bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterizing Perception Deep Learning Algorithms and Applications for Vehicular Edge Computing
Authors: Feng Wang , Tang Sihai , Wang Shengze , He Ying , Chen Donger , Yang Qing , Fu Song
Published: January 2025

Vehicular edge computing relies on the computational capabilities of interconnected edge devices to manage incoming requests from vehicles. This offloading process enhances the speed and efficiency of data handling, ultimately boosting the safety, performance, and reliability of connected vehicles. While previous studies have concentrated on processor characteristics, they often overlook the significance of the connecting components. Limited memory and storage resources on edge devices pose challenges, particularly in the context of deep learning, where these limitations can significantly affect performance. The impact of memory contention has not been thoroughly explored, especially regarding perception-based tasks. In our analysis, we identified three distinct behaviors of memory contention, each interacting differently with other resources. Additionally, our investigation of Deep Neural Network (DNN) layers revealed that certain convolutional layers experienced computation time increases exceeding 2849%, while activation layers showed a rise of 1173.34%. Through our characterization efforts, we can model workload behavior on edge devices according to their configuration and the demands of the tasks. This allows us to quantify the effects of memory contention. To our knowledge, this study is the first to characterize the influence of memory on vehicular edge computational workloads, with a strong emphasis on memory dynamics and DNN layers.
CSGD-YOLO: A Corn Seed Germination Status Detection Model Based on YOLOv8n
Authors: Sun Wenbin , Xu Meihan , Xu Kang , Chen Dongquan , Wang Jianhua , Yang Ranbing , Chen Quanquan , Yang Songmei
Published: January 2025

Seed quality testing is crucial for ensuring food security and stability. To accurately detect the germination status of corn seeds during the paper medium germination test, this study proposes a corn seed germination status detection model based on YOLO v8n (CSGD-YOLO). Initially, to alleviate the complexity encountered in conventional models, a lightweight spatial pyramid pooling fast (L-SPPF) structure is engineered to enhance the representation of features. Simultaneously, a detection module dubbed Ghost_Detection, leveraging the GhostConv architecture, is devised to boost detection efficiency while simultaneously reducing parameter counts and computational overhead. Additionally, during the downsampling process of the backbone network, a downsampling module based on receptive field attention convolution (RFAConv) is designed to boost the model’s focus on areas of interest. This study further proposes a new module named C2f-UIB-iAFF based on the faster implementation of cross-stage partial bottleneck with two convolutions (C2f), universal inverted bottleneck (UIB), and iterative attention feature fusion (iAFF) to replace the original C2f in YOLOv8, streamlining model complexity and augmenting the feature fusion prowess of the residual structure. Experiments conducted on the collected corn seed germination dataset show that CSGD-YOLO requires only 1.91 M parameters and 5.21 G floating-point operations (FLOPs). The detection precision(P), recall(R), mAP0.5, and mAP0.50:0.95 achieved are 89.44%, 88.82%, 92.99%, and 80.38%. Compared with the YOLO v8n, CSGD-YOLO improves performance in terms of accuracy, model size, parameter number, and floating-point operation counts by 1.39, 1.43, 1.77, and 2.95 percentage points, respectively. Therefore, CSGD-YOLO outperforms existing mainstream target detection models in detection performance and model complexity, making it suitable for detecting corn seed germination status and providing a reference for rapid germination rate detection.
Potential of Cover Crop Use and Termination with a Roller-Crimper in a Strip-Till Silage Maize (Zea mays L.) Production System in the Central Valley of California
Authors: Willmott Robert , Valdez-Herrera Jennifer , Mitchell Jeffrey P. , Shrestha Anil
Published: January 2025

Abstract: The potential of terminating cover crops with a roller-crimper is of increasing interest. A two-year (2020/21 and 2021/22) study was conducted in Fresno, CA, USA. Five cover crop treatments (rye (Secale cereale L.) alone, ultra-high diversity mix, multiplex cover crop mix, fava bean (Vicia faba L.) + phacelia (Phacelia tanacetifolia Benth.), and rye + field pea (Pisum sativum L.) + purple vetch (Vicia americana Muhl. Ex Willd.)) were planted in November, roller-crimped in April, and silage maize (Zea mays L.) was strip-till planted in the residue in May. Cover crop kill, soil cover by residue, weed cover, amount of organic residue, and silage maize yield were recorded. The roller-crimper resulted in 95 to 100% kill of the cover crops. Soil cover at maize canopy closure (mid-July) was approximately 90% in the rye plots while it was 30 to 70% in the other treatments. The fava bean + phacelia cover crop disintegrated the most rapidly. Weed cover was <5% in all the treatments until maize canopy closure. The cover crops added 6.7 to 14 MT ha−1 of residue. Maize silage yield was similar across the treatments. Therefore, in this study, cover crops were successfully terminated by the roller-crimper, allowing successful strip-till establishment and production of silage maize.
Lin28b-let-7 Modulates mRNA Expression of GnRH1 Through Multiple Signaling Pathways Related to Glycolysis in GT1-7 Cells
Authors: Xie Yujing , Li Xin , Wang Meng , Chu Mingxing , Cao Guiling
Published: January 2025

Lin28b and let-7 miRNA regulate mammalian pubertal initiation and Gonadotropin-releasing hormone (GnRH) production. However, it remains unclear which signaling pathways Lin28b regulates to modulate GnRH production. In this study, the mRNA expression levels of Lin28b and let-7 in the pubertal and juvenile goat hypothalamus and pituitary gland were detected, and Lin28b expression in the pubertal hypothalamus decreased significantly compared with that in juvenile tissues. It was predicted that Lin28b might inhibit GnRH1 expression, which was verified in the GnRH-producing cell model GT1-7 cells. Lin28b inhibited GnRH1 expression and promoted Kiss1/Gpr54 signaling. The pyruvate content and the expression of Hif1a and Hk2, which were related to glycolysis, were also promoted by Lin28b overexpression. Additionally, 77 differentially expressed miRNAs (DEMIs) in Lin28b-overexpressed GT1-7 cells were identified. Bioinformatics analysis and mRNA expression of the target genes of DEMIs revealed that the MAPK and PI3K-AKT-mTOR signaling pathways were key pathways that involved the regulatory effect of Lin28b on GnRH. In GT1-7 cells, GnRH1 expression was suppressed by blocking mTOR signaling with rapamycin, which was rescued by Lin28b overexpression. These results indicate that Lin28b-let-7 regulates GnRH1 expression through several pathways, including the Kiss1/Gpr54, MAPK, and mTOR signaling pathways, which are all related to glucose metabolism and provide new insights into the molecular mechanism of the regulatory role of Lin28b on GnRH production.
The Evaluation of the Efficacy of a Novel Subunit Vaccine in the Prevention of Cryptosporidium parvum-Caused Diarrhoea in Neonatal Calves
Authors: Reijnders Martine , van Roosmalen Mark , Holtslag Hans , Arts Susan , Pel Suzanne , Dufé Divine , Kaashoek Marianne , Vertenten Geert , van Werven Tine , Sietsma Steven , Roy Christophe , Herman Nicolas
Published: January 2025

Cryptosporidium parvum (C. parvum)-caused calf diarrhoea (scours) is widespread and leads to calf mortality in cattle industries worldwide. A recent discovery of a glycopeptide epitope on the Cryptosporidium parasite recognized by a monoclonal antibody has led to the development of a new vaccine. It was designed for cows to pass on passive immunity to their neonatal calves. This vaccine has been demonstrated to be safe and efficacious in pre-clinical studies. In the process of marketing registration, two clinical studies were conducted with this vaccine on 16 commercial dairy and beef farms collecting data, assessed by the European Medicine Agency. In these studies, its effectiveness in the field was evaluated. The natural challenge and clinical disease caused by Cryptosporidium parvum in the calves in these studies was, however, not high enough to show a significant reduction of most of the clinical signs, although all trends were in favour of the vaccination groups. Nonetheless, the duration of the diarrhoea episodes of the dairy calves was significantly shorter in the vaccination group. Additionally, the levels of Gp40 antibodies in the blood of the calves was notably higher in the vaccination groups, demonstrating the principle of passive immunization. Overall, this vaccine, which can be used concurrently, non-mixed with Bovilis® Rotavec® Corona, introduces an additional approach to mitigate the impact of C. parvum infections in neonatal calves.
Whey Protein Hydrogels and Emulsion Gels with Anthocyanins and/or Goji Oil: Formation, Characterization and In Vitro Digestion Behavior
Authors: Seddiek Abdullah S. , Chen Kaiwen , Zhou Fanlin , Esther Muhindo Mwizerwa , Elbarbary Abdelaziz , Golshany Hazem , Uriho Angelo , Liang Li
Published: January 2025

Whey protein isolate (WPI) has functional properties such as gelation and emulsification. Emulsion gels combine the benefits of both emulsions and hydrogels. In this study, WPI hydrogels and emulsion gels were developed with goji oil (GO) as the oil phase by the inclusion of blueberry extract (BE) in the protein matrix. Heat-denatured WPI (hWPI) particles and emulsions were characterized in terms of size distribution, ζ-potential, interfacial protein, and anthocyanin partition. The inclusion of anthocyanins-rich blueberry extract led to the aggregation of hWPI particles, but it also increased the interfacial protein of 10% goji oil emulsions to 20% and decreased their size distribution to 120 and 325 nm. WPI hydrogels and emulsion gels were analyzed in terms of their water-holding capacity, which decreased from 98% to 82% with the addition of blueberry extract and goji oil. Syneresis, rheological, and morphological characteristics were also analyzed. The gelation time of hWPI particles and emulsions was shortened from 24 h to 12 h when incorporating blueberry extract to form a dense network. The network was the most homogeneous and densest in the presence of 3% blueberry extract and 5% goji oil. The co-inclusion of blueberry extract and goji oil increased the syneresis during the freeze–thaw cycles, with the values rising from 13% to 36% for 5% BE hydrogel and BE-containing emulsion gels after the first cycle. All WPI hydrogels and emulsion gels exhibit predominantly elastic behavior. Moreover, anthocyanin release, antioxidant activity, and the fatty acid composition profile were also analyzed during in vitro digestion. Soluble and free anthocyanins in the digested medium were reduced with the goji oil content but increased with the blueberry extract content. The stability of polyunsaturated fatty acids in the digested medium was improved by the addition of blueberry extract. The antioxidant activity of the digested medium increased with the content of blueberry extract but decreased with the content of goji oil. The ABTS∙+ scavenging capacities decreased from 63% to 49% by increasing the content of GO from 0% to 10% and they increased from 48% to 57% for 5% BE and 10% GO emulsion gels as the BE content increased from 0% to 5% after 6 h of digestion. The data gathered should provide valuable insights for future efforts to co-encapsulate hydrophilic and hydrophobic agents, thereby enhancing their stability, bioavailability, and functional properties for potential applications in food industries.
Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization
Authors: Khaseeb Jomana Yousef , Keshk Arabi , Youssef Anas
Published: January 2025

Feature selection is a preprocessing step for various classification tasks. Its objective is to identify the most optimal features in a dataset by eliminating redundant data while preserving the highest possible classification accuracy. Three improved binary Grey Wolf Optimization (GWO) approaches are proposed in this paper to optimize the feature selection process by enhancing the feature selection accuracy while selecting the least possible number of features. Each approach combines GWO with Particle Swarm Optimization (PSO) by implementing GWO followed by PSO. Afterwards, each approach manipulates the solutions obtained by both algorithms in a different way. The objective of this combination is to overcome the GWO stuck-in-local-optima problem that might occur by leveraging the PSO-wide search space exploration ability on the solutions obtained by GWO. Both S-shaped and V-shaped binary transfer functions were used to convert the continuous solutions obtained from each proposed approach to their corresponding binary versions. The three proposed approaches were evaluated using nine small-instance, high-dimensional, cancer-related human gene expression datasets. A set of comparisons were made against the original binary versions of both GWO and PSO algorithms and against eight state-of-the-art feature selection binary optimizers in addition to one of the recent binary optimizers that combines PSO with GWO. The evaluation results showed that one of the proposed S-shaped and V-shaped approaches achieved 0.9 and 0.95 average classification accuracy, respectively, while selecting the fewest number of features. The results also confirmed the superiority of one of the proposed V-shaped approaches when compared with the original binary GWO and PSO approaches. Moreover, the results confirmed the superiority, in most of the datasets, of one of the three approaches over the state-of-the-art approaches. Finally, the results revealed that the best approach in terms of classification accuracy, fitness value, and number of selected features had the highest computational complexity.
Investigation for Possible Association of the Topside and Bottomside Ionospheric Irregularities over the Midlatitude Ionosphere
Authors: Paul Krishnendu Sekhar , Haralambous Haris
Published: January 2025

The present study investigates the characteristics of ionospheric irregularities at middle latitudes by examining the association between spread F (SF) events detected by Digisondes and medium-scale travelling ionospheric disturbances (MSTIDs) detected by GNSS with a special emphasis on the coupling with topside irregularities observed by Swarm satellites based on in situ electron density (Ne) measurements. We analyzed SF events over the European midlatitude region from 2015 to 2017, over six Digisonde stations coinciding with Swarm satellite overpasses. Swarm latitudinal Ne profiles were used to identify topside irregularities, while GNSS d-TEC and ROTI maps were used to track MSTIDs and irregularities, respectively. Based on ten selected cases demonstrating concurrent SF and topside irregularities, our findings suggest a strong association between SF in the bottomside ionosphere and fluctuations in topside Ne.
Machine Learning-Based Lithium Battery State of Health Prediction Research
Authors: Li Kun , Chen Xinling
Published: January 2025

To address the problem of predicting the state of health (SOH) of lithium-ion batteries, this study develops three models optimized using the particle swarm optimization (PSO) algorithm, including the long short-term memory (LSTM) network, convolutional neural network (CNN), and support vector regression (SVR), for accurate SOH estimation. Key features were extracted by analyzing the temperature, voltage, and current curves of the battery, and health factors with high correlation to SOH were selected as model inputs using the Pearson correlation coefficient. The PSO algorithm was employed to optimize model parameters, resulting in the construction of three predictive models: PSO-LSTM, PSO-CNN, and PSO-SVR. The models were validated using the NASA PCoE battery aging datasets B0005, B0006, and B0007, with prediction accuracy evaluated based on Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Coefficient of Determination (R2). Results indicate that the optimized models achieved significant improvements in prediction accuracy, with RMSE and MAE reduced by over 0.5%, a minimum reduction of 38% in MAPE, and R2 exceeding 0.8, demonstrating strong fitting capabilities and validating the effectiveness of the PSO strategy. Among the three models, PSO-LSTM exhibited the best predictive performance, achieving a minimum MAE of 0.67%, RMSE of 0.94%, MAPE of 45.82%, and R2 as high as 0.9298 across the three datasets. These findings suggest that the PSO-LSTM model provides a robust reference for accurate SOH prediction of lithium-ion batteries and shows promising potential for practical applications.
Leveraging Retrieval-Augmented Generation for Swahili Language Conversation Systems
Authors: Ndimbo Edmund V. , Luo Qin , Fernando Gimo C. , Yang Xu , Wang Bang
Published: January 2025

A conversational system is an artificial intelligence application designed to interact with users in natural language, providing accurate and contextually relevant responses. Building such systems for low-resource languages like Swahili presents significant challenges due to the limited availability of large-scale training datasets. This paper proposes a Retrieval-Augmented Generation-based system to address these challenges and improve the quality of Swahili conversational AI. The system leverages fine-tuning, where models are trained on available Swahili data, combined with external knowledge retrieval to enhance response accuracy and fluency. Four models—mT5, GPT-2, mBART, and GPT-Neo—were evaluated using metrics such as BLEU, METEOR, Query Performance, and inference time. Results show that Retrieval-Augmented Generation consistently outperforms fine-tuning alone, particularly in generating detailed and contextually appropriate responses. Among the tested models, mT5 with Retrieval-Augmented Generation demonstrated the best performance, achieving a BLEU score of 56.88%, a METEOR score of 72.72%, and a Query Performance score of 84.34%, while maintaining relevance and fluency. Although Retrieval-Augmented Generation introduces slightly longer response times, its ability to significantly improve response quality makes it an effective approach for Swahili conversational systems. This study highlights the potential of Retrieval-Augmented Generation to advance conversational AI for Swahili and other low-resource languages, with future work focusing on optimizing efficiency and exploring multilingual applications.
The Impact of Advanced Footwear Technology on the Performance and Running Biomechanics of Mountain Runners
Authors: Corbí-Santamaría Pedro , Gil-Calvo Marina , Herrero-Molleda Alba , García-López Juan , Boullosa Daniel , García-Tormo José Vicente
Published: January 2025

In recent years, advanced footwear technology (AFT) has been shown to improve performance in long-distance road running by altering biomechanics and perceived comfort. This type of footwear is now being marketed for mountain running, although its effects in such races remain unevaluated. This study aimed to examine the impact of AFT on performance, biomechanics, and perceived comfort during a simulated mountain running event. Twelve trained mountain runners participated in a 3-day experiment, with a 7-day recovery between sessions. On the first day, a maximal aerobic speed test assessed the runners’ performance levels. On the second day, participants familiarized themselves with a 5.19 km mountain circuit and comfort scale. On the third day, they completed two time trials on the same circuit, separated by 30 min of passive recovery, using conventional and AFT shoes in a randomized order. Physiological and biomechanical variables were recorded, including body mass, blood lactate, running biomechanics, vertical stiffness, shoe comfort, and rating of perceived exertion (RPE). The findings indicate that AFT does not improve performance or physiological responses during a simulated mountain race, regardless of segment (uphill, downhill, or mixed). However, AFT significantly alters running biomechanics, reducing step frequency and increasing the vertical oscillation of the center of gravity, especially in uphill and downhill sections. While overall comfort remained unchanged, specific differences were observed with AFT. Coaches and practitioners should consider these findings when using AFT in mountain running training or competition.
Optimised Extraction and Purification of Dual-Function Cosmetic-Grade Phycocyanin and Allophycocyanin from Dried Arthrospira platensis Biomass Using Conventional Methods
Authors: Krakauskaitė Ugnė , Aboobacker Shahana , Kitrytė-Syrpa Vaida , Syrpas Michail
Published: January 2025

Arthospira platensis is a filamentous cyanobacterium considered an important source of phycobiliproteins (PBP), a class of water-soluble pigments with a wide range of applications. Although several extraction and purification techniques of PBP have been reported, there is still a need for strategies that achieve a balance between simplicity, cost-effectiveness, and scalability. To address this need, this study systematically evaluated conventional extraction methods—homogenisation, freeze–thaw cycles, and maceration. Maceration showed the best balance between yield purity and recovery among the tested techniques, and under optimal conditions (three cycles, 2 h/cycle, 0.1 M phosphate buffer), 55.9 mg/g of biomass of phycocyanin (PC) and 24.9 mg/g of biomass of allophycocyanin (APC) with notable antioxidant capacity (Folin-Ciocalteu’s and ABTS●+ assays) were yielded. Among the tested purification techniques, ammonium sulphate fractionation achieved a purity of 2.3 with recoveries of 92.9% and 79.9% for PC and APC, respectively, while purification with 0.5% activated carbon resulted in an extract purity of 2.5 and recoveries of 90.9% (PC) and 87.2% (APC). The suggested procedures could be considered a fast and cost-effective way to obtain cosmetic-grade PBP, thus offering an accessible solution for industries prioritising sustainable and economically viable production pipelines.
Modeling Absorbed Energy in Microwave Range for Nanocomposite Hot Melts Containing Metallic Additives
Authors: Damian Radu F. , Ciobanu Romeo Cristian
Published: January 2025

This paper describes the simulation of the S (scattering)-parameters and absorbed energy for polymeric nanocomposites with metallic insertions (iron and aluminum, with two particle dimensions). The considered frequency domain, 0.1–3 GHz, is specific for a wide range of applications in microwave technologies. The actual limitations of electromagnetic simulations are described, along with an application related to the Nicolson–Ross–Weir procedure in infinite media, which opens new perspectives in nanocomposite electromagnetic modeling. It was demonstrated that, due to a higher conductivity, nanocomposites with Al particles can absorb a larger amount of energy compared to Fe particles within composite materials, at both insertion dimensions. At higher frequencies, the power loss density increases for both metals. The significant reduction in transmission, linked to a minimal reflection, verifies that for composites with added metallic powder, microwave energy is extensively absorbed by the materials, particularly at frequencies above 1.5 GHz, confirming their potential functionality as hot melts for advanced reversible bonding technologies.
Evaluation of the Suitability of Urban Underground Space Development Based on Multi-Criteria Decision-Making and Geographic Information Systems
Authors: Zhang Peixing , Jin Tianlu , Wang Meng , Zhou Na , Jia Xueting
Published: January 2025

The rational development of urban underground space resources (UUSRs) is especially crucial for alleviating “urban diseases”, and it is of great significance for exploring the appropriateness of urban underground space (UUS) development under multiple constraints for the rational use of UUSRs. This research selects the UUS in Nantong City, Jiangsu Province, as the research object, and establishes an evaluation index system for the suitability of UUS development under the perspective of sustainable development, including terrain and geomorphology, engineering geological environment, hydrogeological environment, sensitive geological factors, the regional development level, and the distribution of ecological reserve, as well as other multi-source heterogeneous data. On this basis, the relationship between the appropriateness of underground space development and the utilization and various factors was studied. We constructed a comprehensive evaluation model for the suitability of UUS using the Analytic Hierarchy Process (AHP) and the multi-objective linear weighting method. The results of the study show that ecological protection constraints and geological hazards have a greater impact on the evaluation of suitability. The suitable and secondarily suitable areas for the development of the underground space in Nantong City account for 14.74% and 30.66% of the total area, respectively. These areas are mainly distributed in Rugao City and Chongchuan District. The less suitable and unsuitable areas account for 37.17% and 17.44%, with a significant concentration in near-sea areas.
Skull Impact on Photoacoustic Imaging of Multi-Layered Brain Tissues with Embedded Blood Vessel Under Different Optical Source Types: Modeling and Simulation
Authors: Yang Xi , Chai Chengpeng , Chen Yun-Hsuan , Sawan Mohamad
Published: January 2025

Skulls with high optical scattering and acoustic attenuation are a great challenge for photoacoustic imaging for human beings. To explore and improve photoacoustic generation and propagation, we conducted the photoacoustic simulation and image reconstruction of the multi-layer brain model with an embedded blood vessel under different optical source types. Based on the optical simulation results under different types of optical sources, we explored the characteristics of reconstructed images obtained from acoustic simulations with and without skull conditions. Specifically, we focused on the detection of blood vessels and evaluated the image reconstruction features, morphological characteristics, and intensity of variations in the target vessels using optical and acoustic simulations. The results showed that under the initial PA signals, the types of optical source types corresponding to the strongest and weakest photoacoustic signals at different positions within the target region were consistent, while the optical source types were different in the reconstructed images. This study revealed the characteristics of acoustic signal transmission with and without skull conditions and its impact on image reconstruction. It further provides a theoretical basis for the selection of optical sources.
Reverse Shoulder Arthroplasty Baseplate Stability Is Affected by Bone Density and the Type and Amount of Augmentation
Authors: Ritter Daniel , Raiss Patric , Denard Patrick J. , Werner Brian C. , Kistler Manuel , Lesnicar Celina , van der Merwe Micheal , Müller Peter E. , Woiczinski Matthias , Wijdicks Coen A. , Bachmaier Samuel
Published: January 2025

Objective: This study evaluated the effects of bony increased offset (BIO) and metallic augments (MAs) on primary reverse shoulder arthroplasty (RSA) baseplate stability in cadaveric specimens with variable bone densities. Methods: Thirty cadaveric specimens were analyzed in an imaging and biomechanical investigation. Computed tomography (CT) scans allowed for preoperative RSA planning and bone density analysis. Three correction methods of the glenoid were used: (1) corrective reaming with a standard baseplate, which served as the reference group (n = 10); (2) MA-RSA (n = 10); and (3) angled BIO-RSA (n = 10). Each augment group consisted of 10° (n = 5) and 20° (n = 5) corrections. Biomechanical testing included cyclic loading in an articulating setup, with optical pre- and post-cyclic micromotion measurements in a rocking horse setup. Results: There were no differences in bone density between groups based on CT scans (p > 0.126). The BIO-RSA group had higher variability in micromotion compared to the MA-RSA and reference groups (p = 0.013), and increased total micromotion compared to the reference group (p = 0.039). Both augmentations using 20° corrections had increased variance in rotational stability compared to the reference group (p = 0.043). Micromotion correlated with the subchondral bone density in the BIO-RSA group (r = −0.63, p = 0.036), but not in the MA-RSA (p > 0.178) or reference (p > 0.117) groups. Conclusions: Time-zero baseplate implant fixation is more variable with BIO-RSA and correlates with bone density. Corrections of 20° with either augmentation approach increase variability in rotational micromotion. The preoperative quantification of bone density may be useful before utilizing 20° of correction, especially when adding a bone graft in BIO-RSAs.
Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics
Authors: Wang Jihan , Zhang Zhengxiang , Wang Yangyang
Published: January 2025

Cancer’s heterogeneity presents significant challenges in accurate diagnosis and effective treatment, including the complexity of identifying tumor subtypes and their diverse biological behaviors. This review examines how feature selection techniques address these challenges by improving the interpretability and performance of machine learning (ML) models in high-dimensional datasets. Feature selection methods—such as filter, wrapper, and embedded techniques—play a critical role in enhancing the precision of cancer diagnostics by identifying relevant biomarkers. The integration of multi-omics data and ML algorithms facilitates a more comprehensive understanding of tumor heterogeneity, advancing both diagnostics and personalized therapies. However, challenges such as ensuring data quality, mitigating overfitting, and addressing scalability remain critical limitations of these methods. Artificial intelligence (AI)-powered feature selection offers promising solutions to these issues by automating and refining the feature extraction process. This review highlights the transformative potential of these approaches while emphasizing future directions, including the incorporation of deep learning (DL) models and integrative multi-omics strategies for more robust and reproducible findings.
Fully Inkjet-Printed Flexible Graphene–Prussian Blue Platform for Electrochemical Biosensing
Authors: Boček Željka , Zubak Marko , Kassal Petar
Published: January 2025

Prussian Blue (PB) is commonly incorporated into screen-printed enzymatic devices since it enables the determination of the enzymatically produced hydrogen peroxide at low potentials. Inkjet printing is gaining popularity in the development of electrochemical sensors as a substitute for screen printing. This work presents a fully inkjet-printed graphene–Prussian Blue platform, which can be paired with oxidase enzymes to prepare a biosensor of choice. The graphene electrode was inkjet-printed on a flexible polyimide substrate and then thermally and photonically treated with intense pulsed light, followed by inkjet printing of a PB nanoparticle suspension. The optimization of post-printing treatment and electrode deposition conditions was performed to yield a platform with minimal sheet resistance and peak potential differences. A thorough study of PB deposition was conducted: the fully inkjet-printed system was compared against sensors with PB deposited chemically or by drop casting the PB suspension on different kinds of carbon electrodes (glassy carbon, commercial screen-printed, and in-house inkjet-printed electrodes). For hydrogen peroxide detection, the fully inkjet-printed platform exhibits excellent sensitivity, a wider linear range, better linearity, and greater stability towards higher concentrations of peroxide than the other tested electrodes. Finally, lactate oxidase was immobilized in a chitosan matrix, and the prepared biosensor exhibited analytical performance comparable to other lactate sensors found in the literature in a wide, physiologically relevant linear range for measuring lactate concentration in sweat. The development of mediator-modified electrodes with a single fabrication technology, as demonstrated here, paves the way for the scalable production of low-cost, wearable, and flexible biosensors.
Motor Imagery EEG Classification Based on Multi-Domain Feature Rotation and Stacking Ensemble
Authors: Zhu Xianglong , Meng Ming , Yan Zewen , Luo Zhizeng
Published: January 2025

Background: Decoding motor intentions from electroencephalogram (EEG) signals is a critical component of motor imagery-based brain–computer interface (MI–BCIs). In traditional EEG signal classification, effectively utilizing the valuable information contained within the electroencephalogram is crucial. Objectives: To further optimize the use of information from various domains, we propose a novel framework based on multi-domain feature rotation transformation and stacking ensemble for classifying MI tasks. Methods: Initially, we extract the features of Time Domain, Frequency domain, Time-Frequency domain, and Spatial Domain from the EEG signals, and perform feature selection for each domain to identify significant features that possess strong discriminative capacity. Subsequently, local rotation transformations are applied to the significant feature set to generate a rotated feature set, enhancing the representational capacity of the features. Next, the rotated features were fused with the original significant features from each domain to obtain composite features for each domain. Finally, we employ a stacking ensemble approach, where the prediction results of base classifiers corresponding to different domain features and the set of significant features undergo linear discriminant analysis for dimensionality reduction, yielding discriminative feature integration as input for the meta-classifier for classification. Results: The proposed method achieves average classification accuracies of 92.92%, 89.13%, and 86.26% on the BCI Competition III Dataset IVa, BCI Competition IV Dataset I, and BCI Competition IV Dataset 2a, respectively. Conclusions: Experimental results show that the method proposed in this paper outperforms several existing MI classification methods, such as the Common Time-Frequency-Spatial Patterns and the Selective Extract of the Multi-View Time-Frequency Decomposed Spatial, in terms of classification accuracy and robustness.
Analysis of the LCA-Emergy and Carbon Emissions Sustainability Assessment of a Building System with Coupled Energy Storage Modules
Authors: Zhang Junxue , Pan Zhihong , Li Yingnan
Published: January 2025

This paper uses a perspective of life cycle ecological emergy and carbon footprint to quantitatively verify the sustainable status of building systems; it also employs a neural network model to predict and analyze their long-term ecological and carbon footprint effects. The research results show that the stages of building material production and building operation play a major role in the emergy and carbon emissions of the entire building system, and their changes show an inverse trend. As the building system operates, the greater the system loss and consumption, the environmental load rate (ELR) will gradually increase, and the sustainability parameter (ESI) will also gradually decrease. The integration of energy storage modules significantly improves the sustainability of the building system. When calculated over five time periods (5 years, 10 years, 20 years, 30 years, and 50 years), the overall carbon emission reduction rates after adding the energy storage module are 39.4%, 33.6%, 39.2%, 42.5%, and 38.8% respectively, demonstrating that the energy storage module has a significant positive effect on the sustainability of the building system. This study reveals the energy efficiency and environmental impact of the building system throughout its entire life cycle, providing a scientific basis for optimizing building design.
Research on the Effect of Geometric Parameters on the Stress Concentration Factor of Multi-Planar KK-Joints and Carbon Fiber-Reinforced Polymer Wrapping Rehabilitation with Numerical Simulation
Authors: Shi Yuhao , Deng Peng , Zhao Shiqi , Liu Yan , Zhu Zhongyi , Chen Yunkai
Published: January 2025

The focus of this paper is on estimating the stress concentration factor of circular hollow section KK-joints with different geometric parameters and subsequently assessing the effectiveness of carbon fiber-reinforced polymer (CFRP) wrapping for repairing joints with cracks. Different geometric parameters, such as θ (brace inclination angle), γ (the ratio of the outer diameter to the wall thickness of the chord), and τ (the thickness ratio of the brace to the chord), were studied to investigate changes in stress concentration using numerical simulation. The results indicated that the stress concentration factor was most sensitive to changes in θ, followed by γ. Subsequently, the effect of crack length and depth was analyzed to simulate cracks in joints subjected to reciprocating load. The results showed that changing D from T/16 to T/2 (where T is the thickness of the chord) can cause more stress concentration, with an average of 8.37%. Next, damaged joints were wrapped in carbon fiber-reinforced polymer as a repair. Analysis of the effects of different layers and directions of polymer wrap revealed that even six layers of wrapping effectively reduced the stress concentration compared to the initial model. Finally, based on the results of parametric analysis and nonlinear fitting, a calculation formula for the stress concentration factor suitable for KK-joints under axial loads is proposed.
UBR5 in Tumor Biology: Exploring Mechanisms of Immune Regulation and Possible Therapeutic Implications in MPNST
Authors: Odhiambo Diana Akinyi , Fan Selina , Hirbe Angela C.
Published: January 2025

Malignant peripheral nerve sheath tumor (MPNST) is a rare but aggressive soft-tissue sarcoma characterized by poor response to therapy. The primary treatment remains surgical resection with negative margins. Nonetheless, in the setting of neurofibromatosis type 1 (NF1), the five-year survival rate is at 20–50%, with recurrence occurring in up to 50% of individuals. For patients with metastatic and unresectable disease, current treatment options include cytotoxic chemotherapy, which offers minimal benefit, and most patients die within five years of diagnosis. Despite advances in targeted therapy focusing on inhibiting Ras signaling and its downstream effectors, clinical trials report minimal clinical benefit, highlighting the need to explore alternative pathways in MPNST pathogenesis. Here, we discuss the role of the E3 ubiquitin ligase, UBR5, in cancer progression and immune modulation across various malignancies, including breast, lung, and ovarian cancer. We focus on mechanisms by which UBR5 contributes to tumorigenesis, focusing on its influence on tumor microenvironment and immune modulation. Additionally, we explore UBR5’s roles in normal tissue function, DNA damage response, metastasis, and therapeutic resistance, illustrating its multifaceted contribution to cancer biology. We discuss evidence implicating UBR5 in immune evasion and highlight its potential as a therapeutic target to enhance the efficacy of immune checkpoint blockade (ICB) therapy in MPNST, a tumor typically characterized by an immune cold microenvironment. We outline current immune-based strategies and challenges in MPNST management, ongoing efforts to shift the immune landscape in MPNST, and ultimately, we suggest that targeting UBR5 could be a novel strategy to potentiate ICB therapy-mediated anti-tumor immune response and clinical outcomes, particularly in MPNST patients with inoperable or metastatic disease.
SSTR2-Targeted Theranostics in Hepatocellular Carcinoma
Authors: Momeny Majid , AghaAmiri Solmaz , Hernandez Vargas Servando , Acidi Belkacem , Ghosh Sukhen C. , Bateman Tyler M. , Adams Jack T. , Khalaj Vahid , Kaseb Ahmed O. , Tran Cao Hop S. , Azhdarinia Ali
Published: January 2025

Background: While the clinical use of radiolabeled somatostatin analogs is well established in neuroendocrine tumors, there is growing interest in expanding their application to other somatostatin receptor 2 (SSTR2)-expressing cancers. This study investigates the potential utility of SSTR2-targeted theranostics in hepatocellular carcinoma (HCC). Methods: SSTR2 expression in HCC cell lines and clinical samples was evaluated using qRT-PCR, Western blot analysis, and a public dataset. 67Ga-DOTATATE uptake was measured, 177Lu-DOTATATE cytotoxicity was assessed, and 68Ga-DOTATATE tumor targeting was evaluated in HCC animal models and a patient via PET/CT imaging. Results: SSTR2 expression was confirmed in HCC cell lines and clinical samples. Radioligand uptake studies demonstrated SSTR2-mediated 67Ga-DOTATATE uptake. 177Lu-DOTATATE treatment reduced cell proliferation and enhanced the anti-tumor efficacy of the multikinase inhibitor sorafenib. 68Ga-DOTATATE PET/CT scans successfully identified tumors in HCC animal models and spinal metastases in a patient with HCC. Conclusion: These findings provide evidence that SSTR2-based theranostics could have significant implications for the detection and treatment of HCC.
A Comprehensive Analysis of Neoadjuvant Chemotherapy in Breast Cancer: Adverse Events, Clinical Response Rates, and Surgical and Pathological Outcomes—Bozyaka Experience
Authors: Yılmaz Cengiz , Zengel Baha , Üreyen Orhan , Adıbelli Zehra Hilal , Taşlı Funda , Yılmaz Hasan Taylan , Özdemir Özlem , Kocatepe Çavdar Demet , Mollamehmetoğlu Hülya , Çakıroğlu Umut , İmren Yaşar , Yakan Savaş , İlhan Enver
Published: January 2025

Abstract: Objectives: To evaluate the neoadjuvant chemotherapy (NACTx) process in breast cancer (BC), its significant treatment-related adverse events (trAEs), tumor clinical response rates, and surgical and pathological outcomes, and to analyze factors influencing cavity shaving and axillary lymph node dissection (ALND) following sentinel lymph node biopsy (SLNB). Methods: A comprehensive retrospective study was conducted at a single center on patients who received NACTx for BC between 2015 and 2021. Results: Medical records of 242 patients were reviewed. Approximately one-fifth encountered grade ≥ 3 trAEs (21.5%), leading 3.3% to discontinue chemotherapy. Anthracycline cardiotoxicity (2.2%) caused one death (mortality rate = 0.4%). For clinical response and surgical and pathological outcomes, 229 patients were eligible. Clinical progression occurred in 3.9% of the patients (14% in triple-negative BC, p = 0.004). Breast-conserving surgery (BCS) was performed in 55% of the patients. There was no significant difference between the type of breast surgery (BCS vs. mastectomy) and molecular subtype, histology, tumor size, or tumor’s pathological response degree. Cavity shaving was required in one-fifth of the patients who underwent BCS (n = 134) due to an invasive tumor at the surgical margin (SM). Tumor histology (invasive ductal vs. invasive lobular carcinoma; OR: 4.962, 95% CI 1.007–24.441, p = 0.049) and tumor SUVMax value (OR: 0.866, 95% CI 0.755–0.993, p = 0.039) had significant independent efficacy on SM positivity. Initially, 75% underwent SLNB, but nearly half of them needed ALND. ALND rates were significantly higher in the luminal A and LB-HER2(−) groups (87% vs. 69%) than in the HER2(+) and TN groups (43% to 50%) (p = 0.001). All luminal A patients and those with lobular histology required ALND after SLNB, but no patients in the HER2-enriched group required ALND. ER positivity and higher PR expression levels were associated with an increased need for ALND after SLNB, whereas HER2 positivity and higher SUVMax values of LN(s) were associated with a significantly reduced need for ALND. About 27% of the patients achieved overall pCR. No pCR was achieved in the LA group. Conclusions: The BC NACTx process requires close monitoring due to severe AEs and disease progression. NACTx decisions must be made on experienced multidisciplinary tumor boards, considering tumor characteristics and expected targets.
New Promising Steroidal Aromatase Inhibitors with Multi-Target Action on Estrogen and Androgen Receptors for Breast Cancer Treatment
Authors: Amaral Cristina , Almeida Cristina F. , Valente Maria João , Varela Carla L. , Costa Saul C. , Roleira Fernanda M. F. , Tavares-da-Silva Elisiário , Vinggaard Anne Marie , Teixeira Natércia , Correia-da-Silva Georgina
Published: January 2025

Background/Objectives: Endocrine therapies that comprise anti-estrogens and aromatase inhibitors (AIs) are the standard treatment for estrogen receptor-positive (ER+) (Luminal A) breast cancer—the most prevalent subtype. However, the emergence of resistance restricts their success by causing tumor relapse and re-growth, which demands a switch towards other therapeutic approaches in order to minimize or overcome resistance. Indeed, this clinical limitation highlights the search for new molecules to improve cancer treatment. Recently, strategies that address multiple targets have been emerging, and multi-target drugs have the potential to become the future anti-cancer molecules. Our group has been searching for new multi-target compounds, and as part of this, our study aims to understand the anti-cancer and multi-target potential of three new steroidal aromatase inhibitors (AIs): 7α-methylandrost-4-en-17-one (6), 7α-methylandrost-4-ene-3,17-dione (10a) and androsta-4,9(11)-diene-3,17-dione (13). Methods: Their in vitro actions and molecular mechanisms were elucidated in a sensitive ER+ aromatase-overexpressing breast cancer cell line, MCF-7aro cells, as well as in an AI-resistant ER+ breast cancer cell line, LTEDaro cells. Results: All the new AIs (10 µM) prevented the proliferation of MCF-7aro cells by arresting cell cycle progression. Interestingly, all AIs (10 µM) act as androgen receptor (AR) agonists and modulate ER levels, synthesis and signaling to induce the apoptosis of ER+ breast cancer cells. Additionally, these new AIs (10 µM) also re-sensitize resistant cells by promoting apoptosis, offering a therapeutic benefit. Conclusions: Overall, new steroidal polypharmacological compounds have been discovered that, by acting as AIs, ER modulators and AR agonists, impair ER+ breast cancer cell growth. Overall, this study is a breakthrough on drug discovery as it presents new molecules with appealing anti-cancer properties and multi-target action for the treatment of ER+ breast cancer.
Recent Advances in the Synthesis of Substituted Polyacetylenes
Authors: Pisetsky Wladislaw , Müller Thomas J. J.
Published: January 2025

Recent developments in the synthesis of substituted polyacetylenes have considerably benefitted from advancements in organometallic catalysis; however, most important developments rely on the advent of Rh-catalyzed living polymerizations. The latter not only allow the tailoring of well-defined degrees of polymerization with low and narrow polydispersity but also enable access to stereochemical well-defined cis-transoidal polymers with a helical structure. These novel polymers open new avenues for application in photonics and electronics. Rh-catalyzed living polymerizations are mild and concise metal-catalyzed polymer syntheses that not only allow for the decoration of sidechains with multiple functionalities, including chiral units, but also enable enantioselective induction of helical chirality, memory of chirality, well-defined copolymerization, and end-group functionalization at both termini. This review summarizes recent developments in metal-catalyzed syntheses of substituted polyacetylenes, with a special focus on Rh-catalyzed living polymerizations.