Computer-assisted Language Learning Research Articles

Bioinformatics analysis identifies GLUD1 as a prognostic indicator for clear cell renal cell carcinoma

BackgroundRenal cell carcinoma (RCC) is a common primary tumor of the kidney and is divided into three major subtypes, of which clear cell renal cell carcinoma (ccRCC) has the highest incidence. Glutamate dehydrogenase 1 (GLUD1) encodes glutamate dehydrogenase 1, which catalyzes the oxidative deamination of glutamate.MethodsWe analyzed TCGA data using R language software and used multiple online databases to explore the relationship of GLUD1 with signaling pathways and drug sensitivity as well as GLUD1 protein expression and methylation.ResultsThe results showed that GLUD1 mRNA expression was reduced in tumor tissues and correlated with the progression of ccRCC. Univariate and multivariate Cox analysis showed that GLUD1 could be used as a prognostic marker for ccRCC. GLUD1 expression in ccRCC was associated with immune cells infiltration and multiple classical signaling pathways. In addition, GLUD1 mRNA expression was related to drug sensitivity.ConclusionsThese findings provide new ideas for finding new prognostic molecular markers and therapeutic targets for ccRCC.

Mechanisms predictive of Tibetan Medicine Sophora moorcroftiana alkaloids for treatment of lung cancer based on the network pharmacology and molecular docking

BackgroundLeguminous Sophora moorcroftiana (SM) is a genuine medicinal material in Tibet. Many research results have reveal the Sophora moorcroftiana alkaloids (SMA), as the main active substance, have a wide range of effects, such as antibacterial, antitumor and antiparasitic effects. However, there are few reports on the inhibition of lung cancer (LC) and its inhibitory mechanism, and the pharmacological mechanism of SMA is still unclear, Therefore, exploring its mechanism of action is of great significance.MethodsThe SMA active components were obtained from the literature database. Whereas the corresponding targets were screened from the PubChem and PharmMapper database, UniProt database were conducted the correction and transformation of UniProt ID on the obtained targets. The GeneCards and OMIM databases identified targets associated with LC. Venny tools obtained the intersection targets of SMA and LC. R language and Cytoscape software constructed the visual of SMA - intersection targets – LC disease network. The intersection targets protein-protein interaction (PPI) network were built by the STRING database. The functions and pathways of the common targets of SMA and LC were enriched by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking And A549 cells vitro experiment were performed to further validate our finding.ResultsWe obtained six kinds of alkaloids in SM, 635 potential targets for these compounds, and 1,303 genes related to LC. SMA and LC intersection targets was 33, including ALB, CCND1, ESR1, NOTCH1 and AR. GO enrichment indicated that biological process of SMA was mainly involved in the positive regulation of transcription and nitric oxide biosynthetic process, and DNA-templated, etc. Biological functions were mainly involved in transcription factor binding and enzyme binding, etc. Cell components were mainly involved in protein complexes, extracellular exosome, cytoplasm and nuclear chromatin, etc., Which may be associated with its anti-LC effects. KEGG enrichment analysis showed that main pathways involved in the anti-LC effects of SMA, including pathway in cancer, non small-cell lung cancer, p53, PI3K-Akt and FOXO signaling pathways. Molecular docking analyses revealed that the six active compounds had a good binding activity with the main therapeutic targets 2W96, 2CCH and 1O96. Experiments in vitro proved that SMA inhibited the proliferation of LC A549 cells.ConclusionsResults of the present study, we have successfully revealed the SMA compounds had a multi-target and multi-channel regulatory mechanism in treatment LC, These findings provided a solid theoretical reference of SMA in the clinical treatment of LC.

The influence of the hydrometeorological factors on the CO2 fluxes from the oligotrophic bog surface.

The influence of the hydrometeorological factors on the CO2 fluxes from the oligotrophic bog surface.

Enhancing Structural Engineering Education: Integrating Artificial Intelligence for Continuous Improvement

The study aims to analyze the impact of artificial intelligence (AI) usage on structural learning through student-developed programming in open-source software languages: Python, Octave, and OpenSees. The research collaborates with 90 undergraduate students in the early courses of civil engineering at the Universidad Nacional de Chimborazo. The ADDIE methodology is employed in the initial phase for planning, development, and monitoring. A survey on students' perceptions regarding effectiveness, satisfaction, recommendation, and feedback is conducted, followed by academic performance evaluation using a grading rubric to verify the achievement of set objectives. An analysis of factors contributing to AI-focused learning is then performed. Initial results revealed outliers, some deviating from study parameters and others discarded for a comprehensive view of study behavior. Regarding the survey data analysis, efficiency and satisfaction exhibited the highest reliability. Subsequently, variables were correlated considering their normality, showing a relationship between effectiveness and satisfaction; however, a strong connection cannot be guaranteed for these or other variables. Therefore, ANOVA tests, indicating positive linear relationships, and hypothesis testing were employed, demonstrating that students achieved objectives with a moderately high degree of effectiveness and satisfaction. The use of technological options and consideration of innovative learning methods can positively enhance the learning experience, contingent on prior education. Exploring artificial intelligence may prove challenging without guided information search based on predefined criteria and constraints.

Analisis Tindak Tutur Performatif pada Teks Narasi dalam Buku “Teks Narasi dan Literasi Buku Fiksi-Nonfiksi (Cas dari Cerita dan Buku) Modul 5 Bahasa Indonesia Paket B Setara SMP Kelas IX”

This research is a pragmatic study that focuses on performative speech acts in the Narrative Text in the Book "Narrative Text and Literacy of Fiction-Nonfiction Books (Cas from Stories and Books) Module 5 Indonesian Language Package B Equivalent Junior High School Class IX". Performative speech is an action that has been completed by the speaker and that by expressing it means that the action is completed at that moment. In performative speech there are actions that lead to commissive, representative, conative and directive actions. The purpose of this study is to describe the performative speech acts in the Narrative Text in the Book "Narrative Text and Literacy of Fiction-Nonfiction Books (Cas from Stories and Books) Module 5 Indonesian Language Package B Equivalent Junior High School Class IX" so that it is expected to add references to pragmatics research, especially in speech act research. This research method is descriptive qualitative research, which is a research method that aims to make a systematic description. The research approach used a theoretical approach. The methodology used is descriptive qualitative, which is researching on natural object conditions where the researcher is the key instrument. Data collection techniques through listening, reading and recording techniques. The results of the discussion found 10 data in the form of performative speech acts in the book "Narrative Text and Literacy of Fiction-Nonfiction Books (Cas from Stories and Books) Module 5 Indonesian Language Package B Equivalent Junior High School Class IX". The benefit of this research is that it can be used as a development and development of Indonesian language, can be used as a reference for students to students through data examples obtained in this article and can be used as a treasure of pragmatics literature that is already available.

CALL - Language Skills

This study looks into how Libyan students see and use computer-assisted language learning (CALL) to improve their language abilities. The study involved fifty respondents from the seventh and eighth semesters of the English Department in Applied Sciences at the College of Education in the Traghen district under Fezzan University in Libya. The study set out to investigate what factors affect students' use of CALL, how they feel and perceive it in language instruction, what benefits they see from using CALL to learn a second language, and how CALL has helped English majors become more productive and receptive communicators. According to the study, students had a favorable perception of CALL, especially when it comes to how it improves their writing, speaking, listening, reading, and vocabulary. The findings imply that CALL is an effective instrument for improving language skills. Subsequent investigations may concentrate on examining the application of CALL in diverse academic environments and its enduring impacts on language acquisition.

Mobile-assisted means of developing ecologic awareness in contects of modern legislation

The introduction of computer-assisted language learning (CALL) has provided language teachers with excellent possibilities to advance their computer literacy and adopt a learner-centered method of instruction. Mobile-Assisted Language Learning (MALL) is a relatively young term, derived from CALL (Computer-Assisted Language Learning), which both refer to language learning assisted by technology, namely by a type of computer, whether it is a desktop computer or a mobile device (Chirobocea-Tudor, 2021). Language teachers can now play a key role in preparing and encouraging students in various fields such as linguistics, areas of jurisprudence as ecology law, public and private law, criminal law and others. Possibilities and challenges of using a variety of technology for specific language learning thanks to the growing popularity of learning tools. The ultimate goal of this study is to examine how law university students study foreign languages using mobile applications.

Meta-analysis of the correlation between pulmonary hypertension and echocardiographic parameters in patients with chronic kidney disease.

To investigate the correlation between pulmonary hypertension (PH) and echocardiographic parameters in patients with chronic kidney disease (CKD). PubMed, Embase, Web of Science, Cochrane, VIP, CNKI, and Wanfang databases were systematically searched for articles published from inception to 19 May 2023. Study quality was estimated using the Quality Assessment of Case-Control Studies tool. Forest plots were drawn using R language software. The "metacor" function in the "meta" package was utilized for meta-analysis of the r-values and their standard errors. Heterogeneity and sensitivity analyses were carried out, with the main outcomes as r-value, p-value, and I2 value. Eleven studies were included, with 1,809 CKD patients. The correlations between 12 echocardiographic parameters and PH were analyzed. Except for FS and LVEF which were negatively correlated with CKD-PH, the other 10 parameters were positively correlated with CKD-PH. Among them, LA was highly correlated with CKD-PH (0.70 < r < 0.89); LVDD, RA, RV, LVMI, and LVDS were moderately correlated with CKD-PH (0.40 < r < 0.69); while PA, IVS, LVPW, SV, FS, and LVEF were lowly correlated with CKD-PH (0.20 < r < 0.39). The synthesized estimates were stable against heterogeneity. CKD-PH patients may have large cardiac chambers, thickened septal tissue on both sides of the chambers, reduced pulmonary artery flow rates, and decreased left ventricular function.

Implementation of data parsing technology using neural network and web driver

As a rule, data parsing is used to quickly obtain information from various web resources for further study and use. For parsing, you can use both specialized online services and desktop applications. Unfortunately, existing parsing technologies have some limitations. For example, it is often difficult to parse dynamic web pages and classify information obtained through parsing. New approaches are needed in implementing data collection and analysis - using language models and software (web driver) that simulate human actions when working with websites. The web driver assists in accessing data from dynamically updated sites, while artificial intelligence technologies help correctly recognize and classify data. This technology can be used to create parsers for real estate agencies, employment services, university admission committees, advertising campaigns, and financial organizations.

Development of a Nomogram Model to Predict the Risk of Stricture Recurrence after Urethroplasty: A Retrospective Study.

A retrospective study was performed to analyse the influencing factors of stricture recurrence after urethroplasty and to establish a predictive nomogram model. The clinical data of patients who underwent urethroplasty in our hospital from January 2021 to June 2023 were retrospectively analysed. Depending on whether stenosis occurs six months after surgery, the patients were divided into recurrence and nonrecurrence groups. Logistic regression analysis was performed on the indicators with statistically significant differences between the two groups in single factor analysis to analyse the influencing factors of postoperative recurrence risk of stricture. X64.4.1.3 version R language and external source packages were used to build the nomogram model. The nomogram was internally validated through 10-fold cross-validation, and C-index was calculated. The area under the curve (AUC) of the receiver operating characteristic curve was employed to evaluate the results of the internal validation. Amongst 105 patients who underwent urethroplasty in our hospital, 15 patients with recurrence were included in the recurrence group, and 90 patients without recurrence were included in the nonrecurrence group. The length of stricture segment, history of urethroplasty and smoking history within 3 months before surgery were risk factors for stricture recurrence, with odds ratio (OR) values of 1.874 (95% CI: 1.103-5.725), 1.670 (95% CI: 1.105-2.904) and 1.740 (95% CI: 1.456-5.785), respectively. The constructed nomogram obtained an average AUC of 0.842 and an average C-index of 0.794, calculated after 200 times of 10-fold cross-validation. From the data of this study, it can be deduced that the influencing factors of stricture recurrence after urethroplasty include the length of stricture segment, history of urethroplasty and smoking history of 3 months before surgery. Using the above factors as a basis to construct a predictive nomogram model is helpful to screen high-risk patients with recurrence of stricture after urethroplasty.

The ALICE Grid Workflow for LHC Run 3

The ALICE Grid Workflow for LHC Run 3

Angiopoietin-Like Protein 2 Serves as an Independent Prognostic Biomarker and Correlates with Immune Infiltration in Osteosarcoma

Osteosarcoma mostly occurs in adolescents, with high disability and mortality rates and poor prognosis. Angiopoietin-like protein 2 (ANGPTL2) is a secreted glycoprotein protein, which plays important roles in cellular processes and various diseases. Microarray gene expression data GSE16088 and GSE36001 were downloaded from Gene Expression Omnibus (GEO, &lt;ext-link ext-link-type="uri" xlink:href="http://www.ncbi.nlm.nih.gov/geo"&gt;http://www.ncbi.nlm.nih.gov/geo&lt;/ext-link&gt;). The Complex Heatmap package was used to construct heatmaps, the gglot2 R language package to plot volcanoes and differential expression data, and the “VennDiagram” R language package to plot Wayne plots. Western booting and qRT-PCR was used to detect ANGPTL2 expression in osteosarcoma tissues. proteins. In addition, the GeneMANIA database (&lt;ext-link ext-link-type="uri" xlink:href="http://www.genemania.org"&gt;http://www.genemania.org&lt;/ext-link&gt;) was cited to predict the ANGPTL2 interaction network. We used the single-sample gene-set enrichment analysis (ss GSEA) algorithm to quantify the immune infiltration of osteosarcoma. In the GSE16088 database there were 5005 that met the selected threshold of |log2(FC)| &gt; 1 and P &lt;0.05, of which 2719 were highly expressed and 2286 were lowly expressed. WB and qRT-PCR results showed that ANGPTL2 was significantly up-regulated in osteosarcoma tissues. ssGSEA showed that high ANGPTL2 expression in osteosarcoma patients had a worse prognosis. ssGSEA showed that high ANGPTL2 expression was correlated with Mast cells and Th1 cells. Collectively, ANGPTL2 can be an independent prognostic biomarker and correlated with immune infiltration in osteosarcoma.

The Effects of Computer-assisted Language Learning (CALL) and Different Interaction Patterns on Vocabulary Development of EFL Learners

Background: Research on the integration of Computer-assisted language learning (CALL) in EFL contexts has witnessed a significant advance due to the modern changes in language education and technology over the last decades. However, the effects of CALL on vocabulary development through different interaction patterns have not been investigated by researchers.&#x0D; Purpose: Attempts have been made to assess the effects of CALL and Memrise software on the vocabulary development of intermediate EFL learners through the three interaction patterns: 1) pair-work interaction, 2) small-group-work interaction, and 3) individual content.&#x0D; Method: A total of 100 male and female Iranian EFL learners were selected through convenience sampling and assigned into three experimental and one control groups, each consisting of 25 learners. The Oxford Quick Placement Test was taken to assure the homogeneity of the participants. Then, a multiple-choice vocabulary test was taken as a pretest. The three experimental groups learned vocabulary through Memrise desktop software with three different interaction patterns, while the control group learned the same through the conventional pattern. A reshuffled version of the pretest constitutes the subsequent posttest.&#x0D; Result: The results of the comparison between all pretests and posttests indicated that there was a significant difference between the vocabulary scores of the pretest and the posttest of the experimental groups, indicating the efficiency of these treatments. It was revealed that the pair work was slightly more effective than small-group work and that these two types of intervention were more effective than individual-content interaction, where the latter was more effective than conventional instruction.&#x0D; Conclusion: According to the findings, students are advised to take advantage of CALL-based facilities and participate in interactive activities.

The effect of evaluation and feedback in 360-degree video-based VR environments on language learning outcomes

Recently, 360-degree video technology (360VT) received considerable attention in the field of computer-assisted language learning as it creates authentic and immersive virtual reality environments to assist the language learning process. However, not many studies focused on applications of 360VT to assist the evaluation of learner’ performance and providing them with relevant feedback. Therefore, the present study was set to shed light on this aspect. We carried out an experiment to explore the effects of evaluation and feedback in two different video learning environments, i.e. a traditional video technology-based (TVT) and 360VT-based, on learning outcomes. In the context of the present study, evaluation referred to evaluating the content of videos created by students, and feedback referred to providing students with relevant feedback for further improvement of their videos. English as a foreign language (EFL) course was administered for 52 university students. The participants were equally divided into TVT and 360VT groups. They attended EFL classes, and after classes, they created videos using either a traditional video camera (TVT group) or a 360-degree video camera (360VT group) on four learning topics. The evaluators watched videos, evaluated them, and then provided feedback to students. Students then revised their works based on received feedback. The results showed an insignificant difference between the two groups in their pre-test scores when measuring prior knowledge. However, when measuring knowledge after the study, 360VT group students outperformed their counterparts in the post-test. According to the results, students in the 360VT group received significantly more feedback, and it was more detailed compared to that of their counterparts. In addition, the evaluators scored affordances of 360VT higher than those of TVT. The results showed many advantages of 360VT such as it was useful and easy to use during the evaluation process, 360VT created immersive environments so that the evaluators had a realistic experience and a high level of vividness when watching and evaluating videos. The results suggest that evaluation and feedback in 360VT environments had better effects on learning outcomes, and the evaluators positively perceived their experiences in 360VT settings. Therefore, it is suggested that educators and researchers consider implementing 360VT in situations when language learners are tasked with creating their own content, which can subsequently be evaluated with relevant feedback provided.

Expanding the functionality of IoT devices in conditions of emergency situations

The article is devoted to the expansion of functional devices of the Internet of Things (IoT) in order to increase the safety of the population in emergency situations, in particular in the context of natural disasters and military threats. After analyzing the latest research and publications, a conclusion was made about the relevance of the development of IoT technologies in the context of modern challenges for the safety of citizens. Special emphasis is placed on the use of innovative approaches to solving public safety problems, particularly for persons with disabilities, such as the hearing impaired or the elderly. The article describes the implementation of software in the Python programming language to visually display the status of a missile threat or artillery fire using Yeelight smart lamps, which use colored light to convey information about the presence or absence of danger messages. The proposed solutions include synchronous operation of devices in real time, connection to reliable sources of messages and provision of stable communication between devices and the server. The project demonstrated an innovative approach to solving security problems in crisis situations, in particular martial law, promoting a quick and accurate response to valuable threats and protecting the population.

EXPLORING THE USE OF PYTHON-BASED LANGUAGE LEARNING SOFTWARE TO IMPROVE THE VOCABULARY OF ENGINEERING STUDENTS

The paper examines the feasibility of using Python-based language learning software to improve the vocabulary of engineering students as a secondary language. The purpose of the paper is to investigate the following key parameters such as time frame, repeatability, ease of use of the software, and limited time for learning. Two student groups participated in this study – the first-year and the second-year students of engineering faculty. They showed a fluctuating trend in both groups, with the accuracy rate remaining the same for the first six weeks and then increasing as the students learned new words. Software like this could be used as a soft skill-based learning method to improve the language absorption of engineering-based students for non-English speaking student groups. The results indicated that both student groups increased the average vocabulary and had only 20 percent wrong answers by the end of the study programs compared to the 80 percent and 50 percent mistakes at the beginning of the study.

Remote methods of research assessment of the impact of agricultural economic processes on the environmental destruction of the territory

The research is about solving the problem of assessing the impact of agricultural processes on the environmental safety of territories. The research was carried out on the selection, uploading and processing of data from the aerial survey of the area. High-quality multispectral images of the study areas were selected in accordance with the time-related thematic tasks of aerospace research of agricultural plots. With the help of Google Earth Engine platform, JavaScript programming language, ENVI and ArcMap software complexes, segmentation of the image of space images was carried out on these images. Each of them has its own normalized color scale, and highlights certain objects with different colors. To improve the visualization of differences in images, the classification of index images using the Isodata method was studied.An Agrocontrol module for automated deciphering of agricultural was developed. The module allows to select agricultural land with further vectorization and the possibility of creating a geodatabase automatically. Based on results, preliminary cartographic models of the studied territories were created with the indication of land plots that are dangerous for the ecological state of the region and require more careful consideration.At the stage of practical research, an analysis of the received data, based on the agricultural holding "Mriya", was carried out on the scheme of crop rotation, hybrids of grain crops grown on the territory of the plots, the types and amount of fertilizers used, as well as the volume of the harvest for the last 5 years. This made it possible to prove the correlation between the chemical composition of the used fertilizers and the corresponding exceedances of the MPC norms of the soil samples chemical composition.

Analysis of Shared Mechanisms and Chinese Herbal Medicines Between Osteoporosis and Type 2 Diabetes

Background: Osteoporosis (OP) and type 2 diabetes (T2D) are commonly encountered metabolic disorders in clinical practice, but the comorbidity mechanism has not been clarified. This study explored the underlying mechanisms for utilizing bioinformatics methods. Furthermore, it predicted traditional Chinese medicines (TCMs) with preventive and therapeutic effects. Materials and Methods: GSE35958 and GSE43950 were retrieved and downloaded from the GEO database, and differential expression analysis was performed to identify differentially expressed genes (DEGs) with similar expression patterns in OP and T2D. Then, the common DEGs were uploaded to the STRING database to construct a protein interaction network. Enrichment analysis of the screened genes was conducted using R language packages. Relevant TCMs were searched and screened based on gene targets using the Encyclopedia of traditional Chinese medicine (ETCM) database. Molecular docking of active ingredients of the TCMs and related gene targets was performed using AutoDock Vina software. Results: By analyzing the gene expression microarrays, GSE35958 and GSE43950, 34 genes with the same expression pattern shared by OP and T2D were identified. Among these genes, 32 were upregulated and two were downregulated. Protein interaction network analysis revealed that tumor necrosis factor, vascular endothelial growth factor A, and CD44 might play key roles in the co-pathogenesis of T2D and OP. TCMs, including Wolfberry (枸杞), Ginseng (人参), and Yam (山药), were screened based on key genes. Molecular docking results demonstrated binding activity between all active ingredients and the related gene targets. Conclusion: This study explored the potential molecular co-pathogenesis of OP and T2D through bioinformatic analysis and preliminarily predicted traditional herbal medicines that may have preventive and therapeutic effects.

The multi-layer secure communication system based on 2D-OCDMA coding

Abstract This paper presents a novel multi-layer secure communication system that bases 2D-OCDMA technology to enhance the security and number of users of the system. The system innovatively combines RSA encryption, polarization multiplexing, and address coding techniques to protect and transmit the data. At the transmitting end, the data is encrypted by algorithm and then encoded by address code. The encoded optical data is split into two orthogonal polarization states and sent over the same channel. At the receiving end, only the optical signals in the matching polarization state can be retrieved by the polarizer with the right angle. The retrieved data is then decoded by the address code and decrypted by the algorithm to recover the original data. This system achieves multi-layer security and capacity enhancement by processing the information at different layers. The feasibility of the system is demonstrated by joint experimental simulation using Java programming language and Optisystem simulation software. In this paper, low BER transmission of 4 code words for 8 users 50 km 1Gbit/s is realized using optical orthogonal codes (OOC) with BER around 10−30. It realizes the enhancement of 4-user to 8-user without affecting the transmission effect.

Summary Report APE 2023, 10--12 January, Berlin, Germany Berlin Re-Visited: Building Technological Support for Scholarship and Scientific Publishing

This paper summarizes the 18th Academic Publishing in Europe (APE) Conference: Berlin Re-Visited: Building Technological Support for Scholarship and Scientific Publishing, held as a hybrid event 10 and 11 January 2023, and organized by the Berlin Institute of Scholarly Publishing (BISP), a not-for-profit organization dedicated to bringing publishers, researchers, funders, and policymakers together. This year’s conference theme “Out with the old, in with the new!” was discussed and presented in keynote speeches, the APE lecture, and several panel discussions. Current challenges within scholarly publishing, e.g., with research integrity, trust, and research assessment, have much to do with the old ways of doing things. To move science forward, new technologies and innovations, like the decentralized web, FAIR digital objects, and blockchain technology are needed to shape new paradigms. In many sessions it was stressed that not just new technologies are needed to move science forward, but human collaboration and partnerships as well. The changing role of the journal and the importance to recognize more diverse research outputs, beyond the journal article, was a topic of importance. Not only research assessment reforms and improved collaboration amongst different stakeholder groups are needed to address this, new publishing systems, better metadata, and open infrastructures as well. A session presenting different start-ups showcased how Artificial Intelligence, Natural Language Processing and software technology can be used to tackle problems in e.g., finding relevant funders and peer reviewers, and detecting image plagiarism. It was also discussed what publishers can do to help achieve the Sustainable Development Goals. Collaboration, data transparency and sharing best practices amongst researchers, funders, and policy makers are key. Another important topic during this year’s APE was how publishers can support Early Career Researchers: establishing new workflows and infrastructures that enable publication of a wider range of research outputs, and broader recognition of these outputs, will incentivize ECRs. This year’s APE was concluded with the APE Award Ceremony. The winner - Vsevolod Solovyov from Prophy - has used AI to enhance the current peer review system and made a very important contribution to improving the scholarly communication system.