Hashim Ali^*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.087214 - 13 August 2026

Abstract Intensive care unit (ICU) time series are irregular, incomplete, and computationally demanding to model at high temporal resolution. Dense Transformer attention captures long-range dependencies but evaluates all pairwise interactions, including many stable or clinically weak measurements. This study presents Sparse Physio-Attention, a physiology-guided Transformer that retains critical-range violations, patient-relative deviations, informative missingness patterns, and task-relevant variables before sparse attention is computed. Dynamic routing subsequently removes weak attention edges, and a late-fusion adapter incorporates static electronic health record context. The analysis included 25,368 eligible MIMIC-IV ICU stays, of which 2740 were sepsis positive. On the held-out… More >

Zehan Li¹, Yingyi Li^2,*, Zhiwei Tang³, Xuemeng Zhai³, Jiandong Liang¹, Guangmin Hu³

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.086118 - 13 August 2026

Abstract Social network platforms have become primary channels for information dissemination, yet they are increasingly exploited by anomalous users such as bots, fake accounts, and coordinated disinformation spreaders. These malicious actors manipulate public opinion, spread misinformation and undermine platform integrity, posing severe threats to the security of the online ecosystem. Accurate detection of such users is challenging because they often organize into sophisticated high-order connection patterns that extend beyond local neighborhoods. Existing methods address this by either injecting predefined motifs as handcrafted features, which lack flexibility to discover unknown patterns, or employing higher-order Graph neural networks… More >

Mian Muhammad Kamal^1,*, Tianjun Ma^1,*, Mohammed K. Alzaylaee², Husam S. Samkari^3,4, Mohammed F. Allehyani³, Omar Almomani⁵, Heba G. Mohamed^6,7

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.085412 - 13 August 2026

Abstract The cyber-physical network (CPS) combines sensing, communication, and control in physical processes, making them very susceptible to sophisticated cyber-attacks that may cause safety-critical effects. There are two core shortcomings to existing intrusion detection systems (IDS): generative-only models have little transparency of decision-making, while explainable-only models have low robustness in the presence of imbalanced and zero-day attacks. This paper presents a sequentially integrated trustworthy intrusion detection (ID) framework that combines generative learning and explainable AI (XAI) to boost robustness and transparency. The generative module enhances training data diversity, while the explainability module provides post-hoc interpretations during… More >

Qi Li^1,2, Sathish Kumar Selvaperumal^1,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.085073 - 13 August 2026

Abstract Unmanned Aerial Vehicle (UAV) air-to-ground (A2G) communication is a core enabling technology for emerging low-altitude wireless applications. At the same time, accurate real-time channel emulation remains a key bottleneck restricting its large-scale engineering deployment. Conventional universal channel simulators exhibit limited fidelity when modeling UAV-specific fading characteristics and degrade real-time performance on resource-constrained hardware platforms. In this study, we develop a dedicated UAV A2G channel simulator based on a heterogeneous FPGA platform (Processing System (PS) + Programmable Logic (PL)). To achieve high-precision path-loss prediction, we train a lightweight backpropagation neural network (BPNN) using field-measured data in… More >

Bareera Anam, Muhammad Asim, Muhammad Nadeem Ali, Byung-Seo Kim^*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084949 - 13 August 2026

Abstract The rapid evolution of communication networks, driven by the expansion of heterogeneous environments such as 6G, Internet of Things (IoT), and edge computing, has exposed a critical research gap in the lack of unified frameworks that jointly address intelligent network control and quantum-resilient security. Existing networking protocols were originally designed under static configurations and classical security assumptions, making them increasingly inadequate for dynamic, large-scale, and intelligent infrastructures exposed to quantum-enabled threats. At the same time, the emergence of Quantum Computing (QC) introduces severe security risks, as widely used cryptographic mechanisms supporting protocols such as Transport… More >

Ali Hassan¹, Syed Rizwan Hassan^2,*, Ammar Rafiq³

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084672 - 13 August 2026

Abstract Artificial Intelligence of Things (AIoT) systems have emerged through the rapid integration of artificial intelligence (AI) and the Internet of Things (IoT), enabling intelligent sensing, distributed learning, and real-time decision-making across diverse application domains. However, this convergence also introduces a significantly expanded adversarial attack surface spanning sensing devices, communication networks, learning pipelines, and actuation environments. This paper presents a comprehensive systematic review of adversarial threats and defence mechanisms in AIoT systems using a novel 3D-AIoT-TT (Three-Dimensional AIoT Threat Taxonomy) framework. The proposed taxonomy jointly models three fundamental dimensions: (i) AI pipeline stages, (ii) IoT architectural… More >

Muhammad Mujahid¹, Fatima Alshannaq¹, Shaha Al-Otaibi², Tanzila Saba^1,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084273 - 13 August 2026

Abstract Cybersecurity threats in Internet of Things (IoT) networks have escalated, enabled by rapid advancements in wireless communication and edge computing technologies. These advancements expose networks to a wide range of sophisticated and evolving threats and increasingly complex research challenges. Traditional Intrusion Detection and Prevention Systems (IDS/IPS) often fail to provide reliable performance regarding the flexibility and scalability required to handle evolving attack patterns. This study proposes an APENet approach to detect cyberattacks from a real-world cybersecurity dataset, and incorporated a contextual dependency mechanism. The approach captures both local transition dependencies and global relational interactions within… More >

Yi Wen Tan¹, Jun Meng Woh¹, Ee Sin Yong¹, Wai Leong Pang¹, Hui Hwang Goh¹, Kah Yoong Chan², Ari Happonen^3,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083418 - 13 August 2026

Abstract Along with the rapid advancement of Artificial Intelligence (AI), humanoid robots are foreseen to have great potential in the service industry, where human interaction is unavoidable. However, current systems face significant hurdles, including Field of View (FoV) problems, markerless real-time mimicry capabilities for humanoid’s fingers and arms. This study addresses these hurdles by developing an integrated hardware and software pipeline for the Unitree G1 Edu humanoid robot. A custom 3D-printed helmet and stabiliser interface were designed using FreeCAD and fabricated to house an external Orbbec Gemini 2 RGB-D sensor, optimising the FoV for frontal human-robot… More >

Shih-Wei Chiang^1,2, Ming-Cheng Chen^2,3, Chang-Lin Lin², Yi-Lin Huang², Feng-Fan Chiang^2,4,*, Shun-Fa Yang^1,5,*

Oncology Research, Vol.34, No.9, 2026, DOI:10.32604/or.2026.085229 - 13 August 2026

Abstract Background: Anti-EGFR therapy is widely used as first-line treatment for RAS wild-type metastatic colorectal cancer (mCRC), particularly in patients with left-sided tumors. In liver-limited disease, maximizing tumor shrinkage may facilitate conversion to resectability; however, comparative real-world evidence among panitumumab, cetuximab, and bevacizumab remains limited. This study aimed to compare the clinical outcomes of these biologic agents in patients with RAS wild-type mCRC. Methods: We retrospectively analyzed 241 patients with RAS wild-type mCRC treated with first-line chemotherapy plus panitumumab (n = 76), cetuximab (n = 80), or bevacizumab (n = 85) between 2016 and 2024. Outcomes included depth of response… More >

Emmanuel Naveen Raj^1,#, Chia-Jung Li^1,2,3,4,5,#, Shih-Hsuan Cheng¹, Su-Boon Yong^6,7, Zhi-Hong Wen^3,8, An-Jen Chiang^1,9,*

Oncology Research, Vol.34, No.9, 2026, DOI:10.32604/or.2026.079551 - 13 August 2026

Abstract Objectives: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) necessitate the discovery of novel biomarkers for prognostic and therapeutic advancement. This study aims to evaluate the clinical significance of ubiquitin-conjugating enzyme E2C (UBE2C) and its association with the tumor microenvironment (TME) in CESC. Methods: We meticulously sourced CESC data from renowned repositories such as The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO), leveraging cutting-edge techniques including single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and pharmacogenomics. Through multifaceted data analysis, we endeavored to unravel the intricate role and potential value of UBE2C in… More > Graphic Abstract