Receptor tyrosine kinases (RTKs) are key regulators of cellular signaling and are frequently involved in cancer development. As their activation depends on ATP binding to the kinase domain, precisely identifying ATP b...
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Receptor tyrosine kinases (RTKs) are key regulators of cellular signaling and are frequently involved in cancer development. As their activation depends on ATP binding to the kinase domain, precisely identifying ATP binding sites is critical for mechanistic studies and targeted therapy development. However, general ATP binding site prediction methods often fall short for RTKs due to their diverse structural features across different protein families. To address this challenge, we introduce RTK_RAG, a framework that integrates retrieval-augmented generation (RAG) and utilizes protein language models (PLMs) with a multiwindow convolutional neural network (MCNN) architecture to improve ATP binding site prediction for RTKs. When tested on an independent RTK data set, RTK_RAG outperforms general ATP binding site predictors on multiple evaluation metrics. By accounting for RTK-specific structural differences, our study provides a reliable tool for researching RTK function and facilitating the development of novel kinase inhibitors. Moreover, this approach demonstrates the potential of RAG-based frameworks for enhancing functional predictions in specialized protein families, offering a generalizable strategy for improving binding site identification in specific protein families.
In the context of achieving Good Corporate Governance (GCG) in hospitals, among others, it is carried out with control and supervision, including in the case of hospital facility maintenance installations. Besides tha...
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Cervical cancer is one of the deadliest diseases in women. One of the cervical cancer screening methods is pap smear method. However, using a pap smear method to detect cervical cancer takes a long time for a patholog...
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ISBN:
(数字)9781665460309
ISBN:
(纸本)9781665460316
Cervical cancer is one of the deadliest diseases in women. One of the cervical cancer screening methods is pap smear method. However, using a pap smear method to detect cervical cancer takes a long time for a pathologist to diagnose. Hence, a rapid development of medical computerization for early detection to get the results quickly is needed. This paper proposes synthetic data augmentation by using Deep Convolutional Generative Adversarial Network (DCGAN) to increase number of pap smear samples in dataset. Gray Level Co-occurrence Matrix (GLCM) is employed to extract features from dataset. Classification of 3 classes which are Adenocarcinoma, High-Grade Squamous Intraepithelial Lesion (HSIL), and Squamous Cell Carcinoma (SCC) is conducted using Extreme Learning Machine (ELM). The result shows that the addition of synthetic data improves the performance of ELM with the accuracy of 90%. This accuracy is better than the accuracy of ELM using only the original dataset which is 85%.
Shapley values from cooperative game theory are adapted for explaining machine learning predictions. For large feature sets used in machine learning, Shapley values are approximated. We present a protocol for two tech...
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Advances in technology have increased the use and complexity of software. The complexity of the software can increase the possibility of defects. Defective software can cause high losses. Fixing defective software req...
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Physical activity is a cornerstone of health for older adults. Recent evidence underscores that even regular light activity, such as routine walking, offers substantial health benefits. Traditional approaches to promo...
Physical activity is a cornerstone of health for older adults. Recent evidence underscores that even regular light activity, such as routine walking, offers substantial health benefits. Traditional approaches to promoting walking often overlook the importance of the local neighbourhood environment and the wide range of abilities and preferences of older adults. A personalised walking intervention – emphasizing personal preferences and local facilitators by employing Geographic information System (GIS)-based methods for communication and goal setting – might help to overcome problems of low long-term adherence to walking interventions. The MOBITEC-Routes trial aims to assess the effects of personalised, GIS-based walking promotion – versus general information on determinants of health – for mobility-limited and chronically ill older adults on walking (primary outcome) immediately after the 15-week intervention period (primary endpoint) and after another 8 months of follow-up (secondary endpoint). This prospective, two-arm, single centre randomised controlled trial targets sedentary, mobility-limited, chronically ill, and community-living older adults aged 65 + (target N = 130). Outcomes are assessed after 15 weeks of intervention and after an additional 8 months of follow-up. The experimental intervention offers personalised promotion of habitual walking, delivered by an exercise professional in face-to-face and telephone sessions. Opportunities to increase leisure as well as utilitarian walking are identified by using interactive digital maps, personalised walking routes are co-created by the exercise professional and the participant, and a personalised activity plan is developed. Behaviour change strategies are employed. The control group receives general information on determinants of health. Outcomes include walking (average steps per day; primary outcome), time spent lying, sitting, standing and stepping, physical function, life-space mobility, he
This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit cu...
This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..
Intrusion Detection System provides services related to surveillance of computer security, as one of the minimum components that must exist in a computer network architecture. Regarding the adoption of cloud technolog...
Intrusion Detection System provides services related to surveillance of computer security, as one of the minimum components that must exist in a computer network architecture. Regarding the adoption of cloud technology, many users have switched to using cloud computers to operate servers, applications, or the web in cloud computing. To meet the security needs of users, various open source and commercial tools are being developed. Although many developments have taken place in the IDS area, in cloud-based IDS many challenges such as security, interoperability, resource scheduling, virtualization still need to be improved. This paper reviews the paradigms and surveys about the Intrusion Detection System that runs on cloud computing in terms of concepts, technology, tools, and various challenges. A systematic literature review of selected papers, published from 2016 to 2020, was carried out to properly understand the Intrusion detection System paradigm in cloud computing and the security challenges faced in cloud computing. This review paper helps researchers who want to start their research careers in the cloud computing-based Intrusion Detection System
ERP stands for enterprise resource planning. It is an information system that is all rolled into one, is very flexible and adaptable, and optimizes business operations while also centralizing all of the company's ...
ERP stands for enterprise resource planning. It is an information system that is all rolled into one, is very flexible and adaptable, and optimizes business operations while also centralizing all of the company's data. This study aims to empirically investigate the elements that affect users' intention and usage of enterprise resource planning (ERP). This research incorporates self-efficacy into the unified theory of acceptance and use of technology (UTAUT2). A quantitative technique was taken, and as a result, 143 replies that might be used were effectively collected. After that, the information was put through a structural equation modelling partial least square (SEM-PLS) analysis. According to the findings of this research, self-efficacy appears to have a significant influence on all endogenous variables (EE, BI, and UB), as indicated by t-values of 3.951, 7.573, and 5.492, respectively. In addition, the analysis also indicated that PE (4.317), EE (2.397), and HM (3.084) are likewise statistically and substantively significant to BI. The result shows that the R2 for BI and UB indicate a moderate impact of 0.603 and 0.521, respectively. It is suggested that the model has valuable applications in academic and real-world contexts.
Strategy training is a multidisciplinary rehabilitation approach that teaches skills to reduce disability among those with cognitive impairments following a stroke. Strategy training has been shown in randomized, cont...
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