Fankun Meng^1,2,3, Yuyang Liu^1,2,*, Xiaohua Liu⁴, Chenlong Duan^1,2, Yuhui Zhou^1,2,3

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.075865 - 06 February 2026

Abstract Carbonate gas reservoirs are often characterized by strong heterogeneity, complex inter-well connectivity, extensive edge or bottom water, and unbalanced production, challenges that are also common in many heterogeneous gas reservoirs with intricate storage and flow behavior. To address these issues within a unified, data-driven framework, this study develops a multi-block material balance model that accounts for inter-block flow and aquifer influx, and is applicable to a wide range of reservoir types. The model incorporates inter-well and well-group conductive connectivity together with pseudo–steady-state aquifer support. The governing equations are solved using a Newton–Raphson scheme, while particle More > Graphic Abstract

Wei Sun^1,2, Yanqing Feng^1,2,*, Yuan Wang^1,2, Zengping Zhao^1,2, Qian Wang², Xiangyun Li³, Dong Feng⁴

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.075630 - 06 February 2026

Abstract Significant differences exist between deep and medium-shallow coalbed methane (CBM) reservoirs. The unclear understanding of flowback and production behavior severely constrains the development of deep CBM resources. To address this challenge, guided by the gas-liquid two-phase flow theory in ultra-low permeability reservoirs, and integrating theoretical analysis, numerical simulation, and insights from production practices, this study classifies the flowback and production stages of deep CBM well considering the Daning-Jixian Block, Eastern Ordos Basin as a representative case. We summarize the flowback characteristics for each stage and establish a standard flowback production type curve, aiming to guide… More > Graphic Abstract

Kwabena Owusu-Mensah^*, Edward Danso Ansong , Kofi Sarpong Adu-Manu, Winfred Yaokumah

Journal of Cyber Security, Vol.8, pp. 33-92, 2026, DOI:10.32604/jcs.2026.074265 - 20 January 2026

Abstract The rapid growth of digital payment systems and remote financial services has led to a significant increase in Card-Not-Present (CNP) fraud, which is now the primary source of card-related losses worldwide. Traditional rule-based fraud detection methods are becoming insufficient due to several challenges, including data imbalance, concept drift, privacy concerns, and limited interpretability. In response to these issues, a systematic review of twenty-four CNP fraud detection frameworks developed between 2014 and 2025 was conducted. This review aimed to identify the technologies, strategies, and design considerations necessary for adaptive solutions that align with evolving regulatory standards.… More >

Ke Liu^1,2,3,#, Xia Xue^1,2,3,#, Haiming Qin^4,5,#, Jiaying Zhu^6,#, Meng Jin^1,6, Die Dai⁶, Youcai Tang¹, Ihtisham Bukhari¹, Hangfan Liu¹, Chunjing Qiu¹, Feifei Ren¹, Pengyuan Zheng^1,2,3, Yang Mi^1,2,3,*, Weihua Chen^6,7,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.072661 - 19 January 2026

Abstract Background: The gut microbiome has emerged as a critical modulator of cancer immunotherapy response. However, the mechanisms by which gut-associated metabolites influence checkpoint blockade efficacy in prostate cancer (PC) remain not fully explored. The study aimed to explore how gut metabolites regulate death-ligand 1 (PD-L1) blockade via exosomes and boost immune checkpoint inhibitors (ICIs) in PC. Methods: We recruited 70 PC patients to set up into five subgroups. The integrated multi-omics analysis was performed. In parallel, we validated the function of gut microbiome-associated metabolites on PD-L1 production and immunotherapy treatment efficacy in PC cell lines… More >

Kamila Mozga¹, Olga Synowiecka¹, Igor Rydzyk¹, Anna Marek¹, Ewelina Wieczorek¹, Alicja Petniak^2,*, Paulina Gil-Kulik²

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.070505 - 19 January 2026

Abstract Objectives: Immunotherapy based on immune checkpoint blockade (ICB) has become a key treatment for melanoma. However, the increasing number of cases of melanoma resistant to immunotherapy highlights the need to develop methods to overcome this resistance. This study aims to collect the most recent information on melanoma immunotherapy, discuss potential strategies to overcome resistance to immunotherapy, and identify areas that require further analysis. Methods: To achieve this goal, scientific publications from 2021–2024 available in PubMed and Google Scholar databases were analyzed. The databases were searched using the following terms: “melanoma”, “immunotherapy”, “Immune Checkpoint Blockade”, and More >

Shuai Zhao, Zhiwei Zhang^*, Junkai Wang, Ye Yuan, Guoren Wang

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073315 - 12 January 2026

Abstract With the development of sharded blockchains, high cross-shard rates and load imbalance have emerged as major challenges. Account partitioning based on hashing and real-time load faces the issue of high cross-shard rates. Account partitioning based on historical transaction graphs is effective in reducing cross-shard rates but suffers from load imbalance and limited adaptability to dynamic workloads. Meanwhile, because of the coupling between consensus and execution, a target shard must receive both the partitioned transactions and the partitioned accounts before initiating consensus and execution. However, we observe that transaction partitioning and subsequent consensus do not require… More >

Bello Musa Yakubu^1,*, Nor Shahida Mohd Jamail ², Rabia Latif ², Seemab Latif ³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072426 - 12 January 2026

Abstract Federated Learning (FL) enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection. This work proposes Secured-FL, a blockchain-based defensive framework that combines smart contract–based authentication, clustering-driven outlier elimination, and dynamic threshold adjustment to defend against adversarial attacks. The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates. Large-scale simulation on the Cyber Data dataset, under up to 50% malicious client settings, demonstrates Secured-FL achieves 6%–12% higher accuracy, More >

Hanaa Nafea¹, Awais Qasim², Sana Abdul Sattar², Adeel Munawar³, Muhammad Nadeem Ali⁴, Byung-Seo Kim^4,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072281 - 12 January 2026

Abstract The increased connectivity and reliance on digital technologies have exposed smart transportation systems to various cyber threats, making intrusion detection a critical aspect of ensuring their secure operation. Traditional intrusion detection systems have limitations in terms of centralized architecture, lack of transparency, and vulnerability to single points of failure. This is where the integration of blockchain technology with signature-based intrusion detection can provide a robust and decentralized solution for securing smart transportation systems. This study tackles the issue of database manipulation attacks in smart transportation networks by proposing a signature-based intrusion detection system. The introduced More >

Jalees Ur Rahman¹, Muhammad Hanif¹, Usman Haider^2,*, Saeed Mian Qaisar^3,*, Sarra Ayouni⁴

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071251 - 12 January 2026

Abstract Deep neural networks have achieved excellent classification results on several computer vision benchmarks. This has led to the popularity of machine learning as a service, where trained algorithms are hosted on the cloud and inference can be obtained on real-world data. In most applications, it is important to compress the vision data due to the enormous bandwidth and memory requirements. Video codecs exploit spatial and temporal correlations to achieve high compression ratios, but they are computationally expensive. This work computes the motion fields between consecutive frames to facilitate the efficient classification of videos. However, contrary… More >

Gowrishankar Jayaraman¹, Ashok Kumar Munnangi², Ramesh Sekaran³, Arunkumar Gopu³, Manikandan Ramachandran^4,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071124 - 12 January 2026

Abstract Industrial Cyber-Physical Systems (ICPSs) play a vital role in modern industries by providing an intellectual foundation for automated operations. With the increasing integration of information-driven processes, ensuring the security of Industrial Control Production Systems (ICPSs) has become a critical challenge. These systems are highly vulnerable to attacks such as denial-of-service (DoS), eclipse, and Sybil attacks, which can significantly disrupt industrial operations. This work proposes an effective protection strategy using an Artificial Intelligence (AI)-enabled Smart Contract (SC) framework combined with the Heterogeneous Barzilai–Borwein Support Vector (HBBSV) method for industrial-based CPS environments. The approach reduces run time… More >