Functional Information Research Articles

UniProt: the Universal Protein Knowledgebase in 2025

Abstract The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication, we describe ongoing changes to our production pipeline to limit the sequences available in UniProtKB to high-quality, non-redundant reference proteomes. We continue to manually curate the scientific literature to add the latest functional data and use machine learning techniques. We also encourage community curation to ensure key publications are not missed. We provide an update on the automatic annotation methods used by UniProtKB to predict information for unreviewed entries describing unstudied proteins. Finally, updates to the UniProt website are described, including a new tab linking protein to genomic information. In recognition of its value to the scientific community, the UniProt database has been awarded Global Core Biodata Resource status.

MosAIC: An annotated collection of mosquito-associated bacteria with high-quality genome assemblies.

Mosquitoes transmit medically important human pathogens, including viruses like dengue virus and parasites such as Plasmodium spp., the causative agent of malaria. Mosquito microbiomes are critically important for the ability of mosquitoes to transmit disease-causing agents. However, while large collections of bacterial isolates and genomic data exist for vertebrate microbiomes, the vast majority of work in mosquitoes to date is based on 16S rRNA gene amplicon data that provides limited taxonomic resolution and no functional information. To address this gap and facilitate future studies using experimental microbiome manipulations, we generated a bacterial Mosquito-Associated Isolate Collection (MosAIC) consisting of 392 bacterial isolates with extensive metadata and high-quality draft genome assemblies that are publicly available, both isolates and sequence data, for use by the scientific community. MosAIC encompasses 142 species spanning 29 bacterial families, with members of the Enterobacteriaceae comprising 40% of the collection. Phylogenomic analysis of 3 genera, Enterobacter, Serratia, and Elizabethkingia, reveal lineages of mosquito-associated bacteria isolated from different mosquito species in multiple laboratories. Investigation into species' pangenomes further reveals clusters of genes specific to these lineages, which are of interest for future work to test for functions connected to mosquito host association. Altogether, we describe the generation of a physical collection of mosquito-associated bacterial isolates, their genomic data, and analyses of selected groups in context of genome data from closely related isolates, providing a unique, highly valuable resource for research on bacterial colonisation and adaptation within mosquito hosts. Future efforts will expand the collection to include broader geographic and host species representation, especially from individuals collected from field populations, as well as other mosquito-associated microbes, including fungi, archaea, and protozoa.

Pancreatic Neuroendocrine Neoplasms: Classification and Novel Role of Endoscopic Ultrasound in Diagnosis and Treatment Personalization.

The incidence and prevalence of pancreatic neuroendocrine neoplasms are steadily increasing. These tumors are highly heterogeneous, with treatment options ranging from observation to surgery, and various medical therapies. The choice of treatment is influenced by factors such as tumor stage, grade (proliferative activity), and the presence of hormone-related syndromes. Endoscopic ultrasound (EUS) is becoming increasingly valuable for assessing pancreatic neuroendocrine neoplasms, offering detailed morphological, vascular, and functional information through techniques such as contrast enhancement and elastography. It also allows biopsies that are useful for both histopathological and molecular analyses. These tumors are highly heterogeneous, with treatment options ranging from observation to various medical therapies and surgery. Recent data suggest that small, non-functioning PanNENs with low proliferation rates may be safely monitored, whereas more aggressive or functioning tumors typically require surgery. EUS-guided ablation is a promising alternative for patients with functional pancreatic neuroendocrine neoplasms who are unsuitable for surgery, although randomized trials are needed. In non-resectable pancreatic neuroendocrine neoplasms, treatment options include somatostatin analogs, targeted therapies (e.g., everolimus, sunitinib), chemotherapy, and radioligand therapy. This review discusses key factors in planning personalized treatment strategies for pancreatic neuroendocrine neoplasms.

Diagnostic Validity of Clinical Observations for Detecting Physiologic Swallowing Impairment.

A clinical swallow evaluation (CSE) is a noninvasive and indirect assessment of the anatomical and physiological integrity of the swallowing mechanism in a natural setting. A CSE goes beyond a screening, a dichotomized indicator of dysphagia risk, by comprehensively examining the patient's swallowing through gaining sensory and motor information of oral and pharyngeal function. Information obtained from CSEs in combination with medical, social, and environmental patient related factors allow clinicians to make critical decisions about patients' health and quality of life. It is essential that we have assessment tools with rigorous methodological quality to optimize the accuracy of our clinical judgement. The purpose of this study is to investigate the diagnostic validity of clinical observations obtained through the Mann Assessment of Swallowing Ability (MASA) to better inform clinicians regarding the confidence that the items are testing what they are intended to test and reflect indication of true physiologic swallowing impairment and airway invasion. Area Under the ROC Curve (AUC) analyses revealed that the MASA's diagnostic validity showed acceptable accuracy levels for detecting oral impairment and aspiration, and poor accuracy for detecting pharyngeal impairment and penetration. In the cross-validation analysis, the AUC accuracy level for aspiration changed from acceptable to poor, but remained the same for oral impairment, pharyngeal impairment and penetration. In our sample, acceptable levels for detecting aspiration but poor levels for detecting pharyngeal impairment indicate that the MASA does an adequate job of identifying risk but not explaining the nature of impairment. These results support the need for videofluoroscopic imaging to identify the nature and severity of swallowing impairment, guide intervention and provide recommendations for safe and efficient oral intake.

Abstract 4142793: Development of an Angiography-Based Multimodal AI Model for Predicting the risk of In-Stent Restenosis

Background: Despite advances in Second-generation drug-eluting stents (DES), 5-10% of patients still experience in-stent restenosis (ISR) after percutaneous coronary intervention (PCI), which generates significant financial burden and elevates the risk of acute coronary syndrome (ACS) and rehospitalization. Thus, early identification of patients at high risk for ISR is crucial for guiding clinical stratification and early intervention. Aims: To develop and validate a multimodal artificial intelligence (AI) model based on coronary angiography images for predicting ISR risk in patients post-DES implantation. Methods: To establish an accurate predictive model, our approach begins with the pre-training on 100,000 angiographic images to enhance the model’s capability in recognizing image features. Subsequently, we employ the DenseNet architecture as the primary deep learning model, incorporating angiographic images from 2,000 cases of DES-treated de novo lesions—1,000 from patients who did not experience ISR within two years and 1,000 from those who did. A multivariate logistic regression analysis, including radiomic features, clinical baselines, and functional information, constructs the predictive model. Additionally, a separate prospective cohort of 300 cases was assembled for validation to simulate real-world application and to verify the model's reliability and accuracy. Results: Our study successfully developed an AI prediction model for ISR, utilizing a large cohort of coronary angiography images, which effectively predicts ISR with high accuracy. Leveraging the DenseNet architecture and finely tuned machine learning algorithms, the model achieved a sensitivity and specificity of 90% in the validation cohort. The ROC curve from the test phase demonstrated an AUC above 0.90, underscoring the model’s exceptional diagnostic capabilities. Furthermore, the implementation of this model in a prospective cohort confirmed its reliability and practical utility in real-world clinical settings. Conclusions: This study introduces the first multimodal AI model using angiographic imaging to predict ISR. By demonstrating high diagnostic accuracy and reliability in real-world settings, this model serves as an essential tool for early ISR detection and intervention, ultimately helping to reduce the incidence of major adverse cardiac events (MACEs) and mortality.

THE ROLE OF INFORMATION FLOWS IN THE OPERATIONAL MANAGEMENT OF TRANSPORT

The management of transport flows is based on transmitting, receiving and processing the information related to them by applying the principles of the system approach. In a theoretical-applied aspect, it manifests itself as an economic activity for the development and implementation of methods for collecting, storing, processing and distributing information for specific functions and operations in transport infrastructure systems.

CAZac: an activity descriptor for carbohydrate-active enzymes.

The Carbohydrate-Active enZYme database (CAZy; www.cazy.org) has been providing the reference classification of carbohydrate-active enzymes (CAZymes) for >30 years. Based on literature survey, the sequence-based families of CAZymes are enriched with functional data by using the International Union of Biochemistry and Molecular Biology Enzyme Commission (EC) number system. However, this system was not developed to search or compare functional information. To better harness functional information, we have developed CAZac (CAZyme activity descriptor), a multicriterion system that describes CAZymes' mechanisms, glycosidic bond orientations, subsites and inter-residue connectivities. This new system, implemented for glycoside hydrolases, glycoside phosphorylases, transglycosidases, polysaccharide lyases and lytic polysaccharide monooxygenases allows complex searches in the CAZy database to uncover the evolution of substrate specificity and mechanisms of CAZymes across families.

The Hippo Signaling Pathway, Reactive Oxygen Species Production, and Oxidative Stress: A Two-Way Traffic Regulation

The Hippo signaling pathway is recognized for its significant role in cell differentiation, proliferation, survival, and tissue regeneration. Recently, the Hippo signaling pathway was also found to be associated with oxidative stress and reactive oxygen species (ROS) regulation, which are important in the regulation of cell survival. Studies indicate a correlation between components of the Hippo signaling pathway, including MST1, YAP, and TAZ, and the generation of ROS. On the other hand, ROS and oxidative stress can activate key components of the Hippo signaling pathway. For example, ROS production activates MST1, which subsequently phosphorylates FOXO3, leading to apoptotic cell death. ROS was also found to regulate YAP, in addition to MST1/2. Oxidative stress and ROS formation can impair lipids, proteins, and DNA, leading to many disorders, including aging, neurodegeneration, atherosclerosis, and diabetes. Consequently, understanding the interplay between the Hippo signaling pathway, ROS, and oxidative stress is crucial for developing future disease management strategies. This paper aimed to review the association between the Hippo signaling pathway, regulation of ROS production, and oxidative stress to provide beneficial information in understanding cell function and pathological processes.

Exploring lncRNA expression in follicular fluid exosomes of patients with obesity and polycystic ovary syndrome based on high-throughput sequencing technology.

Infertility is a reproductive health problem that attracts worldwide attention. Polycystic ovary syndrome (PCOS) is a major cause of female infertility and patients with obesity and PCOS are particularly common in clinical practice. Long non-coding RNA (lncRNAs) are a functional core in cells that regulate gene expression, transcription, and chromatin modification processes, and participate in epigenetics, cell cycle, and cell differentiation. LncRNAs are assumed to play a role in the occurrence and development of PCOS; however, their specific mechanism of action remains to be elucidated. High-throughput sequencing technology has been used to sequence and analyze lncRNAs in exosomes from the follicular fluid of patients with obesity and PCOS and those who underwent assisted reproductive therapy owing to male factors. Specific expression profiles of patients with obesity and PCOS were obtained and functional information analysis combined with a literature review were performed to screen for differentially expressed lncRNAs, which were validated using real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR). High-throughput sequencing analysis revealed that compared to normal patients with male infertility, patients with obesity and PCOS had a total of 20 lncRNAs with significant expression differences in follicular fluid exosomes. Among them, 17 lncRNAs were upregulated and three were downregulated. Functional analysis showed that differentially expressed genes were mainly enriched in "cell metabolism," "cell adhesion," and other aspects: related gene pathways mainly involved Huntington's disease, Parkinson's disease, spliceosomes, non-alcoholic fatty liver disease, and ribosomes. Verification of differentially expressed lncRNAs revealed that the expression of lncRNAs TPT1-AS1, PTOV1-AS1, PTPRG-AS1, and SNHG14 in follicular fluid exosomes was consistent with the sequencing results. A preliminary differential expression profile of lncRNAs in exosomes of patients with obesity and PCOS was established by transcriptomic analysis of these individuals. Our bioinformatics analysis results may be applicable to further study of the impact mechanism involving obesity and PCOS. These differentially expressed lncRNAs maybe served as potential biomarkers for in-depth studies of the occurrence, development on Follicle quality and function for patients with PCOS in the future.

Continuous evolution of user-defined genes at 1 million times the genomic mutation rate.

When nature evolves a gene over eons at scale, it produces a diversity of homologous sequences with patterns of conservation and change that contain rich structural, functional, and historical information about the gene. However, natural gene diversity accumulates slowly and likely excludes large regions of functional sequence space, limiting the information that is encoded and extractable. We introduce upgraded orthogonal DNA replication (OrthoRep) systems that radically accelerate the evolution of chosen genes under selection in yeast. When applied to a maladapted biosynthetic enzyme, we obtained collections of extensively diverged sequences with patterns that revealed structural and environmental constraints shaping the enzyme's activity. Our upgraded OrthoRep systems should support the discovery of factors influencing gene evolution, uncover previously unknown regions of fitness landscapes, and find broad applications in biomolecular engineering.

API comparison based on the non-functional information mined from Stack Overflow

When comparing similar APIs, developers tend to distinguish them from the aspects of functional details. At the same time, some important non-functional factors (such as performance, usability, and security) may be ignored or noticed after using the API in the project. This may result in unnecessary errors or extra costs. API-related questions are common on Stack Overflow, and they can give a well-rounded picture of the APIs. This provides us with a rich resource for API comparison. However, although many methods are offered for mining Questions and Answers (Q&As) automatically, they often suffer from two main problems: 1) they only focus on the functional information of APIs; 2) they analyze each text in isolation but ignore the correlations among them. In this paper, we propose an approach based on the pre-training model BERT to mine the non-functional information of APIs from Stack Overflow: we first tease out the correlations among questions, answers as well as corresponding reviews, so that one Q&A can be analyzed as a whole; then, an information extraction model is constructed by fine-tuning BERT with three subtasks—entity identification, aspect classification, and sentiment analysis separately, and we use it to mine the texts in Q&As step by step; finally, we summarize and visualize the results in a user-friendly way, so that developers can understand the information intuitively at the beginning of API selection. We evaluate our approach on 4,456 Q&As collected from Stack Overflow. The results show our approach can identify the correlations among reviews with 90.1% precision, and such information can improve the performance of the data mining process. In addition, the survey on maturers and novices indicates the understandability and helpfulness of our method. Moreover, compared with language models, our method can provide more intuitive and brief information for API comparison in non-functional aspects.

Bi-functional and tri-channel image displays based on a single-size nanostructured metasurface enabled by dual-orientation-degeneracy

Benefiting from the extraordinary ability of manipulating lightwaves at the subwavelength scale, nanostructured metasurfaces are expected to achieve multifunctional and multichannel integration to expand functionality and increase information capacity. However, multifunctional and multichannel metasurfaces always consist of various anisotropic nanostructures, inevitably bringing challenges to design and fabrication. In this study, we propose a concept of dual-orientation-degeneracy containing twofold orientation degeneracy. The first-level degeneracy is a one-to-four mapping scheme between the intensity of Channel 1 and orientation angle and the second-level degeneracy refers to a one-to-two mapping between the intensity of Channel 2 and orientation angle. Additionally, we provide a minimalist design of bi-functional and tri-channel image displays based on a single-size nanostructured metasurface. The designed metasurface integrates two functionalities of nanoprinting and holography, which can generate a continuous grayscale meta-image, a binary meta-image and a phase-only holographic image. Three channel displays can be readily switched by polarization controls. More importantly, the metasurface is achieved merely by reconfiguring the orientation angles of the nanostructures with fixed geometries, relieving the structure design and fabrication burden. The presented minimalist design strategy is universal and applicable, which can contribute to advanced research and applications in ultra-compact image displays, high-dense optical storage, multi-folded optical anti-counterfeiting, etc.

Pengaruh Kegagalan Fungsional, Kegagalan Sistem, Kegagalan Informasi dan Kegagalan Layanan Terhadap Penggunaan M-Banking Serta Kaitannya dengan Kepuasan Nasabah BCA Mobile di Indonesia

The rapid development of technology is the main driver of the emergence of digital-based products and services. One of the technology-based banking service products is mobile banking. In Indonesia, the mobile banking that has the most users is BCA Mobile. However, with the largest number of users, the quality of BCA Mobile itself still often complained about by its users. The purpose of this study was to determine how much influence functional failure, system failure, information failure, and service failure have on the use of BCA Mobile and its relationship with user satisfaction. The method used is quantitative method. The sampling technique uses SRS or simple random sampling with a sample size of 400 respondents who are BCA Mobile users in Indonesia. Data collection using a questionnaire distributed via Google Form. The data analysis technique used is SEM - PLS with SmartPLS 4.0 software. The results of this study indicate that functional failure, information failure, and service failure have no effect on the use of BCA Mobile, while system failure has a negative and significant effect on the use of BCA Mobile, and the use of BCA Mobil affects user satisfaction.

Positron emission tomography-magnetic resonance imaging applications in pediatric musculoskeletal tumors.

The hybrid imaging positron emission tomography/magnetic resonance (PET/MR) is an important tool in the management of pediatric oncology patients, particularly in malignant musculoskeletal pathologies, because it combines the functional and metabolic information of tumor provided by PET with the high soft-tissue contrast and the functional information offered by magnetic resonance imaging (MRI). We performed an observational retrospective study that included pediatric patients diagnosed with primary bone or soft-tissue sarcomas in the Pediatric Hematology and Oncology Unit at the HM Montepríncipe University Hospital, Boadilla del Monte, Madrid (Spain) who underwent whole-body 18F-fluorodeoxyglucose (18F-FDG) PET/MRI as a staging study and for follow-up evaluation for treatment response from September 2017 to January 2023. This study explores the protocols, the practical application of the PET/MRI technique and our clinical experience at our center in the diagnosis and follow-up of primary bone tumors and soft-tissue sarcomas in children. Seventy-one 18F-PET/MR studies were performed on 39 patients. Most of them (55%) were initial extension studies and (45%) were follow-up studies. Most of the patients studied were male (74.4%) with a median age of 15 years. Of the 39 cases, 51% were primary bone tumors while 18% were Langerhans cell histiocytosis and 21% soft tissue tumors. Of the 71 studies, five showed metastases at the initial diagnosis, three presented lymph node involvement, one with local infiltration, and one with pulmonary metastasis. PET/MR has represented a significant advancement in the evaluation of pediatric malignant neoplasms, with specific applications in musculoskeletal tumors showing clear benefits over PET/CT. The primary advantage is the reduction in ionizing radiation doses and the assessment of soft tissues, making it an excellent option for malignant musculoskeletal pathologies in pediatric patients who often require long-term follow-up. It is particularly useful for early tumor detection and functional therapy monitoring in oncology. The development of new protocols is making studies increasingly faster and better tolerated, even without the need for anesthesia. PET/MRI has shown to increase diagnostic accuracy in primary bone and soft tissue tumors, as it allows for the comprehensive evaluation of their morpho-metabolic characteristics, locoregional, and distant involvement in a single study. It is also useful in surgical planning and post-treatment follow-up.

Critères d’évaluation de la TEP au 18F-FDG au cours de l’immunothérapie

Checkpoint inhibitor therapy is well established as a first-line treatment for cancer, but assessing treatment response using molecular imaging is still evolving. Evaluating response during checkpoint inhibitor therapy is challenging due to induced immune responses and immune-related adverse effects, which lead to atypical response patterns compared to traditional chemotherapy. Positron emission tomography (PET) and its various radiotracers provide functional information that is valuable for early evaluation of treatment response and can offer critical insights into the efficacy of immunotherapy. Furthermore, PET can help differentiate between patients with a complete response and those with residual disease, potentially guiding clinicians in deciding whether to continue or escalate treatment. This review offers an overview of the application of PET in predicting and evaluating treatment response to immunotherapy, highlighting its potential to refine therapeutic strategies and improve patient outcomes.

Explainable AI framework for skin cancer classification, and melanoma segmentation

Identification and classification of skin diseases are two critical challenges faced in diagnosing and treating patients suffering from them. Deep learning models have been created to best identify and classify skin problems to detect and identify them correctly and effectively. This paper proposes a comprehensive framework for accurate skin cancer prediction, classification, and melanoma surgical lesion extraction. Primarily, a comprehensive extraction method leveraging the unique approach of DenseNet201 and the Local Interpretable Model-Agnostic Explanation offers accurate insight into model decision making and prediction. Secondly, the model has a mid-extraction phase that utilizes advanced convolutional neural network levels to detect the boundaries of melanoma lesions correctly. The framework results in terms of IOU, accuracy, precision, recall, and other metrics compared to existing models like FPN, MAN, and U-Net. The framework presented in our model is smart, easy to use, and can provide functional and accurate information, which means it can be used in clinical practice.

FastProtein-an automated software for in silico proteomic analysis.

Although various tools provide proteomic information, each tool has limitations related to execution platforms, libraries, versions, and data output format. Integrating data generated from different software is a laborious process that can prolong analysis time. Here, we present FastProtein, a protein analysis pipeline that is user-friendly, easily installable, and outputs important information about subcellular location, transmembrane domains, signal peptide, molecular weight, isoelectric point, hydropathy, aromaticity, gene ontology, endoplasmic reticulum retention domains, and N-glycosylation domains. It also helps determine the presence of glycosylphosphatidylinositol and obtain functional information from InterProScan, PANTHER, Pfam, and alignment-based annotation searches. FastProtein provides the scientific community with an easy-to-use computational tool for proteomic data analysis. It is applicable to both small datasets and proteome-wide studies. It can be used through the command line interface mode or a web interface installed on a local server. FastProtein significantly enhances proteomics analysis workflows by producing multiple results in a single-step process, thereby streamlining and accelerating the overall analysis. The software is open-source and freely available. Installation and execution instructions, as well as the source code and test files generated for tool validation, are available at https://github.com/bioinformatics-ufsc/FastProtein.

MOBIDB in 2025: integrating ensemble properties and function annotations for intrinsically disordered proteins.

The MobiDB database (URL: https://mobidb.org/) aims to provide structural and functional information about intrinsic protein disorder, aggregating annotations from the literature, experimental data, and predictions for all known protein sequences. Here, we describe the improvements made to our resource to capture more information, simplify access to the aggregated data, and increase documentation of all MobiDB features. Compared to the previous release, all underlying pipeline modules were updated. The prediction module is ten times faster and can detect if a predicted disordered region is structurally extended or compact. The PDB component is now able to process large cryo-EM structures extending the number of processed entries. The entry page has been restyled to highlight functional aspects of disorder and all graphical modules have been completely reimplemented for better flexibility and faster rendering. The server has been improved to optimise bulk downloads. Annotation provenance has been standardised by adopting ECO terms. Finally, we propagated disorder function (IDPO and GO terms) from the DisProt database exploiting sequence similarity and protein embeddings. These improvements, along with the addition of comprehensive training material, offer a more intuitive interface and novel functional knowledge about intrinsic disorder.

Emerging MRI Biomarkers for Prognostication in Rectal Cancer

Abstract: Rectal cancer is a significant health concern with substantial morbidity and mortality rates. Magnetic Resonance Imaging (MRI) plays a crucial role in the diagnosis and management of rectal cancer, providing detailed anatomical and functional information. However, traditional MRI techniques have limitations in prognosticating tumor behavior and treatment response. The study emphasizes the importance of emerging techniques such as Diffusion-Weighted Imaging (DWI), mrDEC scoring system, Dynamic Contrast-Enhanced MRI (DCE-MRI), Radiomics, and Machine Learning. By examining recent research and clinical trials, we aim to offer a comprehensive overview of the current landscape, challenges, and future directions associated with the incorporation of these MRI biomarkers in predicting outcomes for rectal cancer patients. This review paper aims to provide an overview of the emerging MRI biomarkers that hold the potential for prognostication of rectal cancer.

Premise‐Variable‐Domain‐Partition‐Dependent Output Feedback Switched Controllers Design for Switched IT2 Fuzzy Systems With Switching Signal Transmission Delays and Local Nonlinear Model

ABSTRACTThis article studies the guaranteed cost extended dissipative stabilization problem of switched IT2 fuzzy systems (SIT2FSs) with switching signal transmission delays and local nonlinear model. The guaranteed cost performance, guaranteed cost strict dissipative performance, guaranteed cost − performance and guaranteed cost passivity performance are considered for SIT2FSs in a unified form. First, a novel asynchronous control scheme is proposed for SIT2FSs with local nonlinear model. The controller gains in mismatched interval are designed separately. By using a premise‐variable‐domain‐partition‐dependent switched fuzzy Lyapunov functions (PDSFLFs) approach, the membership‐function‐shape‐independent (MFSI) existence conditions of a class of IT2 fuzzy switched controllers, which can ensure the guaranteed cost extended dissipative performance of SIT2FSs, are established. Then, by utilizing the shape information of membership functions and dividing the premise variable domain into multiple partitions, the membership‐function‐shape‐dependent (MFSD) existence conditions of a class of premise‐variable‐domain‐partition‐dependent (PVDPD) IT2 fuzzy switched controllers are presented. The results indicate that less conservative results can be achieved by using the PVDPD IT2 fuzzy switched controllers, and better system performance can be gotten compared with the Type‐1 fuzzy switched controllers. Finally, the effectiveness of the results is demonstrated through a robot arm model.