Yasmine Labiad¹, Céline Baier¹, Michèle Genin², Caroline Besson^3,4, Sophie Prevot⁵, Hubert Lepidi⁶, Régis Costello^1,7,*

Oncology Research, Vol.34, No.8, 2026, DOI:10.32604/or.2026.076241 - 16 July 2026

Abstract Objectives: Transcriptomic profiling has enabled the classification of Diffuse Large B-Cell Lymphoma (DLBCL) into distinct subtypes, such as Germinal Center B-cell-like (GCB) and Activated B-cell-like (ABC), primarily in HIV-negative patients. However, HIV-associated DLBCL may follow different molecular mechanisms due to immune dysregulation. This study aimed to characterize the transcriptomic landscape of HIV-related DLBCL to identify distinct subtypes and deregulated pathways with potential theranostic implications. Methods: Twelve formalin-fixed, paraffin-embedded DLBCL samples from HIV-positive patients were analyzed using Agilent’s microarray. Quantile normalization and unsupervised hierarchical clustering were performed to classify tumors based on gene expression profiles. Results: Two distinct More > Graphic Abstract

Huajie Zhang^1,2, Xiaopeng Li^1,2, Hanlin Xiao^3,*, Lifeng Xing³, Wenyue Zhou^1,2

Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2026.086505 - 12 July 2026

Abstract This article has no abstract. More >

Qiang Xu^1,*, Leyao Cong¹, Jianing Wang¹, Xingyu Zhu¹, Shaojun Cui¹, Guoqiang Sun², Xueheng Shi²

Energy Engineering, Vol.123, No.8, 2026, DOI:10.32604/ee.2025.073947 - 12 July 2026

Abstract Power system faults can trigger a massive influx of complex alarm signals to the operation and maintenance center, posing significant challenges for dispatchers in accurately identifying the underlying faults. To address the issues of sample imbalance and low accuracy in traditional power grid monitoring alarm event identification methods, a power grid monitoring alarm event identification method based on BERT large language model is proposed. Firstly, information entropy is employed to filter effective monitoring alarm signals, and the k-means clustering algorithm is used to group all alarm signals into different event types, forming the initial power… More >

Chengcheng Sha^*, Manyuan Li, Xiaolei Pan^*

Journal of Psychology in Africa, Vol.36, No.3, pp. 341-349, 2026, DOI:10.32604/jpa.2026.074832 - 30 June 2026

Abstract This study explores how authentic leadership reduces workplace deviance behavior in the era of artificial intelligence (AI) through a chain mediation mechanism involving positive psychological capital and organizational identification. The sample comprised 619 business professionals who regularly used AI tools in their work (52% male; M = 34 years, 20.7% from the service education). The results revealed a significant workplace deviance behavior to be lower with authentic leadership. Organizational identification mediated the relationship between authentic leadership and workplace deviance behavior for lower workplace deviance. Although positive psychological capital alone did not mediate this relationship, it More >

Liqiong Chen¹, Haoyu Jia¹, Mailun Liu², Kai Zhang^1,*, Song Yang¹, Zongjun Jiang¹

Structural Durability & Health Monitoring, Vol.20, No.4, 2026, DOI:10.32604/sdhm.2026.077675 - 30 June 2026

Abstract Buried natural gas pipelines are critical components of energy infrastructure, and their durability and safe operation depend on effective structural health monitoring and the early identification of damage states. In farmland environments, rotary tillage imposes repeated and often concealed mechanical loads on buried pipelines, resulting in stress accumulation, progressive deterioration, and potentially structural failure. However, predictive and interpretable health monitoring approaches that explicitly incorporate rotary tiller-induced damage mechanisms remain scarce. In this study, a physics-informed and interpretable hybrid framework is proposed for the structural health monitoring of buried pipelines subjected to rotary tiller loading. A… More >

Yuan Chen^#, Sumeera Asghar^#, Hanfei Li, Ju Cai, Yin You, Yan Li^*

Phyton-International Journal of Experimental Botany, Vol.95, No.6, 2026, DOI:10.32604/phyton.2026.080045 - 29 June 2026

Abstract The TIFY transcription factor family plays a major role in plant growth and development. Petal size is a very important agronomic characteristic in the ornamental species of Verbena bonariensis. This study identifies 16 TIFY genes (VbTIFYs) in the V. bonariensis genome. Phylogenetic reconstruction divided these genes into six distinct subclades, indicating a high degree of homology between Verbena bonariensis and Arabidopsis thaliana. Promoter sequence analysis illustrated that the promoters of TIFY genes harbor not only cis-acting elements related to hormone regulation, but also functional motifs involved in light responses and low-temperature adaptation. Chromosomal localization results shows that VbTIFY genes… More >

Svetlana Goryunova^1,2,*, Margarita Lebedeva¹, Aya Trifonova¹, Denis Goryunov^2,3, Anastasia Sivolapova², Aleksey Troitsky³, Igor Loskutov⁴, Vitalii Pukhalskiy¹

Phyton-International Journal of Experimental Botany, Vol.95, No.6, 2026, DOI:10.32604/phyton.2026.077294 - 29 June 2026

Abstract Twenty-six cultivated and wild oat species with genomes of varying ploidy levels are currently known worldwide. The search for informative markers, as well as the analysis of variability and phylogeny of oat species, represents a key research directions with both fundamental and applied significance. Chloroplast microsatellites are promising markers for studying groups of closely related species, particularly in the context of allopolyploid origin analyses. The transferability of chloroplast microsatellite markers among species belonging to different “core pooids” supertribes within the Pooideae subfamily of Poaceae has been demonstrated. Following preliminary screening, twelve primer pairs were selected… More >

Hsuan-Chih Ku¹, Jyun-Kai Yang¹, Pang-Wei Tsai¹, Shih-Hsiung Lee^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.079318 - 15 June 2026

Abstract With the rapid proliferation of the Industrial Internet of Things (IIoT), Building Automation Systems (BAS) and Industrial Control Systems (ICS) are increasingly exposed to sophisticated cyber threats. Conventional Intrusion Detection Systems (IDS) often encounter significant limitations when addressing emerging or hybrid attack patterns, primarily due to delayed signature updates and high false-positive rates. Meanwhile, existing anomaly detection approaches frequently lack sufficient awareness of the physical domain, making them ineffective in identifying falsification attacks that comply with communication protocol specifications while violating underlying physical laws. To address these challenges, this study proposes a hybrid threat detection… More >

Asma Sattar¹, Maryam Bukhari², M. Saud Khan³, Anam Mustaqeem⁴, Mi Young Lee⁵, Seungmin Rho^5,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.078413 - 15 June 2026

Abstract Video surveillance systems play an important role in maintaining security in smart city environments. In this context, person identification (Re-ID) systems based on deep learning are currently drawing substantial academic interest. However, these systems remain vulnerable to adversarial attacks. In existing methods, several attacks against Re-ID systems have been designed; nevertheless, they operate in the spatial domain. Existing attacks often suffer from perturbation visibility and low imperceptibility, making them easily detectable by human observers or automated detection systems. From this line of research, this study proposed a novel and potent alternative by designing frequency domain… More >

Amjad Hussain^1,*, Ayesha Saadia^2,*, Chihhsiong Shih³, Nazish Nawaz², Amir H. Gandomi^4,*, Khursheed Aurangzeb⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.078451 - 27 May 2026

Abstract Malware has evolved from the early Creeper virus into highly sophisticated and organized cyber threats. Over time, it grew in sophistication, adopting advanced techniques, stealth tactics, and autonomous propagation. Modern malware leverages encryption, obfuscation, zero-day exploits, and AI-assisted techniques to conduct stealthy and persistent attacks. Classification of its exact family is the end goal to defend and mitigate the latest attacks. Researchers have contributed significantly and introduced many techniques to tackle malware threats. Binary detection is performed at a large scale, but very little in multi-class classification. In this research, a hybrid technique is proposed… More >