otitis worldwide. It is common in humid regions and Chinese cultures with ear-cleaning custom. Aspergillus and Candida are the major pathogens causing long-term infection. Early endoscopic and microbiological examinations, performed by otologists and microbiologists, respectively, are important for the appropriate medical treatment of otomycosis. The deep-learning model is a novel automatic diagnostic program that provides quick and accurate diagnoses using a large database of images acquired in clinical settings. The aim of the present study was to introduce a machine-learning model to accurately and quickly diagnose otomycosis caused by Aspergillus and Candida. We propose a computer-aided decision-making system based on a deep-learning model comprising two subsystems: Java web application and image classification. The web application subsystem provides a user-friendly webpage to collect consulted images and display the calculation results. The image classification subsystem mainly trained neural network models for end-to-end data inference. The end user uploads a few images obtained with the ear endoscope, and the system returns the classification results to the user in the form of category probability values. To accurately diagnose otomycosis, we used otoendoscopic images and fungal culture secretion. Fungal fluorescence, culture, and DNA sequencing were performed to confirm the pathogens Aspergillus or Candida spp. In addition, impacted cerumen, external otitis, and normal external auditory canal endoscopic images were retained for reference. We merged these four types of images into an otoendoscopic image gallery. To achieve better accuracy and generalization abilities after model-training, we selected 2,182 of approximately 4,000 ear endoscopic images as training samples and 475 as validation samples. After selecting the deep neural network models, we tested the ResNet, SENet, and EfficientNet neural network models with different numbers of layers. Considering the accuracy and operation speed, we finally chose the EfficientNetB6 model, and the probability values of the four categories of otomycosis, impacted cerumen, external otitis, and normal cases were outputted. After multiple model training iterations, the average accuracy of the overall validation sample reached 92.42%. The results suggest that the system could be used as a reference for general practitioners to obtain more accurate diagnoses of otomycosis.

An Automated Approach to Assess Relative Galectin-Glycan Affinity Following Glycan Microarray Analysis.

Numerous studies have highlighted the utility of glycan microarray analysis for the elucidation of protein-glycan interactions. However, most current glycan microarray studies analyze glycan binding protein (GBP)-glycan interactions at a single protein concentration. While this approach provides useful information related to a GBP’s overall binding capabilities, extrapolation of true glycan binding preferences using this method fails to account for printing variations or other factors that may confound relative binding. To overcome this limitation, we examined glycan array binding of three galectins over a range of concentrations to allow for a more complete assessment of binding preferences. This approach produced a richer data set than single concentration analysis and provided more accurate identification of true glycan binding preferences. However, while this approach can be highly informative, currently available data analysis approaches make it impractical to perform binding isotherms for each glycan present on currently available platforms following GBP evaluation. To overcome this limitation, we developed a method to directly optimize the efficiency of assessing association constants following multi-GBP concentration glycan array analysis. To this end, we developed programs that automatically analyze raw array data (kdMining) to generate output graphics (kaPlotting) following array analysis at multiple doses. These automatic programing methods reduced processing time from 32.8 h to 1.67 min. Taken together, these results demonstrate an effective approach to glycan array analysis that provides improved detail and efficiency when compared to previous methods.

Lower extremity joint compensatory effects during the first recovery step following slipping and stumbling perturbations in young and older subjects

BackgroundThe lower extremity may play a crucial role in compensating for gait perturbations. The study aimed to explore the mechanism of perturbation compensation by investigating the gait characteristics and lower extremity joint moment effects in young (YS) and older subjects (OS) during the first recovery gait following slipping (slipping_Rec1) and stumbling (stumbling_Rec1).MethodAn automatic perturbation-triggered program was developed using D-Flow software based on the Gait Real-time Analysis Interactive Lab to induce the two aforementioned perturbations. Marker trajectories and ground reaction forces were recorded from 15 healthy YS (age: 26.53 ± 3.04 years; body height: 1.73 ± 0.07 m; body mass: 66.81 ± 11.44 kg) and 15 healthy OS (age: 68.33 ± 3.29 years; body height: 1.76 ± 0.10 m; body mass: 81.13 ± 13.99 kg). The Human Body Model was used to compute the variables of interest. One-way analysis of variance and independent samples t-test statistical analyses were performed.ResultsIn slipping_Rec1 and stumbling_Rec1, the change in gait pattern was mainly reflected in a significant increase in step width, no alterations in step length and stance/swing ratio were revealed. Based on perturbed task specificity, lower extremity joint moments increased or decreased at specific phases of the gait cycle in both YS and OS in slipping_Rec1 and stumbling_Rec1 compared to normal gait. The two perturbed gaits reflected the respective compensatory requirements for the lower extremity joints, with both sagittal and frontal joint moments producing compensatory effects. The aging effect was not reflected in the gait pattern, but rather in the hip extension moment during the initial stance of slipping_Rec1.ConclusionsSlipping appears to be more demanding for gait recovery than stumbling. Gait perturbation compensatory mechanisms for OS should concentrate on ankle strategy in the frontal plane and counter-rotation strategy around the hip.

Development of an autogeneration program for building a clear height cloud map based on BIM

Because the clear height of a building involves many particularities of buildings, structures and equipment, the traditional design mode can only roughly estimate the clear height of a building and cannot fully reflect the distribution of the clear height of the whole building, which is not conducive to designers’ design and optimization of buildings. To solve this problem, the concept of a cloud map of the clear height of buildings was proposed for the first time. Based on Revit software, a BIM-based, automatic building clear height cloud map generation program, which realized the efficient analysis of BIM model clear height and can quickly obtain the building clear height cloud map, was developed, therefore enhancing the clear height analysis function of Revit. Compared with the traditional clear height area analysis color block diagram, the clear height cloud diagram of BIM was more accurate, which provides an effective technical means for designers to comprehensively evaluate the clear heights of buildings.

Method and automatic program for accurate thermodynamic data of reaction mechanisms for combustion modeling

Thermodynamic parameters are the main components of reaction mechanisms for combustion modeling. In this work, the high-precision and efficient methods are investigated to calculate the thermodynamic data of enthalpies of formation, entropies, and heat capacities. An automatic program of thermodynamic data off-line calculator (TDOC) is developed for given reaction mechanisms to efficiently get high-accuracy thermodynamic parameters. It is found the extrapolation of connectivity-based hierarchy (CBH) method can broaden the scope of application for larger molecules to achieve high-accuracy calculations for enthalpies of formation at CCSD(T)/CBS level with bond additivity correction (BAC). Moreover, the high-precision thermodynamic data must consider the contributions of the hindered-rotor corrections and conformational contributions. Finally, the simulations of ignition delay time and species concentration are performed by substituting the high-precision thermodynamic parameters. It reveals that the high-precision thermodynamic parameters can improve the performance of reaction mechanisms, in which the simulated ignition delay time and species concentration are closer to experimental data. We hope this work can shed new light on the construction of reaction mechanisms for combustion modeling.

Results from a cervical cancer screening program in Samsun, Turkey

BackgroundCervical cancer is a preventable disease. This study aimed to share the results of the national cervical cancer screening program performed in primary health care institutions in Samsun between 2015 and 2019.MethodsWomen aged 30–65 years who were screened for cervical cancer in screening centers of Samsun between January 01, 2015, and December 31, 2019, were included in this descriptive study. The data were obtained from the automation program of the “National Human Papilloma Virus (HPV) Laboratory Application” used by the Provincial Directorate of Health Cancer Unit through filtering the completion time of the tests, and all results were evaluated without sampling. Thus, data were presented using descriptive statistics.ResultsThe mean age of 89,302 women included in the cervical cancer screening program was 45.9 ± 9.0 years. Of the samples obtained from the participants, 1.0% were determined as insufficient material, 94.1% as HPV-negative, and 4.9% as HPV-positive. The most common HPV genotypes were 16, 51, 31, and 52. Of the 4337 HPV-positive women, 74.7% of the pap smear results were negative (including infection, 36.5%), and the most common premalignant lesions were atypical squamous cells of undetermined significance in 7.1% and low-grade squamous intraepithelial lesions in 6.9%. HPV 16/18 was also observed in 31.7% of HPV-positive women. Seven hundred ninety-five women were referred to a specialist physician for further examination and treatment within the scope of the screening algorithm.ConclusionDetecting HPV-positivity by reaching more women within the national cervical cancer screening program’s scope is vital in fighting against this disease. The effectiveness of cancer screening programs should be increased by ensuring community participation through awareness activities.

Natural Language-Based Automatic Programming for Industrial Robots

Natural Language-Based Automatic Programming for Industrial Robots

Automatic Multi-functional Integration Program (AMFIP) towards all-optical mechano-electrophysiology interrogation.

Automatic operations of multi-functional and time-lapse live-cell imaging are necessary for the biomedical science community to study active, multi-faceted, and long-term biological phenomena. To achieve automatic control, most existing solutions often require the purchase of extra software programs and hardware that rely on the manufacturers’ own specifications. However, these software programs are usually non-user-programmable and unaffordable for many laboratories. To address this unmet need, we have developed a novel open-source software program, titled Automatic Multi-functional Integration Program (AMFIP), as a new Java-based and hardware-independent system that provides proven advantages over existing alternatives to the scientific community. Without extra hardware, AMFIP enables the functional synchronization of the μManager software platform, the Nikon NIS-Elements platform, and other 3rd party software to achieve automatic operations of most commercially available microscopy systems, including but not limited to those from Nikon. AMFIP provides a user-friendly and programmable graphical user interface (GUI), opening the door to expanding the customizability for myriad hardware and software systems according to user-specific experimental requirements and environments. To validate the intended purposes of developing AMFIP, we applied it to elucidate the question whether single cells, prior to their full spreading, can sense and respond to a soft solid substrate, and if so, how does the interaction depend on the cell spreading time and the stiffness of the substrate. Using a CRISPR/Cas9-engineered human epithelial Beas2B (B2B) cell line that expresses mNeonGreen2-tagged mechanosensitive Yes-associated protein (YAP), we show that single B2B cells develop distinct substrate-stiffness-dependent YAP expressions within 10 hours at most on the substrate, suggesting that cells are able to sense, distinguish, and respond to mechanical cues prior to the establishment of full cell spreading. In summary, AMFIP provides a reliable, open-source, and cost-free solution that has the validated long-term utility to satisfy the need of automatic imaging operations in the scientific community.

Automatic Repair Method for Null Pointer Dereferences Guided by Program Dependency Graph

Automatic program repair (APR) is an effective technique for eliminating defects. The repair of null pointer dereferences, as the most common defects, requires accurate dependencies among statements to determine where to repair and how to repair. In order to precisely identify the data and control dependencies, the program dependency graph is adopted. Based on the symmetry among a large number of patches, we propose four repair mechanisms in this passage, namely the assignment mechanism, restraint mechanism, evading mechanism, and transfer mechanism, and employ the decision tree algorithm to match the best repair mechanism for defects. The four repair mechanisms locate the accurate repair position using the program dependency graph, and generate candidate patches by reassigning the null pointer with an appropriate value, making a judgment for the null value in advance, or throwing an exception. Our method was implemented in the repair tool DTSFix, which supports the automatic repair of null pointer dereference in Java programs. The experimental result on Defects4J shows that 73% of null pointer dereferences are successfully repaired by DTSFix, and that the generated candidate patches do not contain over-fitting patches.

Clinical acceptability of fully automated external beam radiotherapy for cervical cancer with three different beam delivery techniques.

PurposeTo fully automate CT‐based cervical cancer radiotherapy by automating contouring and planning for three different treatment techniques.MethodsWe automated three different radiotherapy planning techniques for locally advanced cervical cancer: 2D 4‐field‐box (4‐field‐box), 3D conformal radiotherapy (3D‐CRT), and volumetric modulated arc therapy (VMAT). These auto‐planning algorithms were combined with a previously developed auto‐contouring system. To improve the quality of the 4‐field‐box and 3D‐CRT plans, we used an in‐house, field‐in‐field (FIF) automation program. Thirty‐five plans were generated for each technique on CT scans from multiple institutions and evaluated by five experienced radiation oncologists from three different countries. Every plan was reviewed by two of the five radiation oncologists and scored using a 5‐point Likert scale.ResultsOverall, 87%, 99%, and 94% of the automatically generated plans were found to be clinically acceptable without modification for the 4‐field‐box, 3D‐CRT, and VMAT plans, respectively. Some customizations of the FIF configuration were necessary on the basis of radiation oncologist preference. Additionally, in some cases, it was necessary to renormalize the plan after it was generated to satisfy radiation oncologist preference.ConclusionApproximately, 90% of the automatically generated plans were clinically acceptable for all three planning techniques. This fully automated planning system has been implemented into the radiation planning assistant for further testing in resource‐constrained radiotherapy departments in low‐ and middle‐income countries.

Calculation of Gas-phase Standard Formation Enthalpy via Ring-Preserved Connectivity-Based Hierarchy and Automatic Bond Separation Reaction Platform

Bond separation reaction (BSR) is an effective scheme to derive reliable thermochemical properties by systematic error cancellation, while some challenges exist before its wide applications. The traditional BSR schemes are less feasible to cyclic molecules, and automatic BSR programs are not yet fully developed, unbeneficial to maintain the reliability and efficiency of BSR. Herein, we propose an improved scheme of BSR, the Ring-Preserved Connectivity-Based Hierarchy (RCBH) scheme, to enhance the predicted accuracy of gas-phase standard enthalpy of formation (EOF) by quantum chemical calculations. The accuracy and time–cost of RCBH scheme are tested at various DFT levels, involving 12 functionals and 6 basis sets, with samples covering 250 cyclic organic molecules. The superiority of RCBH in calculating EOF is verified, with M062X/6-31 + G(2df,p) recommended as the most cost-effective DFT level, which can approach the accuracy of G4 with only 4% CPU-time of G4. The EOFs calculated by M062X/6-31 + G(2df,p) with RCBH correction are highly consistent with the experimental measurements, with a MAE of 1.1 kcal/mol. We also develop an automated BSR software package, Automatic Bond Separation Reaction Platform (ABSRP), feasible for all categories of organic molecules. The RCBH scheme and ABSRP are expected to be used in calculating other thermochemical properties of extensive categories of neutral organic molecules, with high accuracy while low computational cost.

Measurement method of maize morphological parameters based on point cloud image conversion

The plant height (PH), stem thickness long axis (STLA), and stem thickness short axis (STSA) in maize morphological parameters can effectively reflect the growth, lodging resistance and yield information of maize plants. Terrestrial laser scanning (TLS) can achieve rapid measurement of crop phenotypic parameters. To address the problems of low automation and leaf interference in the existing measurement methods, TLS was used as the measurement sensor, and a morphological measurement method for PH, STLA and STSA of field maize based on point cloud image conversion was proposed. First, in the V3, V6, V9, and V12 stages, three-dimensional (3D) point cloud data of two maize varieties (Jingnongke 728 and Nongda 84) were obtained by TLS. Second, the point cloud processing software was used to match the collected maize point cloud data, obtain the registered multi-site cloud data, remove the background point cloud data, extract the maize row data, and carry out down-sampling. Programming was used to realize data format conversion and individual plant segmentation. Third, several methods, including plane segmentation, statistical filtering, pass filtering, maximum and minimum traversal, and Euclidean clustering were used to remove ground point clouds, judge whether there was maize plant, and extract area maize point clouds. A method of point cloud image conversion was proposed to realize the segmentation of maize stem and leaf. Finally, the height of the plant was measured by calculating the vertical distance from the highest point of the plant to its base. The point cloud of the stem at a specific location was identified, and the ellipse fitting method was used to measure the thickness of the long axis and the short axis of the stem. Compared with the measured value of artificial point cloud, the PH, STLA and STSA of maize in 4 growth stages were measured using automatic program. The root mean square error (RMSE) of the PH, STLA and STSA of Jingnongke 728 were 0.61 cm, 3.16 mm and 2.53 mm respectively, and the mean absolute percentage error (MAPE) were 0.52%, 7.90% and 9.70% respectively. The RMSE of Nongda 84 were 0.66 cm, 2.63 mm and 2.42 mm respectively, and the MAPE were 0.75%, 7.07% and 9.76% respectively. The results show that the point cloud image conversion method for measuring PH, STLA and STSA proposed in this article is suitable for maize of different growth periods and different maize varieties. It is highly consistent with the artificial point cloud measurement values and can replace manual measurement. It can provide breeders with a fast, automatic and accurate measurement program for the PH, STLA and STSA of maize.

Towards automatic configuration and programming of a manufacturing cell

Manufacturing industries are moving from mass production towards customized production, aiming for high-quality products with innovative technologies, low prices, and high reliability. A reconfigurable manufacturing system (RMS) is an attractive approach to facilitate the movement toward such flexible manufacturing systems. However, reconfiguration and programming of RMS are time-consuming and labor-intensive. Industry 4.0 technologies (such as robotics, digital twin technology, and IoT solutions) decrease human interaction in the preparation phase of a new production series. One challenge that industry 4.0 does not address is a flexible electrification of the system. The lack of electrical outlets limits the available space on the shop floor, and extensive cabling constrains the motion of humans and machines in the same area. This paper solves these challenges by proposing a highly flexible RMS system with advanced robotics, a digital twin programming interface, and a wireless power transfer (WPT) solution. Experimental results, through simulations and verification by laboratory experiments, show great potential in the reduction of human interaction and time to set up a new manufacturing line.

Efficacy of Basic Life Support and Automatic External Defibrillator Educational Program for High School

Background: Bystander-initiated cardiopulmonary resuscitation (CPR), the automatic external defibrillator (AED), and rapid activation of emergency medical service have major roles in the chain of survival of out-of-hospital cardiac arrest patients. To integrate the basic life support (BLS) knowledge into the high school curriculum, teachers are the key person. Objective: To examine the effectiveness of the BLS training program for high school teachers. Methods: In this prospective study of 146 participants, before and immediately after 2 hours lecture and 3 hours hands-on activity of BLS training program consisting of instruction on CPR, AED, and first aid for foreign body aspiration, written tests were done to assess knowledge while participants’ attitudes were evaluated by a questionnaire survey. Results: A total of 146 participants, BLS knowledge increased in all parts (early activation, chest compression, and defibrillation increased by 27.3%, 51.3%, and 82.1% with adjusted OR 13.81, 19.08, and 849.47, respectively; P &lt; .001), as well as participant’s confidence increased from 47.6% to 95.8% (adjusted OR, 31.69; P &lt; .001). Conclusions: BLS training in high school teachers increased both knowledge of chains of survival and confidence.

Improving the safety relevance of automatic emergency braking testing programs: An examination of common characteristics of police-reported rear-end crashes in the United States

Objective Forward collision warning and automatic emergency braking (AEB) systems help prevent rear-end crashes where a vehicle strikes the rear of another. However, the benefits may be limited if the systems are stymied by common crash circumstances or only target scenarios evaluated in vehicle testing programs. This study examined the prevalence of characteristics that may limit AEB system performance in police-reported rear-end crashes and the relevance of scenarios used to evaluate these systems. Methods Police-reported rear-end crashes (n = 6,731,215, Crash Report Sampling System) and fatal rear-end crashes (n = 4,285, Fatality Analysis Reporting System) with a fatality in the striking or struck vehicle during 2016–2019 were analyzed. Percentages of police-reported rear-end crashes, nonfatal-injury rear-end crashes, and fatal rear-end crashes were computed to identify common crash characteristics. Roadway speed limit was used as a proxy for striking vehicle speed. Results A straight-moving vehicle striking a stopped or decelerating vehicle on roads with a speed limit of 40 km/h (25 mph) or less only accounted for 3% of all rear-end crashes, 3% of nonfatal-injury rear-end crashes, and 1% of fatal rear-end crashes. In contrast, 36% of all rear-end crashes, 36% of nonfatal-injury rear-end crashes, and 11% of fatal rear-end crashes involved a straight-moving vehicle striking a stopped or decelerating vehicle on roads with a speed limit between 56 and 72 km/h (35 and 45 mph). A medium or heavy truck was the struck vehicle in 32% of fatal rear-end crashes, and a motorcycle was the struck vehicle in 11% of fatal rear-end crashes. At least one of the following characteristics that may degrade AEB system performance was present in 14% of the rear-end crashes studied: striking vehicle turning; a struck vehicle turning or changing lanes; a struck vehicle that is not a passenger vehicle; wintery weather; wet or icy roads; or a speed limit of 113 km/h (70 mph) or higher. Conclusion Circumstances shown to diminish AEB effectiveness accounted for 14% of rear-end crashes, and scenarios currently used to evaluate AEB systems accounted for 3%. Evaluating AEB systems at speeds up to 72 km/h (45 mph) and incorporating a motorcycle or medium/heavy truck target will make AEB evaluations more representative of police-reported rear-end crashes.

An Adaptive Combination Resolution Algorithm for Moving Object Vector Graphics Based on Automatic Programming Optimization Algorithm

A new moving target adaptive image segmentation algorithm is proposed. On the basis of setting the adaptive tracking wave gate to track the moving target, the adjustment coefficient is adaptively calculated according to the criterion of maximum interclass variance function, and then, the adaptive segmentation of the image is completed by setting the threshold segmentation method. Compared with algorithm, iteration method, and maximum entropy method, the proposed algorithm can not only adapt to a variety of complex backgrounds but also has high precision and high speed. Therefore, it is a practical and effective image segmentation method. As a kind of nonparametric density estimation algorithm, automatic programming optimization algorithm of moving target vector graphic combination and resolution has been widely used in video moving target tracking. The algorithm has fast calculation efficiency and is not sensitive to target deformation and rotation; in the case of a partial shade, it has certain robustness. However, the algorithm moves too fast under clear conditions without considering the direction and speed of the target information, so it is easy to lose tracking when tracking fast moving targets. To solve this problem, a new method based on motion vector analysis and automatic programming optimization of moving target vector graphics combination resolution tracking algorithm is proposed. Firstly, the probability and statistics analysis of motion vectors generated in the process of video coding is carried out to obtain the estimated value of target motion direction and speed. Then, the center position of the candidate region can be split by correcting the combination of moving object vector graphics optimized by automatic programming so that the candidate center position is closer to the actual target center position at the beginning of each search. Compared with the traditional automatic programming optimization algorithm, the new algorithm not only improves the tracking accuracy of the fast-moving target but also reduces the number of search iterations, thus improving the operation efficiency. The algorithm can be applied to the case that video coding and target tracking are calculated simultaneously in the intelligent video surveillance equipment, and the experimental results show that the algorithm is effective and feasible.

PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management

IntroductionAccuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories.ObjectivesTo design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management.MethodsWe developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles.ResultsPeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases.ConclusionPeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest.

Design and Implementation of Smart Tourism Service Platform from the Perspective of Artificial Intelligence

With the advancement of science and technology and the further improvement of people’s living standards, tourism has become a hot topic in today’s society. This paper is aimed at studying the development of a smart tourism service platform using artificial intelligence recognition technology and automatic program design. This paper proposes functions such as online ticket booking through the design of intelligent access control in scenic spots (combined with intelligent voice, face recognition, and other technologies), scenic miniprograms, and WeChat public accounts. Tourists can collect tickets automatically through the intelligent assistant designed by the intelligent service system. This allows tourists to consult and interact with intelligent machine assistants, reducing human-to-human contact during travel, thereby reducing the probability of epidemic infection (mainly spread by coughing or sneezing, close contact with sick people, touching contaminated surfaces, etc.). Finally, the smart tourism service platform is promoted, and an online questionnaire survey is conducted on 2,000 tourists who use the service platform to understand the actual use of the system. The results of the questionnaire survey showed that among the 2,000 tourists’ evaluations, 55.15% were satisfied with the system, 41.5% were very satisfied, 3.1% felt average, 0.25% felt dissatisfied, and 0% were very dissatisfied. At the same time, a large number of positive evaluation words were received in the feedback results of tourists, which shows that the smart service system designed in this paper is very popular with tourists. Meanwhile, a great deal of positive evaluation words were received in the feedback results of tourists (such as full of technology, special convenience, and special safety). This shows that the intelligent service system designed in this paper is very popular with tourists.