Applied Sciences最新文献

{"title":"Virtual Screening and Molecular Dynamics Simulation to Identify Inhibitors of the m6A-RNA Reader Protein YTHDC1","authors":"Memoona Aslam, Nidhi Singh, Xiaowen Wang, Wenjin Li","doi":"10.3390/app14188391","DOIUrl":"https://doi.org/10.3390/app14188391","url":null,"abstract":"YTHDC1 (YTH domain containing 1), a crucial reader protein of N6-methyladenosine (m6A) mRNA, plays a critical role in various cellular functions and is considered a promising target for therapeutic intervention in acute myeloid leukemia and other cancers. In this study, we identified orthosteric small-molecule ligands for YTHDC1. Using a molecular docking approach, we screened the eMolecules database and recognized 15 top-ranked ligands. Subsequently, molecular dynamics simulations and MM/PBSA analysis were used to assess the stability and binding free energy of these potential hit compounds in complex with YTHDC1. Notably, five compounds with IDs of ZINC82121447, ZINC02170552, ZINC65274016, ZINC10763862, and ZINC02412146 exhibited high binding affinities and favorable binding free energies. The results also showed that these compounds formed strong hydrogen bonds with residues SER378, ASN363, and ASN367 and interacted with the aromatic cage of the YTHDC1 reader protein through TRP377, TRP428, and hydrophobic residue LEU439. To assess their viability as lead compounds, we conducted absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies to reveal promising features for these identified small molecules, shedding light on their pharmacokinetic and safety profiles.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"YOLOv8-E: An Improved YOLOv8 Algorithm for Eggplant Disease Detection","authors":"Yuxi Huang, Hong Zhao, Jie Wang","doi":"10.3390/app14188403","DOIUrl":"https://doi.org/10.3390/app14188403","url":null,"abstract":"During the developmental stages, eggplants are susceptible to diseases, which can impact crop yields and farmers’ economic returns. Therefore, timely and effective detection of eggplant diseases is crucial. Deep learning-based object detection algorithms can automatically extract features from images of eggplants affected by diseases. However, eggplant disease images captured in complex farmland environments present challenges such as varying disease sizes, occlusion, overlap, and small target detection, making it difficult for existing deep-learning models to achieve satisfactory detection performance. To address this challenge, this study proposed an optimized eggplant disease detection algorithm, YOLOv8-E, based on You Only Look Once version 8 nano (YOLOv8n). Firstly, we integrate switchable atrous convolution (SAConv) into the C2f module to design the C2f_SAConv module, replacing some of the C2f modules in the backbone network of YOLOv8n, enabling our proposed algorithm to better extract eggplant disease features. Secondly, to facilitate the deployment of the detection model on mobile devices, we reconstruct the Neck network of YOLOv8n using the SlimNeck module, making the model lighter. Additionally, to tackle the issue of missing small targets, we embed the large separable kernel attention (LSKA) module within SlimNeck, enhancing the model’s attention to fine-grained information. Lastly, we combined intersection over union with auxiliary bounding box (Inner-IoU) and minimum point distance intersection over union (MPDIoU), introducing the Inner-MPDIoU loss to speed up convergence of the model and raise detection precision of overlapped and occluded targets. Ablation studies demonstrated that, compared to YOLOv8n, the mean average precision (mAP) and F1 score of YOLOv8-E reached 79.4% and 75.7%, respectively, which obtained a 5.5% increment and a 4.5% increase, while also reducing the model size and computational complexity. Furthermore, YOLOv8-E achieved higher detection performance than other mainstream algorithms. YOLOv8-E exhibits significant potential for practical application in eggplant disease detection.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Historical Comprehensive Multimodal Transportation Data for Testing the Commuting Time Paradox: Evidence from the Portland, OR Region","authors":"Huajie Yang, Jiali Lin, Jiahao Shi, Xiaobo Ma","doi":"10.3390/app14188369","DOIUrl":"https://doi.org/10.3390/app14188369","url":null,"abstract":"There have been numerous theoretical and empirical transportation studies contesting the stability of commuting time over time. The constant commuting time hypothesis posits that people adjust trip durations, shift across modes, and sort through locations, so that their average commuting time remains within a constant budget. There is a discrepancy between studies applying aggregate analysis and those using disaggregate analysis, and differences in data collection may have contributed to the varying conclusions reported in the literature. This study conducts both aggregate and disaggregate analyses with two travel surveys of the Portland region. We employ descriptive analysis and t-tests to compare the aggregate commuting times of two years and use regression models to explore factors affecting the disaggregate commuting time at the individual trip level to examine whether the stability of the commuting time remains after substantial changes in the transportation and land use systems. Our study indicates that the average commuting time, along with the average commuting distance, increased slightly, as the mode share shifted away from driving during the examined period. The growth in shares of non-driving modes, which are slower than driving, coupled with an increased travel distance, contributed to the small increase in the average commuting time. Our analysis also indicates that the average travel speed improved for transit riders as well as drivers, contradicting earlier research that claims that public transit investment has worsened the congestion in Portland.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Framework for Agricultural Intelligent Analysis Based on a Visual Language Large Model","authors":"Piaofang Yu, Bo Lin","doi":"10.3390/app14188350","DOIUrl":"https://doi.org/10.3390/app14188350","url":null,"abstract":"Smart agriculture has become an inevitable trend in the development of modern agriculture, especially promoted by the continuous progress of large language models like chat generative pre-trained transformer (ChatGPT) and general language model (ChatGLM). Although these large models perform well in general knowledge learning, they still have certain limitations and errors when facing agricultural professional knowledge about crop disease identification, growth stage judgment, and so on. Agricultural data involves images and texts and other modalities, which play an important role in agricultural production and management. In order to better learn the characteristics of different modal data in agriculture, realize cross-modal data fusion, and thus understand complex application scenarios, we propose a framework AgriVLM that uses a large amount of agricultural data to fine-tune the visual language model to analyze agricultural data. It can fuse multimodal data and provide more comprehensive agricultural decision support. Specifically, it utilizes Q-former as a bridge between an image encoder and a language model to achieve a cross-modal fusion of agricultural images and text data. Then, we apply a Low-Rank adaptive to fine-tune the language model to achieve an alignment between agricultural image features and a pre-trained language model. The experimental results prove that AgriVLM demonstrates great performance in crop disease recognition and growth stage recognition, with recognition accuracy exceeding 90%, demonstrating its capability to analyze different modalities of agricultural data.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time Document Collaboration—System Architecture and Design","authors":"Daniel Iovescu, Cătălin Tudose","doi":"10.3390/app14188356","DOIUrl":"https://doi.org/10.3390/app14188356","url":null,"abstract":"This article explores the world of dependable systems, specifically focusing on system design, software solutions, and architectural decisions that facilitate collaborative work on shared text documents across multiple users in near real time. It aims to dive into the intricacies of designing robust and effective document collaboration software focusing on understanding the requirements of such a system, the working principle of collaborative text editing, software architecture, technology stack selection, and tooling that can sustain such a system. To examine the pros and cons of the proposed system, the paper will detail how collaborative text editing software can benefit from such an architecture regarding availability, elasticity, and scaling. The intricate nature of this system renders this paper a valuable resource for prospective investigations within the domain of dependable systems and distributed systems. This research first examines the requirements of a real-time collaboration system and the necessary core features. Then, it analyzes the design, the application structure, and the system organization while also considering key architectural requirements as the necessity of scaling, the usage of microservices, cross-service communications, and client–server communication. For the technology stack of the implementation, this research considers the alternatives at each layer, from client to server. Once these decisions are made, it follows system development while examining possible improvements for the issues previously encountered. To validate the architecture, a testing strategy is developed, to examine the key capabilities of the system, such as resource consumption and throughput. The conclusions review the combination of modern and conventional application development principles needed to address the challenges of conflict-free document replication, decoupled and stateless event-driven architecture, idempotency, and data consistency. This paper not only showcases the design and implementation process but also sets a foundation for future research and innovation in dependable systems, collaborative technologies, sustainable solutions, and distributed system architecture.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142268263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Peri-Implant Tissue Stability: A Series of Five Case Reports on an Innovative Implant Design","authors":"Marco Aurélio Bianchini, Mario Escobar, Maria Elisa Galarraga-Vinueza, Thalles Yurgen Balduino, Sergio Alexandre Gehrke","doi":"10.3390/app14188354","DOIUrl":"https://doi.org/10.3390/app14188354","url":null,"abstract":"Background/Aim: The stability of peri-implant tissues is crucial for the long-term success of dental implant treatments. A new cervical implant design has been developed to address the challenges associated with peri-implant tissue stability, featuring a concave cervical portion to increase tissue volume in this area. The present study aimed to clinically evaluate the effectiveness of the new cervical implant design in maintaining peri-implant tissue stability. Materials and Methods: Five clinical cases involving completely edentulous patients were selected, in which 25 implants were installed. The marginal bone level around each implant was assessed at three different time points—T0: immediately after the prosthesis installation, T1: 6 months post installation, and T2: at the last control visit, up to 38 months later. Measurements were taken to analyze changes in marginal bone levels (MBLs) and the keratinized mucosa (KM) over time. Furthermore, the keratinized mucosa (KM) around the implants was evaluated. Results: The mean and standard deviation values of the marginal bone levels at each time point were as follows—T0: 0.59 ± 0.55 mm; T1: 1.41 ± 0.59 mm; T2: 1.76 ± 0.69 mm. Statistical analysis showed significant differences across the time points (ANOVA p < 0.0001). The overall mean KM values were 3.85 mm for T1 and T2, showing the stability of the peri-implant soft tissues at ≥1-year controls. Conclusion: Within the limitations of the present study, the results showed that the Collo implants presented measured MBL values increasing within the time range analyzed in each case but within the normal values cited in the literature for these types of rehabilitation treatments. However, the measured KM values presented, in all cases, an average above the values referenced in the literature as a minimum for maintaining the health of the peri-implant tissues.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Memory-Based Learning and Fusion Attention for Few-Shot Food Image Generation Method","authors":"Jinlin Ma, Yuetong Wan, Ziping Ma","doi":"10.3390/app14188347","DOIUrl":"https://doi.org/10.3390/app14188347","url":null,"abstract":"Generating food images aims to convert textual food ingredients into corresponding images for the visualization of color and shape adjustments, dietary guidance, and the creation of new dishes. It has a wide range of applications, including food recommendation, recipe development, and health management. However, existing food image generation models, predominantly based on GANs (Generative Adversarial Networks), face challenges in maintaining semantic consistency between image and text, as well as achieving visual realism in the generated images. These limitations are attributed to the constrained representational capacity of sparse ingredient embedding and the lack of diversity in GAN-based food image generation models. To alleviate this problem, this paper proposes a food image generation network, named MLA-Diff, in which ingredient and image features are learned and integrated as ingredient-image pairs to generate initial images, and then image details are refined by using an attention fusion module. The main contributions are as follows: (1) The enhanced CLIP (Contrastive Language-Image Pre-Training) module is constructed by transforming sparse ingredient embedding into compact embedding and capturing multi-scale image features, providing an effective solution to alleviate semantic consistency issues. (2) The Memory module is proposed by embedding a pre-trained diffusion model to generate initial images with diversity and reality. (3) The attention fusion module is proposed by integrating features from diverse modalities to enhance the comprehension between ingredient and image features. Extensive experiments on the Mini-food dataset demonstrate the superiority of the MLA-Diff in terms of semantic consistency and visual realism, generating high-quality food images.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study of Millimeter-Wave Fuze Echo Characteristics under Rainfall Conditions Using the Monte Carlo Method","authors":"Bing Yang, Zhe Guo, Kaiwei Wu, Zhonghua Huang","doi":"10.3390/app14188352","DOIUrl":"https://doi.org/10.3390/app14188352","url":null,"abstract":"Due to the similarity in wavelength between millimeter-wave (MMW) signals and raindrop diameters, rainfall induces significant attenuation and scattering effects that challenge the detection performance of MMW fuzes in rainy environments. To enhance the adaptability of frequency-modulated MMW fuzes in such conditions, the effects of rain on MMW signal attenuation and scattering are investigated. A mathematical model for the multipath echo signals of the fuze was developed. The Monte Carlo method was employed to simulate echo signals considering multiple scattering, and experimental validations were conducted. The results from simulations and experiments revealed that rainfall increases the bottom noise of the echo signal, with rain backscatter noise predominantly affecting the lower end of the echo signal spectrum. However, rain conditions below torrential levels did not significantly impact the detection of strong reflection targets at the high end of the spectrum. The modeling approach and findings presented offer theoretical support for designing MMW fuzes with improved environmental adaptability.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Engagement and Brand Recall in Software Developers: An Eye-Tracking Study on Advergames","authors":"Duygu Akcan, Murat Yilmaz, Ulaş Güleç, Hüseyin Emre Ilgın","doi":"10.3390/app14188360","DOIUrl":"https://doi.org/10.3390/app14188360","url":null,"abstract":"Advergames represent a novel product placement strategy that surpasses traditional advertising methods by fostering interaction between brands and their target audiences. This study investigates the unique engagement opportunities provided by video games, focusing mainly on the ‘flow experience’, an intensified state of immersion frequently encountered by players of computer games. Such immersive experiences have the potential to significantly influence a player’s perception, offering a new avenue for advertisements to impact and engage audiences effectively. The primary objective of this research was to examine the influence of advergames on players who are deeply immersed in the gaming experience, with a specific focus on the subsequent effects on brand recognition over time. The study involved 44 software developers, who were evenly divided into two groups for the experiment. Both groups were exposed to an identical gaming environment with the task of locating a designated product within the game. However, one group interacted with an enhanced version of the game, which included additional stimuli—such as dynamic music, an engaging narrative, time constraints, a competitive leaderboard, and immersive voice acting—to intensify the gaming experience. The experiment strategically placed various products within the game, and their detectability was assessed using eye-tracking technology. Following gameplay, participants completed questionnaires that measured their experience with flow state and brand recall. The data were analyzed using the Mann–Whitney U test and correlation analysis to facilitate comparisons. The findings indicated that the product associated with the primary task achieved the highest recall rate between both groups. Furthermore, eye-tracking technology identified the areas in the game that attracted the most attention, revealing a preference for mid- and high-level placements over lower-level ones.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reviewing the Phenomenon of Antimicrobial Resistance in Hospital and Municipal Wastewaters: The Crisis, the Challenges and Mitigation Methods","authors":"Nazim Hasan, Embar Prasanna Kannan, Othman Hakami, Abdullah Ali Alamri, Judy Gopal, Manikandan Muthu","doi":"10.3390/app14188358","DOIUrl":"https://doi.org/10.3390/app14188358","url":null,"abstract":"Antibiotic resistance is a major crisis that the modern world is confronting. This review highlights the abundance of different types of antibiotic resistance genes (ARGs) in two major reservoirs in the environment, namely hospital and municipal wastewater, which is an unforeseen threat to human lives across the globe. The review helps understand the current state of affairs and the whereabouts on the dissemination of ARGs in both these environments. The various traditional wastewater treatment methods, such as chlorination and UV treatment, and modern methods, such as electrochemical oxidation, are discussed, and the gaps in these technologies are highlighted. The need for the development of newer techniques for wastewater treatment with enhanced efficiency is urgently underscored. Nanomaterial applications for ARG removal were observed to be less explored. This has been discussed, and prospective nanomaterials and nanocomposites for these applications are proposed.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142249370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}