bluuebunny/crossref_metadata_2025 huggingface dataset:
Tales of Brand Admiration: Insight from Automotive Industry in Indonesia
Authors: Ramaditya Muhammad , Manalu Erwin , Hadi Abdul Razak Abdul , Syah Donny Oktavian , Lusiana Dewi
Published: December 2024

Purpose – This research aims to understand how to build brand admiration and the antecedent to its impact of consumer behavior in the Automotive Industries. This study is conducted in Indonesia because of its market size, increasing purchasing power, and low car ownership, which makes an attractive automotive marketplace. 
Methodology – The design is quantitative used a questionnaire was administered to 510 consumers in Indonesia. The data collected were analyzed using partial least square structural equation modeling.
Findings – This study finds that an automotive company will have an admired brand if they are able to deliver customer enablement, customer inspiration, and customer excitement. In addition to offering alternate theories for brand management, this study serves as a foundation for further research aimed at enhancing the body of knowledge on brand admiration. This research is expected to provide insight into the importance of making their brand admired, and how to achieve it.
Originality – This study also contributes a new perspective around branding. Although there are a lot of benefits that an admired brand can get, the previous study on this topic is very limited, especially in emerging markets such as Indonesia.
Gambaran Personal Hygiene Pada Anak Autis
Authors: Pauwah Hermawansah , Amalia Maya , Apriani Nuni
Published: December 2024

Autisme adalah kondisi yang dialami seorang anak sejak lahir atau masa balita, di manaanak kesulitan membangun hubungan sosial dan komunikasi secara normal, sehinggadapat memengaruhi kemandiriannya dalam memenuhi kebutuhan kebersihan pribadiatau personal hygiene. Penelitian ini bertujuan untuk mengetahui gambaran personalhygiene pada anak autis di SLB Autisma Bunda Bening Selakshahati Cileunyi denganrentang usia 6 sd 12 tahun. Penelitian ini menggunakan metode deskriptif kuantitatifyang dilakukan dari Juni hingga Juli 2023. Populasi penelitian yaitu anak autis di SLBBunda Bening Selakshahati Cileunyi 70 anal. Pemilihan responden menggunakan teknikpurposive sampling dengan kriteria inklusi dan eksklusi sehingga responden yangdiambil hanya 64 anak. Alat ukur yang digunakan adalah lembar observasi perilakupersonal hygiene. Penelitian ini menggunakan analisis data univariat. Hasil penelitianmenunjukkan mayoritas responden dapat melakukan personal hygiene sebanyak 48 orang(75,0%), cukup mandiri 10 orang (15,6%) dan kemampuan anak autis kurang mandiri 6orang (9,4%). Anak autis mampu menjaga kebersihan diri sendiri dengan pengawasandari pengurus SLB. Pengurus SLB disarankan agar lebih melatih kemampuan personalhygiene anak autis
Modeling Seed Longevity and Percentile Prediction: A Sigmoidal Function Approach in Soybean, Maize, and Tomato
Authors: Carvalho Felipe Souza , Rezende Brunna Rithielly , Santos Amanda Rithieli Pereira dos , Sartori Maria Márcia Pereira
Published: December 2024

This study aims to evaluate the behavior of seed longevity in soybean, maize, and tomato stored under controlled conditions using Logistic and Boltzmann sigmoidal models. Additionally, it seeks to determine the performance of these models in predicting P50, P85, and P25. The models were fitted to the experimental longevity data, and their performance in predicting the percentiles was evaluated. The Logistic model showed better performance in predicting P50 (time for viability to drop to 50%), P85 (time for viability to drop to 85%), and P25 (time for viability to drop to 25%), estimating the parameters more frequently within the experimental range (obtained from the initial viability data). The results of this study suggest that some cultivars exhibited different patterns in deterioration rates, with some showing abrupt declines in viability, highlighting differences in the speed and nature of seed deterioration. The Logistic model proved to be superior, with an accuracy of 83% in estimating the P85 and P25 percentiles, while the Boltzmann model achieved an accuracy of 54%. The tomato cultivar Gaucho showed the greatest loss in germination, reaching P25 quickly, while the soybean cultivar M 7119 IPRO and maize cultivar MAM06 maintained high germination for a longer period. These findings emphasize the importance of using viability percentiles to optimize storage practices, minimize economic losses, and prevent genetic erosion in conservation programs. Modeling seed longevity using sigmoidal models can significantly contribute to determining various viability percentiles, supporting storage practices and providing valuable insights for strategic decision-making in seed management, proving useful in both commercial and species conservation contexts.
PMDNet: An Improved Object Detection Model for Wheat Field Weed
Authors: Qi Zhengyuan , Wang Jun
Published: December 2024

Efficient and accurate weed detection in wheat fields is critical for precision agriculture to optimize crop yield and minimize herbicide usage. The dataset for weed detection in wheat fields was created, encompassing 5967 images across eight well-balanced weed categories, and it comprehensively covers the entire growth cycle of spring wheat as well as the associated weed species observed throughout this period. Based on this dataset, PMDNet, an improved object detection model built upon the YOLOv8 architecture, was introduced and optimized for wheat field weed detection tasks. PMDNet incorporates the Poly Kernel Inception Network (PKINet) as the backbone, the self-designed Multi-Scale Feature Pyramid Network (MSFPN) for multi-scale feature fusion, and Dynamic Head (DyHead) as the detection head, resulting in significant performance improvements. Compared to the baseline YOLOv8n model, PMDNet increased mAP@0.5 from 83.6% to 85.8% (+2.2%) and mAP@0.50:0.95 from 65.7% to 69.6% (+5.9%). Furthermore, PMDNet outperformed several classical single-stage and two-stage object detection models, achieving the highest precision (94.5%, 14.1% higher than Faster-RCNN) and mAP@0.5 (85.8%, 5.4% higher than RT-DETR-L). Under the stricter mAP@0.50:0.95 metric, PMDNet reached 69.6%, surpassing Faster-RCNN by 16.7% and RetinaNet by 13.1%. Real-world video detection tests further validated PMDNet’s practicality, achieving 87.7 FPS and demonstrating high precision in detecting weeds in complex backgrounds and small targets. These advancements highlight PMDNet’s potential for practical applications in precision agriculture, providing a robust solution for weed management and contributing to the development of sustainable farming practices.
Efficient Pruning of Detection Transformer in Remote Sensing Using Ant Colony Evolutionary Pruning
Authors: Su Hailin , Sun Haijiang , Zhao Yongxian
Published: December 2024

This study mainly addresses the issues of an excessive model parameter count and computational complexity in Detection Transformer (DETR) for remote sensing object detection and similar neural networks. We propose an innovative neural network pruning method called “ant colony evolutionary pruning (ACEP)” which reduces the number of parameters in the neural network to improve the performance and efficiency of DETR-based neural networks in the remote sensing field. To retain the original network’s performance as much as possible, we combine population evolution and ant colony algorithms for dynamic search processes to automatically find efficient sparse sub-networks. Additionally, we design three different sparse operators based on the structural characteristics of DETR-like neural networks. Furthermore, considering the characteristics of remote sensing objects, we introduce sparsity constraints to each network layer to achieve efficient network pruning. The experimental results demonstrate that ACEP is effective on various DETR-like models. After removing a significant number of redundant parameters, it greatly improves the inference speed of these networks when performing remote sensing object detection tasks.
DVCW-YOLO for Printed Circuit Board Surface Defect Detection
Authors: Shi Pei , Zhang Yuyang , Cao Yunqin , Sun Jiadong , Chen Deji , Kuang Liang
Published: December 2024

The accurate and efficient detection of printed circuit board (PCB) surface defects is crucial to the electronic information manufacturing industry. However, current approaches to PCB defect detection face challenges, including large model sizes and difficulties in balancing detection accuracy with speed. To address these challenges, this paper proposes a novel PCB surface defect detection algorithm, named DVCW-YOLO. First, all standard convolutions in the backbone and neck networks of YOLOv8n are replaced with lightweight DWConv convolutions. In addition, a self-designed C2fCBAM module is introduced to the backbone network for extracting features. Next, within the neck structure, the C2f module is substituted with the more lightweight VOVGSCSP module, thereby reducing model redundancy, simplifying model complexity, and enhancing detection speed. By enhancing prominent features and suppressing less important ones, this modification allows the model to better focus on key regions, thereby improving feature representation capabilities. Finally, the WIoU loss function is implemented to replace the traditional CIoU function in YOLOv8n. This adjustment addresses issues related to low generalization and poor detection performance for small objects or complex backgrounds, while also mitigating the impact of low-quality or extreme samples on model accuracy. Experimental results demonstrate that the DVCW-YOLO model achieves a mean average precision (mAP) of 99.3% and a detection speed of 43.3 frames per second (FPS), which represent improvements of 4% and 4.08%, respectively, over the YOLOv8n model. These results confirm that the proposed model meets the real-time PCB defect detection requirements of small and medium-sized enterprises.
A Comparative Review on Biodegradation of Poly(Lactic Acid) in Soil, Compost, Water, and Wastewater Environments: Incorporating Mathematical Modeling Perspectives
Authors: Hajilou Narjess , Mostafayi Seyed Sepehr , Yarin Alexander L. , Shokuhfar Tolou
Published: December 2024

As the demand for environmentally friendly materials continues to rise, poly(lactic acid) (PLA) has emerged as a promising alternative to traditional plastics. The present review offers a comprehensive analysis of the biodegradation behavior of PLA in diverse environmental settings, with a specific focus on soil, compost, water, and wastewater environments. The review presents an in-depth comparison of the degradation pathways and kinetics of PLA from 1990 to 2024. As the presence of different microorganisms in diverse environments can affect the mechanism and rate of biodegradation, it should be considered with comprehensive comparisons. It is shown that the mechanism of PLA biodegradation in soil and compost is that of enzymatic degradation, while the dominant mechanisms of degradation in water and wastewater are hydrolysis and biofilm formation, respectively. PLA reveals a sequence of biodegradation rates, with compost showing the fastest degradation, followed by soil, wastewater, accelerated landfill environments, and water environments, in descending order. In addition, mathematical models of PLA degradation were reviewed here. Ultimately, the review contributes to a broader understanding of the ecological impact of PLA, facilitating informed decision-making toward a more sustainable future.
Characterizing Radon Among Public Buildings and Small/Medium-Sized Businesses in a Canadian Province
Authors: Yang Lily X. , Kirkham Tracy L. , Boksman Laura , Nicol Anne-Marie , Demers Paul A.
Published: December 2024

Radon is a naturally occurring radioactive gas that causes lung cancer. It has been measured extensively in homes and mines but research in other workplaces has been limited. The present study examined 453 workplaces in Ontario, Canada, to characterize radon levels. Radon monitors (n = 687) were placed in occupied ground floor and basement workplace locations for a minimum of three months. The radon measurements ranged from <4 to 566 Bq/m3, with a median of 26 Bq/m3, arithmetic mean of 40.2 Bq/m3, and geometric mean of 26.9 Bq/m3. Using the Health Canada and Ontario labor guideline of 200 Bq/m3, 2.5% of participating workplaces had at least one measurement above this level; 7.2% were above the World Health Organization guideline. Workplaces were also asked to fill out questionnaires to identify possible determinants of exposure. Radon levels varied significantly based on municipality and background radon zone, highlighting the importance of geography in influencing radon levels. Radon levels also varied significantly based on window-opening behavior, business access type, the presence of an elevator, air conditioning, additions to the building, and cracks and/or gaps in the foundation/wall and around drains, indicating building characteristics with some influence on air circulation may impact overall radon levels.
MobileNet-HeX: Heterogeneous Ensemble of MobileNet eXperts for Efficient and Scalable Vision Model Optimization
Authors: Pintelas Emmanuel , Livieris Ioannis E. , Tampakas Vasilis , Pintelas Panagiotis
Published: December 2024

Efficient and accurate vision models are essential for real-world applications such as medical imaging and deepfake detection, where both performance and computational efficiency are critical. While recent vision models achieve high accuracy, they often come with the trade-off of increased size and computational demands. In this work, we propose MobileNet-HeX, a new ensemble model based on Heterogeneous MobileNet eXperts, designed to achieve top-tier performance while minimizing computational demands in real-world vision tasks. By utilizing a two-step Expand-and-Squeeze mechanism, MobileNet-HeX first expands a MobileNet population through diverse random training setups. It then squeezes the population through pruning, selecting the top-performing models based on heterogeneity and validation performance metrics. Finally, the selected Heterogeneous eXpert MobileNets are combined via sequential quadratic programming to form an efficient super-learner. MobileNet-HeX is benchmarked against state-of-the-art vision models in challenging case studies, such as skin cancer classification and deepfake detection. The results demonstrate that MobileNet-HeX not only surpasses these models in performance but also excels in speed and memory efficiency. By effectively leveraging a diverse set of MobileNet eXperts, we experimentally show that small, yet highly optimized, models can outperform even the most powerful vision networks in both accuracy and computational efficiency.
Sulfated and Phosphorylated Agarose as Biomaterials for a Biomimetic Paradigm for FGF-2 Release
Authors: Forget Aurelien , Shastri V. Prasad
Published: December 2024

Cardiovascular diseases such as myocardial infarction or limb ischemia are characterized by regression of blood vessels. Local delivery of growth factors (GFs) involved in angiogenesis such as fibroblast blast growth factor-2 (FGF-2) has been shown to trigger collateral neovasculature and might lead to a therapeutic strategy. In vivo, heparin, a sulfated polysaccharide present in abundance in the extracellular matrix (ECM), has been shown to function as a local reservoir for FGF-2 by binding FGF-2 and other morphogens and it plays a role in the evolution of GF gradients. To access injectable biomaterials that can mimic such natural electrostatic interactions between soluble signals and macromolecules and mechanically tunable environments, the backbone of agarose, a thermogelling marine–algae-derived polysaccharide, was modified with sulfate, phosphate, and carboxylic moieties and the interaction and release of FGF-2 from these functionalized hydrogels was assessed by ELISA in vitro and CAM assay in ovo. Our findings show that FGF-2 remains active after release, and FGF-2 release profiles can be influenced by sulfated and phosphorylated agarose, and in turn, promote varied blood vessel formation kinetics. These modified agaroses offer a simple approach to mimicking electrostatic interactions experienced by GFs in the extracellular environment and provide a platform to probe the role of these interactions in the modulation of growth factor activity and may find utility as an injectable gel for promoting angiogenesis and as bioinks in 3D bioprinting.
Peptide Inhibitor Assay for Allocating Functionally Important Accessible Sites Throughout a Protein Chain: Restriction Endonuclease EcoRI as a Model Protein System
Authors: Otaki Joji M.
Published: December 2024

Functionally important amino acid sequences in proteins are often located at multiple sites. Three-dimensional structural analysis and site-directed mutagenesis may be performed to allocate functional sites for understanding structure‒function relationships and for developing novel inhibitory drugs. However, such methods are too demanding to comprehensively cover potential functional sites throughout a protein chain. Here, a peptide inhibitor assay (PIA) was devised to allocate functionally important accessible sites in proteins. This simple method presumes that protein‒ligand interactions, intramolecular interactions, and dimerization interactions can be partially inhibited by high concentrations of competitive “endogenous” peptides of the protein of interest. Focusing on the restriction endonuclease EcoRI as a model protein system, many endogenous peptides (6mer-14mer) were synthesized, covering the entire EcoRI protein chain. Some of them were highly inhibitory, but interestingly, the nine most effective peptides were located outside the active sites, with the exception of one. Relatively long peptides with aromatic residues (F, H, W, and Y) corresponding to secondary structures were generally effective. Because synthetic peptides are flexible enough to change length and amino acid residues, this method may be useful for quickly and comprehensively understanding structure‒function relationships and developing novel drugs or epitopes for neutralizing antibodies.
The Influence of Trait and State Creative Self-Efficacy on Creative Behavior: An Experimental Study Using False Feedback
Authors: Tao Rui , Zhang Haoman , Geng Li , Li Yu , Qiu Jiang
Published: December 2024

This study explores the relationship between creative self-efficacy and creative behavior by modulating state-level creative self-efficacy through false feedback to enhance creative performance. In Study 1, 1539 college students completed the Alternative Uses Task (AUT) to measure performance-based creativity and the Creative Achievement Questionnaire (CAQ) to assess self-reported creative achievements. The Big Five personality traits and curiosity served as covariates. Regression and correlation analyses were conducted to examine the relationship between trait-level creative self-efficacy and both creative performance measures. Experiment 2 employed a 2 × 2 between-subjects design to test the effects of false feedback (positive vs. negative) and trait-level creative self-efficacy (high vs. low) on state-level creative self-efficacy and creative behavior, using the same covariates. In Study 1, creative self-efficacy was positively correlated with both AUT and CAQ, with stronger associations for CAQ. Experiment 2 found that false feedback significantly affected state-level creative self-efficacy and the originality of creative behavior. Changes in state-level creative self-efficacy were positively correlated with originality. This study emphasizes the role of both trait and state-level creative self-efficacy in influencing creative behavior. It offers insights for enhancing creativity through feedback, with implications for educational and workplace settings.
Zeolite Synthesized from Solid Waste for Eco-System Remediation: Selective Adsorption in Wastewater
Authors: Araujo Mariana S. , Costa-Silva Danilo , Izidoro Juliana C. , Fungaro Denise A. , Castanho Sonia Mello
Published: December 2024

The present investigation explores the potential of two synthesized zeolites, derived from coal fly ash (CFA; thermoelectric waste) and sugarcane bagasse ash (SCBA; agro-industrial waste), for the selective adsorption of cesium in wastewater. The synthesized zeolites (ZCFA and ZSCBA) were characterized and compared with a commercial zeolite to evaluate their physicochemical properties and effectiveness in removing cesium ions (Cs+) from simulated radioactive wastewater. The results obtained from X-ray diffraction, scanning electron microscopy, and elemental analysis confirmed the successful synthesis of high-purity zeolite from both solid wastes. The impurities present in the ashes impacted the Si/Al ratio and consequently influenced the exchange capacity. After adsorption experiments, neutron activation analysis (NAA) revealed that ZSCBA adsorbed 33.4% of Cs2O by weight, outperforming both ZCFA (26.0%) and commercial zeolite (27.9%). The superior performance of ZSCBA is attributed to its distinct Si/Al ratio and lower levels of impurities, highlighting the impact of these factors on adsorption selectivity. The findings in this study demonstrate the feasibility of valorizing agro-industrial waste for synthesizing zeolites, offering a sustainable approach for managing these residues while producing valuable materials for environmental remediation.
Identification of Olfactory Receptors Responding to Androstenone and the Key Structure Determinant in Domestic Pig
Authors: Yang Peidong , Luo Tingting , Yang Shuqi , Zhang Anjing , Tang Yuan , Chen Li , Wang Jinyong , Zhao Yongju , Zhong Zhining , Li Xuemin , Han Ziyin , Zhang Yupei , Tang Yue , Ma Jideng , Jin Long , Long Keren , Li Mingzhou , Lu Lu
Published: December 2024

Olfactory receptors (ORs) are members of the transmembrane G protein-coupled receptor superfamily, playing a crucial role in odor recognition, which further mediates crucial biological processes in mammals. In sows, androstenone can trigger sexual behaviors through olfaction, but the underlying mechanism remains to be explored. To efficiently and accurately screen pig olfactory receptors responding to androstenone and the key structure determinant, we adapted the high-throughput RNA-seq strategy to screen the altered genes upon androstenone treatment in the olfactory epithelium of pigs, yielding 1397 downregulated genes. Of which, 15 OR genes and 49 OR-like genes were candidate androstenone-responsive genes, and 5 ORs (OR2D2, OR8D1, OR8D2, OR10Z1 and OR7D4) were proven as responsible for androstenone-mediated olfaction in vitro. Among the five ORs, pig OR7D4 has the highest level of androstenone response. To further find the structural determinant, we performed ligand-binding cavity analysis on pig OR7D4 with androstenone, predicted seven potential structural sites and further confirmed that F178 and T203 are the key sites for recognizing androstenone. Nevertheless, the natural non-synonymous mutation M133V (rs696400829) of pig OR7D4 was proven to significantly impair the respondence to androstenone. This is the first time the ORs responding to androstenone in pigs and the key structural determinant of pig OR7D4 were identified, which highlights the significance of investigating the role of OR7D4 in pig reproduction performance in the future.
Methodologic and Policy Efforts to Improve a National Long COVID Study
Authors: Jason Leonard A.
Published: December 2024

Researching COVID to Enhance Recovery (RECOVER) is a National Institutes of Health initiative to improve our understanding of recovery after SARS-CoV-2 infection and to prevent and treat Long COVID. For almost two years, I worked with a RECOVER Task Force called Commonalities with Other Post Viral Syndromes, whose scope was the overlap of Long COVID symptoms and possible pathways with other post-viral syndromes, including Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and other dysautonomias. In this article, I review how I was selected to be on this Commonalities task force, and my role as chairperson of a subcommittee that accomplished some specific goals, such as being able to introduce ME/CFS-specific symptoms and ways to assess them in the adult and pediatric RECOVER battery. An effort to have a study funded to collect an independent sample of patients diagnosed with ME/CFS before the pandemic was not successful. This commentary outlines the process of working with this Long COVID task force, including steps such as questionnaire development, protocol design, reviews, and policy initiatives. The outcomes of this task force and subcommittee are reviewed, and lessons learned are presented for those with an interest in working toward policy and structural change.
Elliptic Curve Cryptography with Machine Learning
Authors: Jebrane Jihane , Chhaybi Akram , Lazaar Saiida , Nitaj Abderrahmane
Published: December 2024

Elliptic Curve Cryptography (ECC) is a technology based on the arithmetic of elliptic curves used to build strong and efficient cryptosystems and infrastructures. Several ECC systems, such as the Diffie–Hellman key exchange and the Elliptic Curve Digital Signature Algorithm, are deployed in real-life applications to enhance the security and efficiency of digital transactions. ECC has gained even more importance since the introduction of Bitcoin, the peer-to-peer electronic cash system, by Satoshi Nakamoto in 2008. In parallel, the integration of artificial intelligence, particularly machine learning, in various applications has increased the demand for robust cryptographic systems to ensure safety and security. In this paper, we present an overview of machine learning and Elliptic Curve Cryptography algorithms. We begin with a detailed review of the main ECC systems and evaluate their efficiency and security. Subsequently, we investigate potential applications of machine learning-based techniques to enhance the security and performance of ECC. This study includes the generation of optimal parameters for ECC systems using machine learning algorithms.
Retrospective, Non-Interventional, Multicenter Study on the Effectiveness and Safety of Intravesical Bacillus Calmette–Guerin in Patients with Non-Muscle-Invasive Bladder Cancer: Real-World Experience from Six Hospital Centers in Greece
Authors: Angelopoulos Panagiotis , Markopoulos Titos , Lazarou Lazaros , Skolarikos Andreas , Stamatakos Panagiotis , Papadopoulos Georgios I. , Fragkoulis Charalampos , Ntoumas Konstantinos , Moulavasilis Napoleon , Levis Panagiotis , Papanikolaou Dimitrios , Sokolakis Ioannis , Hatzimouratidis Konstantinos , Tzanetakos Charalampos , Psarra Marina , Mavridoglou George , Skriapas Konstantinos , Akrivou Dimitra , Karagiannis Dimitrios , Noutsos Christos , Georgiou Andreas , Hastazeris Konstantinos , Gourzoulidis George , Mitropoulos Dionysios
Published: December 2024

Background: While the clinical application of SII-ONCO-Bacillus Calmette–Guerin (BCG) for non-muscle-invasive bladder cancer (NMIBC) is well established in Greece, there is a lack of real-world data on its effectiveness and safety. This retrospective, observational, multicenter, chart-review study aims to provide real-life data on the effectiveness and safety of SII-ONCO-BCG in patients with intermediate- and high-risk NMIBC. Methods: From January 2016 to December 2023, medical records from six hospital centers were reviewed for adult patients with histologically confirmed stage Ta or T1 NMIBC (with or without carcinoma in situ [CIS]) who received at least one maintenance course of SII-ONCO-BCG after induction. Tumor recurrence and progression were monitored at scheduled time intervals. Primary outcomes included recurrence-free survival (RFS) and progression-free survival (PFS), while adverse events (AEs) constituted secondary outcomes. Results: A total of 162 patients receiving SII-ONCO-BCG were enrolled. Among all patients, 145 (89.5%) patients were men, 88 (54.3%) aged 70 years or older, 103 (63.6%) had T1, 43 (26.5%) Ta, and 21 (12.9%) concurrent CIS. The median follow-up duration was 28.9 months (range, 5–36) and the mean BCG intravesical instillation courses were 13.7 (range, 9–27). After 3-, 2-, and 1-year follow-up, RFS rates of 85.2% (95% CI, 79.7–90.7%), 85.8% (80.4–91.2%), and 87.0% (81.8–92.3%) were observed, respectively. The corresponding 3-, 2-, and 1-year PFS rates were 96.9% (94.2–99.6%), 96.9% (94.2–99.6%), and 97.5% (95.1–99.9%), respectively. During the whole follow-up period, 24 (14.8%) patients experienced at least one AE. Conclusions: This real-world study demonstrates that SII-ONCO-BCG is an effective and safe treatment for patients with intermediate- and high-risk NMIBC.
Role of Age, Comorbidity, and Frailty in the Prediction of Postoperative Complications After Surgery for Vulvar Cancer: A Retrospective Cohort Study with the Development of a Nomogram
Authors: Delli Carpini Giovanni , Sopracordevole Francesco , Cicoli Camilla , Bernardi Marco , Giuliani Lucia , Fichera Mariasole , Clemente Nicolò , Del Fabro Anna , Di Giuseppe Jacopo , Giannella Luca , Busato Enrico , Ciavattini Andrea
Published: December 2024

Surgery is the cornerstone of vulvar cancer treatment, but it is associated with a significant risk of complications that may impact prognosis, particularly in older patients with multiple comorbidities. The objective of this study was to evaluate the role of age, comorbidities, and frailty in predicting postoperative complications after vulvar cancer surgery and to develop a predictive nomogram. A retrospective cohort study was conducted, including patients who underwent surgery for vulvar cancer at two Italian institutions from January 2018 to December 2023. A logistic regression model for the rate of Clavien-Dindo 2+ 30-days complications was run, considering the age-adjusted Charlson Comorbidity Index (AACCI), body mass index (BMI), and frailty as exposures. Lesion characteristics and surgical procedures were considered as confounders. Among the 225 included patients, 50 (22.2%) had a grade 2+ complication. The predictive score of the nomogram ranged from 44 to 140. The AACCI (0–64 points) and BMI (0–100 points) were independently associated with a risk of complications. A nomogram including the AACCI and BMI predicts the risk of complications for patients undergoing surgery for vulvar cancer. The preoperative determination of the risk of complications enables surgical planning and allows a tailored peri- and postoperative management plan.
Pain and Frailty in Childhood Cancer Survivors: A Narrative Review
Authors: Papini Chiara , Sodhi Jaspreet K. , Argenbright Cassie M. , Ness Kirsten K. , Brinkman Tara M.
Published: December 2024

A significant proportion of childhood cancer survivors experience persistent health problems related to cancer or cancer treatment exposures, including accelerated or early onset of aging. Survivors are more likely than non-cancer peers to present a frail phenotype suggestive of reduced physiologic reserve and have symptoms that interfere with function in daily life, including pain. Studies in the general population, mostly among older adults, suggest that pain is a significant contributor to development and progression of frail health. This association has not been explored among childhood cancer survivors. In this narrative review, we highlight this gap by summarizing the epidemiologic evidence on pain and frailty, including their prevalence, common risk factors, and correlates in childhood cancer survivors. We further discuss associations between pain and frailty in non-cancer populations, likely biological mechanisms in survivors, and potential interventions targeting both domains.
Geographic Distribution Patterns of Soil Microbial Community Assembly Process in Mangrove Constructed Wetlands, Southeast China
Authors: Hu Ping , Yang Qiong
Published: December 2024

Constructed wetlands, as an emerging wastewater treatment system, have been widely used worldwide due to their high purification efficiency and low investment and operating costs. Wetland plants, on the other hand, together with their inter-root microbes, significantly affect the ecological functions of constructed wetlands. The mangrove constructed wetland within Futian District, Shenzhen, China, is a typical wastewater treatment area, but the structure and function of its soil microbial community remain largely unexplored. In this study, the assembly and processes of the soil microbial communities in this constructed wetland were intensively investigated using high-throughput sequencing technology. Our results showed that the three mangrove plants had significant effects on the soil bacterial microbial community α-diversity, insignificant effects on β-diversity, and significant effects on fungal α-diversity and β-diversity. The abundance of genera changed significantly between the treatment groups, such as the genus Candidatus_Udaeobacter for bacteria versus Russula for fungi, and the random forest model showed that rare genera (e.g., Acidibacter, Dyella, Sebacina, and Lachnellula) also play an important role in microbial community construction. Community assembly revealed the deterministic process of soil bacterial and fungal communities under different mangrove species. Overall, this study enhanced our understanding of soil microbial community composition and diversity in constructed wetlands ecosystems, providing insights into their manageability.
Adoption and Use of Customized Wheelchairs Manufactured for Persons Living with Disability: Modified UTUAT-2 Perspective
Authors: Dzogbewu Thywill Cephas , Whitehead Timothy , de Beer Deon Johan , Torrens George
Published: December 2024

The mobility and independence of people with disabilities could be significantly improved by wheelchairs. Wheelchair adoption is a complex process that is influenced by various factors, including personal demands, social dynamics, and technological advancements. To effectively promote wheelchair adoption and enhance the quality of life for people with mobility issues, it is crucial to understand the adoption of wheelchairs from a holistic perspective. A model comprising six hypotheses was developed based on the UTUAT-2 (Unified Theory of Acceptance and Use of Technology) framework with modifications. The data was analyzed from 330 individuals living with a disability using SPSS and Smart PLS. The study revealed that performance expectancy, effort expectancy, habit, social influence, and perceived infrastructure individually influence the intention to use wheelchairs. The results further revealed that price value and facilitating conditions were not significant predictors of intention to use a wheelchair. The results also showed that aesthetic design moderates the effect of effort expectancy, habit, social influence, price value, and perceived infrastructure on behavioral intention. Through a multidimensional lens, the paper offers practical recommendations to improve the adoption of wheelchairs for people with mobility impairments.
Cost-Effective Drone Survey of Areas with Elevated Background Radiation
Authors: Katreiner Hédi , Kovács Béla , Horváth Ákos , Tóth Szabolcs , Vörös Fanni
Published: December 2024

The use of UAVs to map ionising radiation resulting from radioactive decay is gaining popularity among researchers due to its efficiency and safety. Many studies have been conducted, most of them using expensive sensors. The present research aims to investigate the applicability of an affordable radiation detector in areas where anomalies from natural sources occur. In this research, we use a DJI Matrice 210 V2 RTK quadcopter equipped with a cost-effective Safecast bGeigie Nano Kit radiation sensor to take measurements at different altitudes above ground. We convert these data into GIS-compatible formats and produce accurate isoline maps using the Minimum Curvature interpolation technique. The results show that while the radiation intensity decreases with height, the anomaly was visible but less detailed at all heights investigated. In addition, the study highlights the significant differences in position measurements between RTK GNSS and autonomous GNSS measurements that affect the accuracy of the data. The results will contribute to a more accurate determination of the radiation extent and, thus, to maintaining safety, as well as assisting in emergency surveys and environmental monitoring.
Autonomous Underwater Glider: A Comprehensive Review
Authors: Petritoli Enrico , Leccese Fabio
Published: December 2024

A comprehensive review of Autonomous Underwater Gliders encompasses their development, technological advancements, operational principles, and applications in various fields. It explores the different types of architectures, such as those with blended wing or conventional designs, and examines their roles in scientific research and civil use. The review also addresses the challenges and limitations in areas like payload, navigation, swarm management, and the effects of underwater environments on glider performance. This knowledge is essential for improving glider technology and expanding their potential in future underwater exploration and data collection missions.
Relationship Between the 2019 Ridgecrest, California, MW7.1 Earthquake and Its MW6.4 Foreshock Sequence
Authors: Zheng Jianchang , Zhang Zhengshuai , Li Xiaohan
Published: December 2024

The 2019 Ridgecrest MW7.1 earthquake has received significant attention due to its complex fault activity. It is also noticeable for its MW6.4 foreshock sequence. There are intricate dynamic relationships between earthquakes in such vigorous sequences. Based on the relocated catalogue, we adopt the nearest neighbour algorithm to analyze its foreshock and aftershock sequences. Detailed links and family structures of the sequence are obtained. The results show that a MW5.0 event at 03:16 (UTC) on 6 July is a direct foreshock of the MW7.1 mainshock. It is likely related to barriers on the northwest-striking fault. The MW6.4 event on 4 July is characterized as a complex conjugate rupture. Notably, a magnitude 4.0 event occurred on the northwest-striking fault before the MW6.4 event, establishing it as a direct foreshock. The Ridgecrest sequence is predominantly influenced by northwest fault activity. It first caused small fractures on the northwest-striking fault. Then, it triggered conjugate slips on the southwest-striking fault. Lastly, it led to larger ruptures on the northwest-striking fault.
Algorithms for Solving the Equilibrium Composition Model of Arc Plasma
Authors: Chi Zhongyuan , Ji Yuzhang , Liu Ningning , Jiang Tianchi , Liu Xin , Zhang Weijun
Published: December 2024

In the present study, the Homotopy Levenberg−Marquardt Algorithm (HLMA) and the Parameter Variation Levenberg–Marquardt Algorithm (PV–LMA), both developed in the context of high-temperature composition, are proposed to address the equilibrium composition model of plasma under the condition of local thermodynamic and chemical equilibrium. This model is essentially a nonlinear system of weakly singular Jacobian matrices. The model was formulated on the basis of the Saha and Guldberg–Waage equations, integrated with Dalton’s law of partial pressures, stoichiometric equilibrium, and the law of conservation of charge, resulting in a nonlinear system of equations with a weakly singular Jacobian matrix. This weak singularity primarily arises due to significant discrepancies in the coefficients between the Saha equation and the Guldberg–Waage equation, attributed to differing chemical reaction energies. By contrast, the coefficients in the equations derived from the other three principles within the equilibrium composition model are predominantly single−digit constants, further contributing to the system’s weak singularity. The key to finding the numerical solution to nonlinear equations is to set reasonable initial values for the iterative solution process. Subsequently, the principle and process of the HLMA and PV–LMA algorithms are analyzed, alongside an analysis of the unique characteristics of plasma equilibrium composition at high temperatures. Finally, a solving method for an arc plasma equilibrium composition model based on high temperature composition is obtained. The results show that both HLMA and PV–LMA can solve the plasma equilibrium composition model. The fundamental principle underlying the homotopy calculation of the (n−1) −th iteration, which provides a reliable initial value for the n−th LM iteration, is particularly well suited for the solution of nonlinear equations. A comparison of the computational efficiency of HLMA and PV–LMA reveals that the latter exhibits superior performance. Both HLMA and PV–LMA demonstrate high computational accuracy, as evidenced by the fact that the variance of the system of equations ||F|| < 1 × 10−15. This finding serves to substantiate the accuracy and feasibility of the method proposed in this paper.
A Conceptual Framework for the Apibotanical Evaluation of Different Landscapes
Authors: Díaz Rosana , Niell Silvina , Cesio María Verónica , Heinzen Horacio
Published: December 2024

The suitability of different agroecosystems (native forest, soybean, artificial forest with Eucalyptus sp., mixed horticulture and fruticulture, and dairy prairies) for settling and managing hives for honey production were appraised via holistic surveys of the spatial and seasonal occurrence of floral resources. Metadata were obtained from a project developed by our group, which took place between 2014 and 2017. Species richness, abundance, growth habit (tree, shrub, stand, scrub or stem, accompanying species), and the flowering period for each melliferous plant across the different seasons in 120 samples were measured. Using the Shannon–Wiener diversity index and the floral characteristics of the different species in each environment, an Agroecosystem Apibotanical Index was developed. It revealed that the best agroecosystems for honey production were the most biodiverse native forest as well as mixed horticulture and fruit culture. Knowledge of the floral characteristics and species arrangement enabled the categorization of agroecosystems, aiming for rational management to enhance honey production.
Numerical Investigation on the Applicability of Variable Compression Ratio in a Marine Two-Stroke Dual-Fuel Engine for Fuel Economy Improvement
Authors: Shen Haosheng , Lu Daoyi
Published: December 2024

Marine two-stroke dual-fuel (DF) engines with a low-pressure gas concept normally face the problem of inferior fuel economy in diesel mode, mainly due to their lower compression ratio. To address this issue, a numerical study is performed to investigate the applicability of variable compression ratio (VCR) in a marine two-stroke DF engine, aiming at improving fuel economy in diesel mode. First, an engine simulation model is established and validated. Then, parametric investigation is performed to obtain insights on the effects of VCR on engine combustion, performance, and emissions. Finally, regression models of selected engine response variables are determined based on the response surface methodology (RSM), which are then optimized by particle swarm optimization (PSO) to obtain the optimal solution of engine setting parameters. The results show that with the application of VCR, the brake specific fuel consumption (BSFC) decreases by 9.65, 11.38, 11.13, and 11.27% at 25, 50, 75, and 100% maximum continuous rating (MCR), respectively. Meanwhile, the nitrogen oxides (NOx) emissions are maintained at the original levels, and the engine’s operating parameters are within specified limits. This study contributes to the delineation of the benefits and limits of VCR and provides a feasible method to facilitate the implementation of VCR in marine engines.
Low-Voltage Renewable Energy Communities’ Impact on the Distribution Networks
Authors: Mocci Susanna , Ruggeri Simona , Pilo Fabrizio
Published: December 2024

Renewable energy communities (RECs) are widely regarded as a transformative opportunity to enhance the management of electricity distribution networks, benefiting the system as a whole and its participants through local energy production, increased self-consumption, and empowering citizens. However, their proliferation introduces significant challenges for distribution system management, particularly at the low-voltage (LV) level, where participants are primarily located. Despite its critical role, the LV network is often overlooked in favor of studies focusing on the system-level impacts. This paper addresses this gap by evaluating the impact of RECs on LV networks and the broader distribution system. The study analyzes various LV networks representative of the Italian context, encompassing both rural and urban areas. By leveraging the software tool OpenDSS and Monte Carlo simulations over an entire year, the analysis captures the inherent variability of load demand and photovoltaic generation, as well as the resulting network imbalances under diverse policy scenarios. The findings reveal that the increasing level of self-consumption could significantly challenge distribution network operation, limiting also the sourcing of flexibility. These results underscore the necessity for advanced management strategies and targeted investments in grid flexibility to ensure the reliability and efficiency of distribution networks integrating RECs.
Numerical Simulation Study on Gas Migration Patterns in Ultra-Long Fully Mechanized Caving Face and Goaf of High Gas and Extra-Thick Coal Seams
Authors: An Huaming , Gong Ruyue , Liang Xingxing , Wang Hongsheng
Published: December 2024

The purpose of this study is to understand the law of gas migration in the goaf and reduce the gas on the working face. Taking the N2105 working face of the coal mining industry as the research object, the mathematical model of gas seepage in the goaf was established based on the percolation theory of porous media, and the model was solved. Using Fluent software to simulate the initial pressure, the working face airflow, and gas concentration distribution, different ventilation modes of gas concentration distribution and migration law with different wind speeds after the initial gas pressure. It is concluded that for the first time, the effect of gas on the working face is insignificant, and the influence of the initial pressure on the working surface is gradually revealed. The influence of airflow speed on the goaf is mainly concentrated in the 20~30 m area near the working face, which is affected by the airflow speed of the working face. The gas concentration in the goaf is low, and the fluctuation is obvious. The types of ventilation directly affect the seepage law of goaf gas. The U + I and U + L type ventilation can reduce the gas concentration in the upper corner and f gas seepages from goaf to the working face.