bluuebunny/crossref_metadata_2025 huggingface dataset:
Multikinase Treatment of Glioblastoma: Evaluating the Rationale for Regorafenib
Authors: Muñoz-Mármol Ana Maria , Meléndez Bárbara , Hernandez Ainhoa , Sanz Carolina , Domenech Marta , Arpí-Llucia Oriol , Gut Marta , Esteve Anna , Esteve-Codina Anna , Parra Genis , Carrato Cristina , Aldecoa Iban , Mallo Mar , Pineda Estela , Alameda Francesc , de la Iglesia Nuria , Martinez-Balibrea Eva , Martinez-Cardús Anna , Estival-Gonzalez Anna , Balana Carmen
Published: January 2025

We explored the rationale for treating glioblastoma (GBM) with regorafenib. In 103 newly diagnosed GBM patients, we assessed mutations, copy number variants (CNVs), fusions, and overexpression in 46 genes encoding protein kinases (PKs) potentially targeted by regorafenib or its metabolites and performed a functional enrichment analysis to assess their implications in angiogenesis. We analyzed regorafenib’s binding inhibitory activity and target affinity for these 46 PKs and focused on a subset of 18 genes inhibited by regorafenib at clinically achievable concentrations and on 19 genes involved in angiogenesis. Putative oncogenic alterations were defined as oncogenic/likely oncogenic mutations, oncogenic fusions, CNVs > 5, and/or gene overexpression. Regorafenib did not target all 46 PKs. For the 46-gene set, 40 genes (86.9%) and 73 patients (70.8%) harbored at least one alteration in genes encoding targetable PKs, but putative oncogenic alterations were present in only 34 patients (33%). In the 18-gene set, 18 genes (100%) and 48 patients (46.6%) harbored alterations, but putative oncogenic alterations were detected in only 26 patients (25.2%). Thirty patients (29.1%) had oncogenic alterations in the 18-gene set and/or in angiogenesis-related genes. Around 33% of patients had oncogenic alterations in any of the 46 potential targets. Additionally, the suboptimal dosing of regorafenib, due to its poor penetration of the blood–brain barrier, may reduce the likelihood of effectively targeting certain PKs. Future use of multi-target drugs must be guided by a thorough understanding of target presence, effective inhibition, and the drug’s ability to reach brain tumors at adequate concentrations.
Personalized Immunity: Neoantigen-Based Vaccines Revolutionizing Hepatocellular Carcinoma Treatment
Authors: Aggeletopoulou Ioanna , Pantzios Spyridon , Triantos Christos
Published: January 2025

Hepatocellular carcinoma (HCC), the most prevalent form of primary liver cancer, presents significant therapeutic challenges due to its molecular complexity, late-stage diagnosis, and inherent resistance to conventional treatments. The intermediate to low mutational burden in HCC and its ability to evade the immune system through multiple mechanisms complicate the development of effective therapies. Recent advancements in immunotherapy, particularly neoantigen-based vaccines, offer a promising, personalized approach to HCC treatment. Neoantigens are tumor-specific peptides derived from somatic mutations in tumor cells. Unlike normal cellular antigens, neoantigens are foreign to the immune system, making them highly specific targets for immunotherapy. Neoantigens arise from genetic alterations such as point mutations, insertions, deletions, and gene fusions, which are expressed as neoepitopes that are not present in healthy tissues, thus evading the immune tolerance mechanisms that typically protect normal cells. Preclinical and early-phase clinical studies of neoantigen-based vaccines have shown promising results, demonstrating the ability of these vaccines to elicit robust T cell responses against HCC. The aim of the current review is to provide an in-depth exploration of the therapeutic potential of neoantigen-based vaccines in HCC, focusing on neoantigen identification, vaccine platforms, and their integration with immune checkpoint inhibitors to enhance immunogenicity. It also evaluates preclinical and clinical data on efficacy and safety while addressing challenges in clinical translation. By taking advantage of the unique antigenic profile of each patient’s tumor, neoantigen-based vaccines represent a promising approach in the treatment of HCC, offering the potential for improved patient outcomes, long-term remission, and a shift towards personalized, precision medicine in liver cancer therapy.
Analysis of CeO2-Supported Ru Catalysts for an Efficient Catalytic Wet Air Oxidation of Reconstituted Tobacco Wastewater
Authors: Qian Guanfan , Zhong Fan , Lu Hongliang , Chen Huangbin , Shi Jianzai , Ma Pengfei , Deng Xiaohua , Fang Zhengzhong , Zhang Nuowei , Zheng Quanxing , Chen Binghui
Published: January 2025

CeO2-supported noble metal catalysts show great application potential in the catalytic oxidation of volatile organic compounds and hazardous organic wastewater. In this paper, an efficient Ru/CeO2 catalyst is developed by combining the oxygen affinity of noble metals and the redox of supports for catalytic wet air oxidation (CWAO) of reconstituted tobacco wastewater. First, what factors affect the catalytic performance are studied by investigating the effect of supports (C, TiO2, Al2O3, and CeO2) and noble metals (Pt, Pd, and Ru) on the activity. Second, the catalytic performance of Ru/CeO2 is further enhanced by tuning the morphology of CeO2 supports. The results indicate that the Ru/CeO2-R (rod-like) catalyst is highly active and can reach a high TOC conversion of 97.6% at 220 °C in 1 h. In contrast, the TOC conversions of Ru/CeO2-MOF, Ru/CeO2-NP (nanoparticle), and Ru/CeO2-C (cube-like) are 93.3, 77.9, and 68.2%, respectively. Ru/CeO2-R also presented good stability. The TOC conversion can be maintained at approximately 85% in four consecutive cycles. The characterization results indicate that better Ru dispersion, higher Ce3+ content, more surface reactive oxygen species, electron transfer between Ru and CeO2-R, and oxygen transfer from CeO2-R to Ru are the main reasons for the best catalytic performance of the Ru/CeO2-R catalyst.
Effect of Support on Complete Hydrocarbon Oxidation over Pd-Based Catalysts
Authors: Tabakova Tatyana , Grahovski Bozhidar , Karakirova Yordanka , Petrova Petya , Venezia Anna Maria , Liotta Leonarda Francesca , Todorova Silviya
Published: January 2025

Developing efficient strategies for VOC emission abatement is an urgent task for protection of the environment and human health. Complete catalytic oxidation exhibits advantages, making it an effective, environmentally friendly, and economically profitable approach for VOC elimination. Pd-based catalysts are known as highly active for hydrocarbon catalytic oxidation. The nature of carrier materials is of particular importance because it may affect activity by changing physicochemical properties of the palladium species. In this work, Al2O3, CeO2, CeO2-Al2O3, and Y-doped CeO2-Al2O3 were used as carriers of palladium catalysts. Methane and benzene were selected as representatives of two types of hydrocarbons. A decisive step in complete methane oxidation is the first C–H bond breaking, while the extraordinary stability of the six-membered ring structure is a challenge in benzene oxidation. The support effect was explored by textural measurements using XRF, XRD, XPS, EPR, and TPR techniques. Three ceria-containing samples showed superior CH4 oxidation performance, achieving 90% methane conversion at about 300 °C and complete oxidation at 320 °C. Evidence for presence of Pd2+ species in all samples regarded as most active was provided by XP-derived analysis. Pd/Y-Ce/Al catalysts exhibited very high activity in benzene oxidation by reaching 100% conversion at 180 °C. The contributions of higher Pd and Ce3+ surface concentrations, the presence of O2−-adsorbed superoxo species, and Pd0 ↔ PdO redox transfer were considered. The potential of a simple, environmentally friendly, and less energy demanding mechanochemical preparation procedure of mixed oxides was demonstrated.
Similarities in Mechanisms of Ovarian Cancer Metastasis and Brain Glioblastoma Multiforme Invasion Suggest Common Therapeutic Targets
Authors: Jackson Gia A. , Adamson David Cory
Published: January 2025

Epithelial-to-mesenchymal transition (EMT) is a critical process in malignant ovarian cancer metastasis. EMT involves the conversion of epithelial cells to mesenchymal cells, conferring enhanced migratory and invasive capabilities. Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor and exhibits an aggressive invasive phenotype that mimics some steps of EMT but does not undergo true metastasis, i.e., the invasion of other organ systems. This study conducts a comparative genomic analysis of EMT in ovarian cancer and invasion in GBM—two malignancies characterized by poor prognosis and limited therapies. Investigating the molecular biology in ovarian cancer and GBM demonstrates shared mechanisms of tumor progression, such as similar genetic and molecular pathways influencing cell plasticity, invasion, and resistance to therapy. The comparative analysis reveals commonalities and differences in the regulatory networks and gene expression profiles associated with EMT and invasion in these cancers. Key findings include the identification of core EMT regulators, such as TWIST1, SNAIL, and ZEB1, which are upregulated in both ovarian cancer and GBM, promoting mesenchymal phenotypes and metastasis. Additionally, the analysis uncovers EMT-related pathways, such as the PI3K/AKT and TGF-β signaling, which are critical in both cancers but exhibit distinct regulatory dynamics. Understanding the intricacies of EMT in ovarian cancer and invasion in GBM provides valuable insights into their aggressive behavior and identifies potential common therapeutic targets. The findings stress the importance of targeting EMT/invasion transitions to develop effective treatments to halt progression and improve patient outcomes in these malignancies.
Decoding Cytokine Dynamics: Wharton’s Jelly Stromal Cells and Chondro-Differentiates in PHA-Stimulated Co-Culture
Authors: Meenakshi Sundaram Raja Sundari , Rupert Secunda , Srinivasan Prasanna , Sathyanesan Jeswanth , Govarthanan Kavitha , Jeyaraman Naveen , Ramasubramanian Swaminathan , Jeyaraman Madhan , Chung Ho Yun , Gangadaran Prakash , Ahn Byeong-Cheol
Published: January 2025

Introduction: Articular cartilage damage presents a significant clinical challenge, with limited options for effective regeneration. Mesenchymal stromal cells (MSCs) derived from Wharton’s jelly (WJ) are a promising cell source for cartilage repair due to their regenerative and immunomodulatory properties. While undifferentiated MSCs have demonstrated potent immunoregulatory effects, the immunomodulatory potential of chondrocytes derived from WJ-MSCs remains underexplored, particularly under inflammatory conditions. This study investigates the differential cytokine expression profiles of WJ-MSC-derived chondrocytes and undifferentiated MSCs under inflammatory stimulation with phytohemagglutinin (PHA) to understand their immunomodulatory capacities. Materials and Methods: WJ-MSCs were differentiated into chondrocytes using a micromass culture system. Differentiated chondrocytes were then co-cultured with immune cells under PHA-induced inflammatory conditions. Control groups included co-cultured cells without PHA activation and chondrocytes activated with PHA in the absence of immune cell interaction. Cytokine expression profiles were analyzed using the RT2 Customized Gene Array to evaluate pro- and anti-inflammatory markers. Morphological changes were assessed microscopically. The immunomodulatory responses of chondrocytes were compared to those of undifferentiated MSCs under the same experimental conditions. Results: Chondrocytes co-cultured with immune cells under PHA activation exhibited downregulation of IDO, HLA-G, PDGF, IL-10, TNF-α, IL-6, and IFN-γ compared to undifferentiated MSCs in similar conditions. In non-PHA co-cultured conditions, chondrocytes showed increased expression of IL-6, IFN-γ, IL-4, VEGF, iNOS, PDGF, PTGS-2 and TGF-β, while TNF-α, IL-10, IDO and HLA-G were decreased. In contrast, chondrocytes activated with PHA without immune cell interaction displayed reduced expression of HLA-G and TNF-α, with no significant changes in IL-6, IFN-γ, IL-4, IL-10, VEGF, PDGF, PTGS-2, TGF-β, IDO, and iNOS compared to PHA-stimulated undifferentiated MSCs. Conclusion: This study demonstrates that chondrocytes derived from WJ-MSCs exhibit limited immunomodulatory potential compared to undifferentiated MSCs, particularly under PHA-induced inflammatory conditions. Undifferentiated MSCs showed superior regulation of key cytokines associated with immune modulation. These findings suggest that maintaining MSCs in an undifferentiated state may be advantageous for therapeutic applications targeting inflammatory conditions, such as osteoarthritis. Future research should explore strategies to enhance the immunomodulatory efficacy of chondrocytes, potentially through genetic modification or adjunctive therapies.
A Computational Study on Two-Parameter Singularly Perturbed Third-Order Delay Differential Equations
Authors: Rajendran Mahendran , Sethurathinam Senthilkumar , Veerasamy Subburayan , Agarwal Ravi P.
Published: January 2025

A class of third-order singularly perturbed two-parameter delay differential equations of boundary value problems is studied in this paper. Regular and singular components are used to estimate the solution’s a priori bounds and derivatives. A fitted finite-difference method is constructed to solve the problem on a Shishkin mesh. The numerical solution converges uniformly to the exact solution; it is validated via numerical test problems. The order of convergence of the numerical method is almost first-order, which is independent of the parameters ε and μ.
A Two-for-One Diagnosis: A Rare Case of Chronic Abdominal Pain Caused by Gastroptosis and Wilkie’s Syndrome in a Young Woman
Authors: Youssoufi Nosseir , Jaafari Ayoub , Mansour Sohaïb , El Hamdi Mohamed , Gallerani Andrea , Pierrakos Charalampos , Attou Rachid
Published: January 2025

Long-term abdominal pain (LAP) affects 30% to 40% of children, often linked to functional gastrointestinal disorders (FGIDs) such as functional dyspepsia and irritable bowel syndrome. Less common causes include gastroptosis and superior mesenteric artery (SMA) syndrome, conditions that can be challenging to diagnose due to their rarity. Gastroptosis refers to the downward displacement of the stomach, while SMA syndrome, also known as Wilkie’s syndrome, involves the compression of the duodenum between the abdominal aorta and the superior mesenteric artery. While both conditions have been described separately, their coexistence has not been previously documented. Herein, we present the case of a 17-year-old girl with a six-month history of postprandial abdominal pain and vomiting, diagnosed with both gastroptosis and SMA syndrome. Diagnostic tests, including a CT scan and barium radiography, confirmed the presence of a duodenal stricture and severe gastric elongation, providing an insight into the pathophysiology of these rare conditions.
Lightweight Deep Learning Framework for Accurate Detection of Sports-Related Bone Fractures
Authors: Abdusalomov Akmalbek , Mirzakhalilov Sanjar , Umirzakova Sabina , Ismailov Otabek , Sultanov Djamshid , Nasimov Rashid , Cho Young-Im
Published: January 2025

Background/Objectives: Sports-related bone fractures are a common challenge in sports medicine, requiring accurate and timely diagnosis to prevent long-term complications and enable effective treatment. Conventional diagnostic methods often rely on manual interpretation, which is prone to errors and inefficiencies, particularly for subtle and localized fractures. This study aims to develop a lightweight and efficient deep learning-based framework to improve the accuracy and computational efficiency of fracture detection, tailored to the needs of sports medicine. Methods: We proposed a novel fracture detection framework based on the DenseNet121 architecture, incorporating modifications to the initial convolutional block and final layers for optimized feature extraction. Additionally, a Canny edge detector was integrated to enhance the model ability to detect localized structural discontinuities. A custom-curated dataset of radiographic images focused on common sports-related fractures was used, with preprocessing techniques such as contrast enhancement, normalization, and data augmentation applied to ensure robust model performance. The model was evaluated against state-of-the-art methods using metrics such as accuracy, recall, precision, and computational complexity. Results: The proposed model achieved a state-of-the-art accuracy of 90.3%, surpassing benchmarks like ResNet-50, VGG-16, and EfficientNet-B0. It demonstrated superior sensitivity (recall: 0.89) and specificity (precision: 0.875) while maintaining the lowest computational complexity (FLOPs: 0.54 G, Params: 14.78 M). These results highlight its suitability for real-time clinical deployment. Conclusions: The proposed lightweight framework offers a scalable, accurate, and efficient solution for fracture detection, addressing critical challenges in sports medicine. By enabling rapid and reliable diagnostics, it has the potential to improve clinical workflows and outcomes for athletes. Future work will focus on expanding the model applications to other imaging modalities and fracture types.
Water Hyacinth Invasion and Management in a Tropical Hydroelectric Reservoir: Insights from Random Forest and SVM Classification
Authors: Correa-Mejía Luis Fernando , Garcés-Gómez Yeison Alberto
Published: January 2025

The rapid proliferation of water hyacinth (Eichhornia crassipes) in newly formed reservoirs poses a significant threat to aquatic ecosystems and hydroelectric operations. The objective of this study was to map and monitor the spatio-temporal distribution of water hyacinth in the Hidroituango reservoir in Colombia from 2018 to 2023, using Sentinel-2 satellite imagery and machine learning algorithms. The Random Forest (RF) and Support Vector Machine (SVM) algorithms were employed for image classification, and their performance was evaluated using various accuracy metrics. The results revealed that both algorithms effectively detected and mapped water hyacinth infestations, with RF demonstrating greater stability in capturing long-term trends and SVM exhibiting higher sensitivity to rapid changes in coverage. The study also highlighted the impact of the COVID-19 pandemic on control efforts, leading to a temporary increase in infestation. The findings underscore the importance of continuous monitoring and adaptive management strategies to mitigate the ecological and economic impacts of water hyacinth in the Hidroituango reservoir and similar environments.
Analysis of Maternity Rights Perception: Impact of Maternal Care in Diverse Socio-Health Contexts
Authors: Silva-Fernández Claudia Susana , Camacho Paul Anthony , de la Calle María , Arribas Silvia M. , Garrosa Eva , Ramiro-Cortijo David
Published: January 2025

Maternity rights are perceived and fulfilled differently according to women’s psychosocial characteristics, leading to varying maternal experiences and outcomes. It is necessary to know the impact of cultural context, emotional well-being, and resource availability on the maternal woman’s clinical care experience. The aim is to identify if these factors contribute to disparities in the perception of maternity rights fulfillment in Spain and Colombia. This retrospective observational study focused on women who received maternity-related healthcare in Spain or Colombia. A total of 185 women were included (Spanish = 53; Colombian = 132). Data collected included social and obstetric history, as well as psychological variables such as resilience, positive and negative affect, derailment, and maternity beliefs. The study also assessed women’s knowledge of healthcare rights (MatCODE), perceptions of resource scarcity (MatER), and the fulfillment of maternity rights (FMR). C-section was more prevalent in Colombia, where women also scored higher on maternity beliefs as a sense of life and as a social duty compared to Spanish women. Conversely, FMR was higher in the Spanish context. Colombian women reported lower levels of social support and less involvement in medical decision-making. The FMR was positively correlated with positive affect, MatCODE, and MatER. Predictive modeling identified negative factors for FMR, including giving birth in Colombia (β = −0.30 [−0.58; −0.03]), previous miscarriage (β = −0.32 [−0.54; −0.09]), C-section in the most recent labor (β = −0.46 [−0.54; −0.0]), and higher MatER scores. Positive predictors included gestational age, maternal age, and previous C-section (β = 0.39 [0.11; 0.66]). The perception of the fulfillment of maternity rights depends on socio-healthcare contexts, women’s age, obstetric history, and resources. It is suggested to apply culturally sensitive strategies focused on women’s needs in terms of information, emotional and social support, privacy, and autonomy to manage a positive experience.
Energy-Efficient Deployment of Laser Illumination for Rotating Vertical Farms
Authors: Liu Tian , Ye Yunxiang , Tan Shiyi , Xue Xianglei , Zheng Hang , Ren Ning , Shen Shuai , Yu Guohong
Published: January 2025

As the global population grows, vertical farming offers a promising solution by using vertically stacked shelves in controlled environments to grow crops efficiently within urban areas. However, the shading effects of farm structures make artificial lighting a significant cost, accounting for approximately 67% of total operational expenses. This study presents a novel approach to optimizing the deployment of laser illumination in rotating vertical farms by incorporating structural design, light modeling, and photosynthesis. By theoretically analyzing the beam pattern of laser diodes and the dynamics in the coverage area of rotating farm layers, we accurately characterize the light conditions on each vertical layer. Based on these insights, we introduce a new criterion, cumulative coverage, which accounts for both light intensity and coverage area. Then, an optimization framework is formulated, and a swarm intelligence algorithm, Differential Evolution (DE) is used to solve the optimization while considering the structural and operational constraints. It is found that tilting lights and placing them slightly off-center are more effective than traditional vertically aligned and center-aligned deployment. Our results show that the proposed strategy improves light coverage by 4% compared to the intensity-only optimization approach, and by 10% compared to empirical methods. This study establishes the first theoretical framework for designing energy-efficient artificial lighting deployment strategies, providing insights into enhancing the efficiency of vertical farming systems.
A 13–33 GHz Wideband Low-Noise Amplifier in 150-nm GaAs Based on Simultaneous Noise- and Input-Matched Gain-Core with R-L-C Shunt Feedback Network
Authors: Hwang Seonyeong , Kang Dongwan , Lee Yeonggeon , Park Dae-Woong
Published: January 2025

This work reports the concept of a shunt negative feedback technique for implementing a millimeter-wave wideband low-noise amplifier. The proposed shunt negative feedback network consists of a resistor–capacitor–inductor configuration. The proposed feedback network can achieve simultaneous noise and input matching (SNIM) over a wide frequency range by adjusting the values of the resistor–capacitor–inductor configuration based on numerical analysis. By adopting the SNIM-based gain core as the first stage of the amplifier, the simulation results of the three-stage low-noise amplifier in a 150-nm GaAs pHEMT process achieve a gain of 15.6–18.6 dB and a noise figure of 1.05–2.8 dB in the frequency range of 13–33 GHz, respectively, while dissipating 99 mW.
Zero-Shot Rolling Bearing Fault Diagnosis Based on Attribute Description
Authors: Fan Guorong , Li Lijun , Zhao Yue , Shi Hui , Zhang Xiaoyi , Dong Zengshou
Published: January 2025

Traditional fault diagnosis methods for rolling bearings rely on nemerous labeled samples, which are difficult to obtain in engineering applications. Moreover, when unseen fault categories appear in the test set, these models fail to achieve accurate diagnoses, as the fault categories are not represented in the training data. To address these challenges, a zero-shot fault diagnosis model for rolling bearings is proposed, which realizes knowledge transfer from seen to unseen categories by constructing attribute information, thereby reducing the dependence on labeled samples. First, an attribute method Discrete Label Embedding Method (DLEM) based on word embedding and envelope analysis is designed to generate fault attributes. Fault features are extracted using the Swin Transformer model. Then, the attributes and features are input into the constructed model Distribution Consistency and Multi-modal Cross Alignment Variational Autoencoder (DCMCA-VAE), which is built on Convolutional Residual SE-Attention Variational Autoencoder (CRS-VAE). CRS-VAE replaces fully connected layers with convolutional layers and incorporates residual connections with the Squeeze-and-Excitation Joint Attention Mechanism (SE-JAM) for improved feature extraction. The DCMCA-VAE also incorporates a reconstruction alignment module with the proposed distribution consistency loss LWT and multi-modal cross alignment loss function LMCA. The reconstruction alignment module is used to generate high-quality features with distinguishing information between different categories for classification. In the face of multiple noisy datasets, this model can effectively distinguish unseen categories and has stronger robustness than other models. The model can achieve 100% classification accuracy on the SQ dataset, and more than 85% on the CWRU dataset when unseen and seen categories appear simultaneously with noise interference.
Research on Transfer Alignment Algorithms Based on SE(3) in ECEF Frame
Authors: Lin Hongyi , Bian Hongwei , Wang Rongying , Tang Jun
Published: January 2025

The initial attitude error is challenging to satisfy the requirements of the linear model due to the complex nature of the ocean environment. This presents a challenge in the transfer alignment of the ship. In order to enhance the precision and velocity of ship transfer alignment, as well as to streamline the alignment processes, this paper proposes a transfer alignment methodology based on the Earth-Centered Earth-Fixed (ECEF) frame special Euclidean group (SE(3)) matrix Lie group. After introducing the two navigation states, velocity and attitude, from the ECEF frame into SE(3), the nonlinear inertial navigation system error state model and its corresponding measurement equations are derived based on the mapping relationship between the Lie groups and Lie algebra. The method effectively solves the error problem due to linear approximation in the traditional transfer alignment method, and applies to misalignment angles of arbitrary scale. The simulation results verify the effectiveness and rapidity of the proposed alignment method in the case of arbitrary misalignment angles.
Learnable Anchor Embedding for Asymmetric Face Recognition
Authors: Kim Jungyun , Ng Tiong-Sik , Teoh Andrew Beng Jin
Published: January 2025

Face verification and identification traditionally follow a symmetric matching approach, where the same model (e.g., ResNet-50 vs. ResNet-50) generates embeddings for both gallery and query images, ensuring compatibility. However, real-world scenarios often demand asymmetric matching, especially when query devices have limited computational resources or employ heterogeneous models (e.g., ResNet-50 vs. SwinTransformer). This asymmetry can degrade face recognition performance due to incompatibility between embeddings from different models. To tackle this asymmetric face recognition problem, we introduce the Learnable Anchor Embedding (LAE) model, which features two key innovations: the Shared Learnable Anchor and a Light Cross-Attention Mechanism. The Shared Learnable Anchor is a dynamic attractor, aligning heterogeneous gallery and query embeddings within a unified embedding space. The Light Cross-Attention Mechanism complements this alignment process by reweighting embeddings relative to the anchor, efficiently refining their alignment within the unified space. Extensive evaluations of several facial benchmark datasets demonstrate LAE’s superior performance, particularly in asymmetric settings. Its robustness and scalability make it an effective solution for real-world applications such as edge-device authentication, cross-platform verification, and environments with resource constraints.
Efficient Quantization and Data Access for Accelerating Homomorphic Encrypted CNNs
Authors: Chen Kai , Wang Xinyu , Fu Yuxiang , Li Li
Published: January 2025

Due to the ability to perform computations directly on encrypted data, homomorphic encryption (HE) has recently become an important branch of privacy-preserving machine learning (PPML) implementation. Nevertheless, existing implementations of HE-based convolutional neural network (HCNN) applications are not satisfactory in inference latency and area efficiency compared to the unencrypted version. In this work, we first improve the additive powers-of-two (APoT) quantization method for HCNN to achieve a better tradeoff between the complexity of modular multiplication and the network accuracy. An efficient multiplicationless modular multiplier–accumulator (M-MAC) unit is accordingly designed. Furthermore, a batch-processing HCNN accelerator with M-MACs is implemented, in which we propose an advanced data partition scheme to avoid multiple moves of the large-size ciphertext polynomials. Compared to the latest FPGA design, our accelerator can achieve 11× resource reduction of an M-MAC and 2.36× speedup in inference latency for a widely used CNN-11 network to process 8K images. The speedup of our design is also significant compared to the latest CPU and GPU implementations of the batch-processing HCNN models.
Assessing the Sustainability of Energy-Related Nanomaterial Synthesis: Emphasizing the Need for Energy-Efficient Nanomaterial Preparation Techniques
Authors: Hasan Nazim , Muthu Manikandan , Hakami Othman , Gopal Judy
Published: January 2025

Sustainable energy has always been the top-priority research discussion, and nanomaterials in energy applications have facilitated the achievement of this goal. For the first time, this review highlights the subtle, overlooked, unaccounted expenditure of energy going into nanomaterial synthesis. In the present article, we give a brief overview of the various nanomaterials used in energy applications and present their general synthesis methods. The lack of data/information on the energy expended on nanomaterial synthesis has been critically pointed out. The alternative, energy-saving, energy-efficient methods, considering sustainability even at the nanomaterial synthesis level, have been put forth as recommendations. This article aims at creating an awareness towards planning of holistic sustainable energy-efficient nanomaterial synthesis processes that will conserve energy. The question projected is: what is the purpose of losing energy during synthesis of energy producing and energy storing nanomaterials?
Investigation on Flow Features and Combustion Characteristics in a Boron-Based Solid-Ducted Rocket Engine
Authors: Tang Xiang , Tian Xiaotao , Zhu Liang , Wu Suli , Huang Meng , Li Weixuan
Published: January 2025

Numerical and experimental approaches are conducted to investigate the flow features and secondary combustion performance induced by different air–fuel ratios in a boron-based solid-ducted rocket engine. The results indicated that the afterburning chamber flow features become more complicated owing to the multiple nozzles of the gas injector, and a number of recirculation zones are generated. Because of this, the mixing of the fuel gas and incoming air is enhanced. When the air–fuel ratio decreases, the heat release in the afterburning chamber increases continuously, which causes the pre-combustion shock train to continue to propagate upstream in the subsonic diffuser of the inlet isolator, along with the boundary layer separation zone also moving forward, and the stability margin of the direct-connect inlet decreasing gradually. Furthermore, the direct-connect inlet works at a critical state with an air–fuel ratio of 11.5. As the mass flow rate of the fuel-rich gas rises gradually, the engine thrust gradually increases, and the number of vortexes in the afterburning chamber and the corresponding region affected by the vortexes generally decrease. Meanwhile, the mixing and combustion of the fuel-rich gas and incoming flow were not substantially changed. Additionally, the combustion efficiency and specific impulse are proportional to the air fuel ratio.
Reinforced NEAT Algorithms for Autonomous Rover Navigation in Multi-Room Dynamic Scenario
Authors: Shrestha Dhadkan , Valles Damian
Published: January 2025

This paper demonstrates the performance of autonomous rovers utilizing NeuroEvolution of Augmenting Topologies (NEAT) in multi-room scenarios and explores their potential applications in wildfire management and search and rescue missions. Simulations in three- and four-room scenarios were conducted over 100 to 10,000 generations, comparing standard learning with transfer learning from a pre-trained single-room model. The task required rovers to visit all rooms before returning to the starting point. Performance metrics included fitness score, successful room visits, and return rates. The results revealed significant improvements in rover performance across generations for both scenarios, with transfer learning providing substantial advantages, particularly in early generations. Transfer learning achieved 32 successful returns after 10,000 generations for the three-room scenario compared to 34 with standard learning. In the four-room scenario, transfer learning achieved 32 successful returns. Heatmap analyses highlighted efficient navigation strategies, particularly around starting points and target zones. This study highlights NEAT’s adaptability to complex navigation problems, showcasing the utility of transfer learning. Additionally, it proposes the integration of NEAT with UAV systems and collaborative robotic frameworks for fire suppression, fuel characterization, and dynamic fire boundary detection, further strengthening its role in real-world emergency management.
Study on Smoke Leakage Performance in Mass Timber Construction Taking Cross-Laminated Timber Walls as an Example
Authors: Chang Wen-Yao , Lin Ching-Yuan , Chuang Ying-Ji , Tsai Meng-Ting
Published: January 2025

In contemporary building design, partition walls combined with doors and windows are commonly used to control the spread of smoke. Understanding the smoke leakage characteristics of cross-laminated timber (CLT) walls is crucial for enhancing safety. This study investigates the smoke-sealing performance of CLT walls through full-scale tests, focusing on the application of this type of mass timber construction in smoke control. The test specimens included four joints, with leakage measured under two conditions—non-fire and fire exposure—at three different pressure differentials. A total of 72 tests were conducted. The results showed that under non-fire conditions, the leakage rate was 0.00 m3/h, while exposure to fire caused a significant increase in leakage. Under a pressure differential of 25 Pa, the average leakage rate was 8.17 m3/h, with a maximum of 8.27 m3/h. This study also proposes a method for evaluating the leakage rate of a single joint, which helps estimate the smoke layer descent time and, in turn, the allowable evacuation time. The findings not only enhance the fire safety performance of mass timber construction but also provide valuable insights for evacuation planning.
Nutritional, Chemical, and Functional Properties of Wholegrain Einkorn Pasta Through Cooking and Digestion: A Comparative Study with Wholegrain Durum Wheat Pasta
Authors: Mercatante Dario , Santoni Mattia , Nissen Lorenzo , Didos Spyros , Salvatori Giulia , D’Ambrosio Gianni Jan , Farneti Alice , Chiarello Elena , Casciano Flavia , Picone Gianfranco , Mouchtaropoulou Evangelia , Bordoni Alessandra , Danesi Francesca , Argiriou Anagnostis , Ayfantopoulou Georgia , Gianotti Andrea , Rodriguez-Estrada Maria Teresa
Published: January 2025

Despite growing interest in ancient wheat varieties, the functional and nutritional properties of einkorn (Triticum monococcum) in cereal-based foods remain not fully elucidated. This study examined the chemical composition and functional properties of wholegrain einkorn pasta through cooking and simulated gastrointestinal digestion, comparing it with conventional Triticum durum wheat pasta. While sharing similar macronutrient profiles, einkorn pasta demonstrated higher retention of key compounds including phenolics, tocopherols, and phytosterols throughout cooking and in vitro digestion. Notable findings include enhanced prebiotic activity specifically targeting bifidobacteria populations and preserved antioxidant capacity despite thermal processing. These results demonstrated einkorn’s potential as a functional food ingredient, suggesting its capacity to deliver enhanced nutritional benefits through its unique matrix properties. Our findings provide mechanistic insights into ancient grain functionality in modern food applications, with implications for developing nutritionally enhanced pasta products.
Plant-Based Burgers in the Spotlight: A Detailed Composition Evaluation and Comprehensive Discussion on Nutrient Adequacy
Authors: Biazotto Katia Regina , Xavier Ana Carolina Hadlich , de Mattos Rosane Ribeiro , Furlan Júnior Mendes , Wagner Roger , Bandoni Daniel Henrique , de Rosso Veridiana Vera
Published: January 2025

This study aimed to evaluate the nutritional profile of commercial plant-based burgers (PBBs) available in Brazil and to assess their suitability for fulfilling nutritional requirements. Seven PBBs were selected, based on the different protein sources used in the formulations. The proximate and mineral compositions were evaluated, and the fatty acid and amino acid profiles were determined. The protein contents ranged from 5.25 ± 0.37 to 13.55 ± 1.16 g/100 g in the PBBs made from quinoa and a mix of proteins, respectively. The studied PBBs can offer between 46 and 71% of the essential amino acid (EAA) requirements. In addition, the total amount of EAAs provided the nutritional requirements established by the FAO/UN for all of the PBBs, considering the 100 g portion intake. The total fat content in the PBBs ranged from 3.51 ± 0.11 to 12.74 ± 1.93 g/100 g. Linoleic acid and oleic acid were the major fatty acids in the three PBBs, while myristic acid was the major fatty acid in one PBB studied. This study revealed significant differences in the nutritional composition between PBBs marketed in Brazil. Additionally, the lack of regulation allows for considerable variation in their nutritional profiles, making it difficult to compare them with those of meat burgers.
MicroRNAs miR-148a-3p, miR-425-3p, and miR-20a-5p in Patients with IgA Nephropathy
Authors: Przybyciński Jarosław , Czerewaty Michał , Kwiatkowska Ewa , Dziedziejko Violetta , Safranow Krzysztof , Domański Leszek , Pawlik Andrzej
Published: January 2025

Background/Objectives: IgA nephropathy (IgAN) is one of the most common forms of glomerulonephritis leading to renal failure. MicroRNAs have been shown to play an important role in the pathogenesis and clinical course of IgA nephropathy; therefore, they offer the possibility of noninvasive diagnosis of this disease and have some value in predicting disease prognosis. This study aimed to evaluate the plasma levels of miR-148a-3p, miR-425-3p, and miR-20a-5p in patients with IgA nephropathy and their correlation with selected clinical parameters. Methods: This study included 44 patients with IgA nephropathy and 46 control subjects. Results: The results of our study indicated that in patients with IgA nephropathy, the increased plasma levels of miR-148a-3p and miR-425-3p correlated negatively with eGFR values. According to the Haas classification, plasma levels of miR-20a-5p were statistically significantly increased in patients with histopathological changes classified as Stages 3, 4, and 5 compared with patients with histopathological changes classified as Stages 1 and 2. Conclusions: The results of our study suggest the possible involvement of miR-148a-3p, miR-425-3p, and miR-20a-5p in the pathogenesis of IgA nephropathy.
Three Year Quantitative Study of Compassion Satisfaction and Fatigue Among Teachers and Educational Workers in Alberta, Canada
Authors: Kendrick Astrid Helene , Tay Mawuli Kofi , Shahin Mohammad Jahedul Hoque
Published: January 2025

Although the psychological workplace hazards of compassion satisfaction and compassion fatigue are a known risk factor for mental and emotional health distress for caring professionals, the extent of these hazards has not been explored in Alberta, Canada. Understanding and tracking the experiences of compassion fatigue and satisfaction of teachers and other educational workers was the primary focus of this three-year, cross-sectional research study. Methods: A multimethod, longitudinal study was conducted from June 2020 to May 2023. Data were collected at three different time points between 2020 and 2023 to explore the mental and emotional health of teachers and other educational workers, and the quantitative analysis of these data suggests that mental and emotional health distress is widespread and intensifying across Alberta. Findings: This paper discusses the extent of compassion fatigue and satisfaction across Alberta both at a general level and related to years of experience in the education field. Data analysis suggests worsening workplace wellbeing over time in both number and intensity, across gender and job role. Discussion: This article provides further evidence of the deepening crisis in education and contains some suggestions for policymakers, teacher educators, and system decision-makers invested in improving workplace wellbeing in educational settings.
Compost and Vermicompost as Substrates Enriched with Trichoderma asperellum for the Production of Basic Potato Seed in the Venezuelan Andes
Authors: Peña Haydee , Diánez Fernando , Ramírez Beatriz , Sulbarán José , Arias Karen , Huertas Victoria , Santos Mila
Published: January 2025

The agricultural sector faces significant pressure to meet the growing global demand for food while managing the planet’s limited natural resources. Addressing this challenge requires the strategic use of abundant materials and accessible biotechnologies that farmers can effectively implement. This study evaluated the effects of various substrate mixtures, including combinations of coconut fiber with compost or vermicompost (50:50 v/v). It also assessed the impact of heat treatment and inoculation with the antagonist Trichoderma asperellum on the production of basic potato seeds grown in 70 L plastic baskets. Statistical analysis revealed that the vermicompost-based mixture outperformed others, demonstrating superior biometric variables for potato plants. The treatment with sterilized vermicompost led to a 41% increase in seed weight, underscoring the beneficial effects of vermicompost. Correlation analysis indicated a positive relationship between the phosphorus content of the mixture and a negative relationship with the E4/E6 ratio—a parameter recognized as a reliable and easily measurable indicator of substrate quality, along with pH and electrical conductivity.
A Novel Evolutionary Deep Learning Approach for PM2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran
Authors: Kaveh Mehrdad , Mesgari Mohammad Saadi , Kaveh Masoud
Published: January 2025

Forecasting particulate matter with a diameter of 2.5 μm (PM2.5) is critical due to its significant effects on both human health and the environment. While ground-based pollution measurement stations provide highly accurate PM2.5 data, their limited number and geographic coverage present significant challenges. Recently, the use of aerosol optical depth (AOD) has emerged as a viable alternative for estimating PM2.5 levels, offering a broader spatial coverage and higher resolution. Concurrently, long short-term memory (LSTM) models have shown considerable promise in enhancing air quality predictions, often outperforming other prediction techniques. To address these challenges, this study leverages geographic information systems (GIS), remote sensing (RS), and a hybrid LSTM architecture to predict PM2.5 concentrations. Training LSTM models, however, is an NP-hard problem, with gradient-based methods facing limitations such as getting trapped in local minima, high computational costs, and the need for continuous objective functions. To overcome these issues, we propose integrating the novel orchard algorithm (OA) with LSTM to optimize air pollution forecasting. This paper utilizes meteorological data, topographical features, PM2.5 pollution levels, and satellite imagery from the city of Tehran. Data preparation processes include noise reduction, spatial interpolation, and addressing missing data. The performance of the proposed OA-LSTM model is compared to five advanced machine learning (ML) algorithms. The proposed OA-LSTM model achieved the lowest root mean square error (RMSE) value of 3.01 µg/m3 and the highest coefficient of determination (R2) value of 0.88, underscoring its effectiveness compared to other models. This paper employs a binary OA method for sensitivity analysis, optimizing feature selection by minimizing prediction error while retaining critical predictors through a penalty-based objective function. The generated maps reveal higher PM2.5 concentrations in autumn and winter compared to spring and summer, with northern and central areas showing the highest pollution levels.
Restriction of Zika Virus Replication in Human Monocyte-Derived Macrophages by Pro-Inflammatory (M1) Polarization
Authors: Pagani Isabel , Ghezzi Silvia , Aimola Giulia , Podini Paola , Genova Francesca , Vicenzi Elisa , Poli Guido
Published: January 2025

Zika virus (ZIKV), a member of the Flaviviridae family, is primarily transmitted through mosquito bites, but can also spread via sexual contact and from mother to fetus. While often asymptomatic, ZIKV can lead to severe neurological conditions, including microcephaly in fetuses and Guillain–Barré Syndrome in adults. ZIKV can infect placental macrophages and fetal microglia in vivo as well as human monocytes and monocyte-derived macrophages (MDMs) in vitro. Here, we observed that both human monocytes, and MDM particularly, supported ZIKV replication without evident cytopathicity, with virions accumulating in cytoplasmic vacuoles. We also investigated whether the cytokine-induced polarization of MDMs into M1 or M2 cells affected ZIKV replication. The stimulation of MDMs with pro-inflammatory cytokines (interferon-γ and tumor necrosis factor-α) polarized MDMs into M1 cells, significantly reducing ZIKV replication, akin to previous observations with a human immunodeficiency virus type-1 infection. In contrast, M2 polarization, induced by interleukin-4, did not affect ZIKV replication in MDMs. M1 polarization selectively reduced the expression of MERTK, a TAM family putative entry receptor, and increased the expression of several interferon-stimulated genes (ISGs) previously associated with the containment of ZIKV infection; of interest, ZIKV infection transiently boosted the expression of some ISGs in M1-MDMs. These findings suggest a dual mechanism of ZIKV restriction in M1-MDMs and highlight potential antiviral strategies targeting innate immune responses.