bluuebunny/crossref_metadata_2025 huggingface dataset:
The Equilibrium of Bacterial Microecosystem: Probiotics, Pathogenic Bacteria, and Natural Antimicrobial Substances in Semen
Authors: Miao Xuelan , Zhao Yanhua , Zhu Lingxi , Zeng Yutian , Yang Cuiting , Zhang Run , Khan Arab , Zhang Ming
Published: October 2024

Semen is a complex fluid that contains spermatozoa and also functions as a dynamic bacterial microecosystem, comprising probiotics, pathogenic bacteria, and natural antimicrobial substances. Probiotic bacteria, such as Lactobacillus and Bifidobacterium, along with pathogenic bacteria like Pseudomonas aeruginosa and Escherichia coli, play significant roles in semen preservation and reproductive health. Studies have explored the impact of pathogenic bacteria on sperm quality, providing insights into the bacterial populations in mammalian semen and their influence on sperm function. These reviews highlight the delicate balance between beneficial and harmful bacteria, alongside the role of natural antimicrobial substances that help maintain this equilibrium. Moreover, we discus the presence and roles of antimicrobial substances in semen, such as lysozyme, secretory leukocyte peptidase inhibitors, lactoferrin, and antimicrobial peptides, as well as emerging antibacterial substances like amyloid proteins. Understanding the interactions among probiotics, pathogens, and antimicrobial agents is crucial for elucidating semen preservation and fertility mechanisms. Additionally, the potential for adding probiotic bacteria with recombinant antibacterial properties presents a promising avenue for the development of new semen extenders. This review offers updated insights to understand the equilibrium of bacterial microecosystem in semen and points toward innovative approaches for improving semen preservation.
Correlation Analysis of Vertical Ground Movement and Climate Using Sentinel-1 InSAR
Authors: Pirotti Francesco , Toffah Felix  Enyimah , Guarnieri Alberto
Published: October 2024

The correlation of periodic seasonal vertical ground movement (SVGM) with climatic data from earth observation was investigated in this work. The European Ground Motion Service (EGMS) vertical ground movement measurements, provided from 2018 to 2022, were compared with temperature and precipitation data from MODIS and CHIRP datasets respectively. Measurement Points (MP) from EGMS over Italy provided a value of ground vertical movement approximately every 6 days. Precipitation and temperature datasets were processed to provide Drought Code (DC) maps calculated ad hoc for this study at 1 km spatial resolution and daily temporal resolution. Seasonal patterns were analysed to assess correlation with Spearman’s rank correlation coefficient (ρ) between this measure and DC from Copernicus CEMS (DCCEMS) and from MODIS+CHIRP (DC1km) and from temperature. Results over the considered area (Italy) showed that 0.46% of all MPs (32 826 MPs out of 7 193 676 MPs) have a ρ greater than 0.7: 12 142 of those have positive correlation, and 20 684 have negative correlation. DC1km was the climatic factor that provided the higher number of correlated MPs, roughly giving +59% more correlated MPs than DCCEMS and +300% than temperature data. If ρ greater than 0.8 was considered, the number of MPs drops by a factor of 10; from 12 142 to 1 275 for positive correlation and from 20 684 to 2 594 for negative correlation between DC1km values and SVGM measurements. Correlations lagged in time resulted in most of the correlated MPs being inside a window of +/- 6 days (a single satellite overpass time). Because DC and temperature are strongly co-linear, further analysis to assess which is better at explaining the seasonality of MPs was carried out, resulting in DC1km significantly explaining more variance of the SVGM than temperature for the inversely correlated points more than the directly correlated points. Spatial distribution of correlated MPs shows that they are unevenly distributed in clusters the Italian territory. This work will lead to further investigation both at local scale and at a pan-European scale. An interactive WebGIS application open to the public is available for data consultation. Data are shared in a public repository for replication of the method.
Single Trace Analysis of Visible vs. Invisible Leakage for Comparison Operation Based CDT Sampling
Authors: Choi Keon-Hee , Han Jaseung , Han Dong-Guk
Published: October 2024

The emergence of quantum computers poses a significant threat to the security of conventional public-key cryptosystems, driving the demand for quantum-resistant cryptographic solutions. In response, NIST conducted a multi-year competition, ultimately selecting four ciphers. Among these, Falcon employs CDT sampling, which produces arrays of random values derived from a discrete Gaussian distribution during the signature generation phase. This array is then used with secret key information, forming the core of Falcon. Enhanced variants of Falcon, such as Mitaka, SOLMAE, and Antrag, implemented CDT sampling using comparison operations. Previous research by Choi et al. proposed a single trace analysis and countermeasure for CDT sampling, which exploited a non-constant-time vulnerability in 8-bit AVR microcontrollers. However, this vulnerability is specific to certain environments, and a potentioal vulnerability in comparison operation based constant-time CDT sampling remain not studied. This paper is an extension of that study. This paper investigates the constant-time operation of comparison operation-based CDT sampling on Arm Cortex-M4-based chips and proposes a deep learning-based side-channel analysis to recover the sampling values using novel vulnerability. The proposed model achieves an F1 score of 1.0 and a recovery success rate of 99.97%.
Physiological Evaluation of Salt Tolerance on Different Genotypes of Sunflower Germplasms at the Seedling Stage
Authors: Chen Fangyuan , Xiao Lvting , Huang Qixiu , Xiang Lijun , Li Qiang , Hou Xianfei , Lei Zhonghua , Zeng Youling
Published: October 2024

Sunflower (Helianthus annuus L.) is an important oilseed crop cultivated extensively across the globe. High salinity adversely impacts plant growth and physiological processes. In this study, the data of the phenotypes and various indices were collected to clarify the physiological mechanisms underlying sunflower's salt tolerance with the seedlings of two salt-tolerant (182265 and 182283) and two salt-sensitive (182093 and 186096) genotypes, which were exposed to 350 mM NaCl for 4 days. The findings revealed that, during the seedling stage, salt-tolerant sunflowers accumulated less Na+ and more K+, resulting in a higher K+/Na+ ratio that mitigated ionic toxicity throughout the plants, compared to the salt-sensitive resources. Furthermore, the salt-tolerant germplasms also exerted salt tolerance through the following several pathways: they maintained robust osmotic regulation by accumulating higher levels of proline, soluble sugars, and other osmolytes; they neutralized reactive oxygen species (ROS) by elevating the activity of antioxidant enzymes; and they sustained optimal growth by boosting photosynthesis. Taken together, this study provided a more comprehensive assessment of the sunflower's physiological salt tolerance, offering valuable insights for further exploration of the molecular mechanisms of salt tolerance and accelerating the breeding process for sunflower varieties with improved salt resilience.
Biodegradation of Polyethylene Using Bacillus tropicus Isolated from Sewage Wastewater Treatment Plant
Authors: Isha Isha , Ali Shakir , Chang Young-Cheol
Published: October 2024

One of the most pressing environmental problems contemporary civilizations confront is the ever-increasing amount of plastic waste. Because of their impact on every living thing, these wastes are seen as a major issue on a global scale. To counteract the harmful environmental effects caused by conventional disposal methods, it is critical to show that eco-friendly alternatives are viable. Biodegradation is one of the best eco-friendly methods for removing plastic waste. In this study, we aimed to identify bacteria from sewage wastewater treatment plants (SWW) that could degrade polyethylene. The bacterial strains isolated from sewerage wastewater were incubated for 120 days in 50 ml of minimal salt media (MSM) containing 60mg polyethylene. After four months, our research revealed that Bacillus tropicus (SH4) demonstrated significant potential, degrading poly-ethylene up to 21.6%. We observed the changes after biodegradation using FTIR, GC-MS, and SEM analysis. In conclusion, microorganisms extracted from sewage wastewater possess the ability to mitigate plastic contamination in aquatic ecosystems. Future proteomics and genome investiga-tions are necessary to elucidate the enzymes and metabolic processes implicated in plastic breakdown.
Strontium and Copper Doped Ceramic Granules in Bone Regeneration-Associated Cellular Processes
Authors: Safarova (Yantsen) Yuliya , Nessipbekova Assem , Syzdykova Aizhan , Olzhayev Farkhad , Umbayev Bauyrzhan , Kassenova Aliya , Fadeeva Inna V. , Askarova Sholpan , Rau Julietta V.
Published: October 2024

Background: Pathological bone fracturing is an escalating problem driven by increasing aging and obesity. Bioceramics, particularly tricalcium-phosphate-based materials (TCP), are renowned for their exceptional biocompatibility, osteoconductivity, and ability to promote biomineralization. In the present study, we designed and characterized TCP porous granules doped with Strontium (Sr) and Copper (Cu). Sr2+ ions were selected as it plays a crucial role in early bone formation, osteogenesis and angiogenesis; Cu2+ ions possesses antibacterial properties.
Materials: The synthesized CuSr TCP granules were characterized by X-Ray Diffraction. Cytotoxicity and cell proliferation analyses assays were performed through the Lactate dehydrogenase (LDH) activity and CCK-8 viability tests in rat bone marrow-derived mesenchymal stem cells (BM-MSCs). Hemolytic activity was carried out with human red blood cells (RBCs). Early and late osteogenesis was assessed with alkaline phosphatase (ALP) and Alizarin Red S activity in human osteoblast progenitor cells and rat BM-MSCs. The influence of Sr and Cu-substituted TCP on angiogenesis was investigated in human umbilical vein endothelial cells (HUVECs).
Results: We have demonstrated that a media enriched with CuSr TCP in concentrations ranging from 0.1 mg/ml to 1 mg/ml was not cytotoxic and did not significantly affect cell proliferation rate motility. Moreover, a concentration of 0.5 mg/ml has shown a 2.5-fold increase in the migration potential of BM-MSCs. We also found that CuSr TCP-enriched media slightly increased early osteogenesis. We also found that Sr and Cu substitutions in TCP particles significantly enhanced the measured angiogenic parameters compared to control and unsubstituted TCP granules.
Conclusion: Our results demonstrate that TCP porous granules doped with Sr and Cu are biocompatible, promote osteodifferentiation and angiogenesis, and could be recommended for further in vivo studies.
From Food Supplements to Functional Foods: Emerging Perspectives on Post-Exercise Recovery Nutrition
Authors: Wang Lifeng , Meng Qing , Su Chun-Hsien
Published: October 2024

Post-exercise recovery is fundamental to optimizing athletic performance, focusing on muscle repair, glycogen replenishment, rehydration, and reducing exercise-induced inflammation. This review examines the evolving landscape of recovery nutrition, highlighting the transition from conventional supplements—such as protein, carbohydrates, creatine, and branched-chain amino acids (BCAAs)—to functional foods rich in bioactive compounds. Emerging evidence supports the efficacy of functional foods like tart cherry juice, turmeric, and omega-3 fatty acids in mitigating oxidative stress and inflammation, thus accelerating recovery. Additionally, probiotics and prebiotic-rich foods are gaining recognition for enhancing gut health, promoting nutrient absorption, and strengthening immune function, which are crucial in recovery processes. The concept of personalized nutrition, guided by genetic and metabolic profiling, is explored as a promising approach to tailor recovery strategies to individual physiological needs. Continued research into the long-term effects of supplements, the role of functional foods, and nutrient interactions is essential for developing more comprehensive and individualized recovery protocols. Integrating functional foods with personalized nutrition offers a holistic strategy to enhance recovery, optimize performance, and promote long-term health in athletes.
Molecular Subtypes of Vulvar Squamous Cell Carcinoma: the significance of HPV-independent/p53 Wild Type
Authors: Horn Lars-Christian , Brambs Christine E. , Gilks Blake , Hoang Lien , Singh Naveena , Hiller Ruth GG , Kathrin Hering , McAlpine Jessica N , Alfaraidi Mona , Aktas Bahriye , DORNHÖFER Nadja , Jamieson Amy , Höhn Anne Kathrin
Published: October 2024

Vulvar carcinoma is a rare disease, meeting the criteria of a “rare cancer”. The incidence has been increasing, especially in women <60 years of age. Squamous cell carcinoma (VSCC) accounts for an overwhelming majority of vulvar carcinomas and is the focus of this review. As with many cancers, the increased understanding of molecular events during tumorigenesis has led to emergence of molecular subclassification of VSCC, which is subclassified into those tumors arising secondary to high risk human papillomavirus infection (HPV associated, or HPVa) and those which arise independent of HPV (HPVi), most commonly in the setting of a chronic inflammatory condition of the vulvar skin. This latter group of HPVi VSCC arises in most cases secondary to mutations in TP53, but recently attention has focused on the uncommon TP53 wildtype HPVi VSCC. These three molecular subtypes of VSCC (HPVa, HPVi p53 abnormal, HPVi p53 wild type), and their precursor lesions, cannot be diagnosed based on routine histopathological examination and immunostaining for p53 and p16, as surrogate markers for TP53 mutation and high-risk HPV infection, respectively, is essential. Molecular subtyping of VSCC shows high reproducibility and provides important prognostic information. The HPVa VSCC have the most favorable prognosis while the HPVi VSCC with TP53 mutations (p53abn) have the worst prognosis, and the HPVi VSCC with wild type TP53 (p53wt) have an intermediate prognosis. In this review, we discuss the evidence supporting this molecular subclassification and its implications for diagnosis and treatment of VSCC and its precursors.
The Role of Data Governance in Ensuring System Success and Long-Term IT Performance: A Systematic Review
Authors: Lebaea Ramolatela , Roshe Yamkela , Ntontela Sinalo , Thango Bonginkosi A.
Published: October 2024

Data governance has emerged as a critical factor in determining the effectiveness and long-term stability of IT systems in today’s data-driven environment. It encompasses frameworks that guide organizations in managing data collection, storage, processing, usage, and sharing, while ensuring alignment with business objectives, compliance with regulations, and adherence to ethical standards. However, the complexities associated with data governance, particularly in the context of new technological models, pose significant challenges. This systematic review aims to explore the role of data governance in enhancing data quality, system stability, and regulatory compliance. It seeks to identify common issues, effective practices, and strategic implications for implementing data governance frameworks across diverse industries, focusing particularly on small and medium enterprises (SMEs). We conducted a systematic review of 68 eligible studies published between 2014 and 2024, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The included studies were assessed for risk of bias using the Cochrane Risk of Bias Assessment Tool. The review covered a range of study types, including qualitative (60%), quantitative (19%), and mixed-methods (21%) research, to provide a comprehensive understanding of data governance's impact on IT performance. The findings highlight that data governance significantly influences system success by improving data quality, operational efficiency, and regulatory compliance. Although qualitative studies predominantly emphasized in-depth analysis, a moderate representation of empirical validation through quantitative studies was observed. Common challenges identified include data migration issues, resistance to change, and budget constraints, particularly during system upgrades. Effective practices involve aligning data governance with business strategies, employing hybrid models, and regularly updating governance policies to adapt to technological advancements such as AI and big data. This review provides practical recommendations for IT managers and policymakers to enhance data governance frameworks. These include phased implementation approaches, the establishment of data governance committees, and the use of performance metrics to monitor data quality and system resilience. While significant progress has been made, further research is needed to address gaps related to emerging technologies and the unique challenges faced by SMEs in developing regions.
Invasive Technologies in Generative Artificial Intelligence
Authors: Coccia Mario
Published: October 2024

This study proposes a new concept that explains the modern technological change: technology invasiveness that breaks into a scientific and technological ecosystem, with accelerated diffusion of large quantities of products leading to main change in the innovation ecotone that transfers knowledge and know-how in businesses and markets. Invasive technologies conquer scientific, technological and business space of alternative technologies and expand the knowledge space of adjacent possible by introducing radical innovations that support dynamic interactions between new technologies and emerging development and applications. This theoretical approach is empirically verified in emerging path-breaking technology of transformer, a deep learning architecture having unsupervised and semi-supervised algorithms that create new contents and mimics human ability (Generative Artificial Intelligence). Statistical evidence here, based on patent analyses, reveals that the growth rate of transformer technology is 55.82% (over 2016-2023) more than double compared to 23.02% of all other technologies, such as Convolutional Neural Network: it is force that is revolutionizing the way societies interact with machines. Hence invasive technologies are considered as one of the major causes of global technological change and this study offers a profound exploration of how invasive technologies drive technological change, significantly contributing to our understanding of technological evolution’s dynamics and its societal and industry impacts.
Advancing Brain MRI Images Classification: Integrating VGG16 and ResNet50 with a Multi-verse Optimization Method
Authors: Sarshar Nazanin Tataei , Sadeghi Soroush , Kamsari Mohammadreza , Avazpour Mahrokh , Ghoushchi Saeid Jafarzadeh , Ranjbarzadeh Ramin
Published: October 2024

This research presents a novel methodology for classifying MRI images into two categories: tumor and non-tumor. The study utilizes a combination of two advanced Convolutional Neural Network (CNN) architectures, VGG16 and ResNet50, to address the challenges in analyzing the complexity and variability of brain MRI scans. The approach begins with a comprehensive preprocessing phase, where the MRI images are enhanced through techniques such as resizing, grayscale conversion, Gaussian blurring, and brain area isolation. Central to the approach is the application of the Multi-verse Optimizer (MVO), a metaheuristic algorithm inspired by theories of the multi-verse in physics. The MVO is utilized to optimize the parameters for data augmentation and to fine-tune the combination of trainable layers within the VGG16 and ResNet50 models. The results of this study indicate a high level of effectiveness of the combined CNN models, significantly enhanced by the MVO, in classifying MRI images. These models show marked improvements in accuracy, precision, and recall, underscoring their potential utility in enhancing brain tumor diagnosis. The paper concludes with an analysis of these findings, emphasizing the importance of this approach in medical imaging and suggesting potential avenues for future research in the area of automated MRI classification.
Analysis of Key Environmental Variables Affecting Fish Communities and Species Distribution in Asian Lotic Ecosystems
Authors: Kim Jae-Goo , Min Jeong-Ki , Choi Ji-Woong
Published: October 2024

In 2011, Korea installed artificial structures on four rivers to secure water resources and reduce flood damage; however, these structures have altered ecosystems and aquatic communities. This study analyzed fish communities and environmental variables at 72 sites in the Geumgang River. Fish communities and environmental variables before weir installation were examined using site data from 2008–2009. The results showed that Cyprinidae dominated the 70 observed species. A self-organizing map categorized the 72 sites into 4 groups based on fish communities. Sensitive and insectivorous species decreased, whereas tolerant and omnivorous species increased from Groups I to IV. Twenty-one indicator species were identified, with fewer and less distinct distribution patterns in Groups II and III than in Groups I and IV. The fish assessment index (FAI) showed a decline in grades A and B and an increase in grades C and D from Groups I to IV. Correlation analysis between FAI and environmental variables indicated that fish communities in the Geumgang River were mainly influenced by water quality, reflecting altitude gradients and pollution levels. This study’s findings are anticipated to significantly inform water management strategies for the Geumgang, Yeongsangang, Nakdonggang, and Hangang Rivers.
As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference
Authors: Thestrup Waade Peter , Lundbak Olesen Christoffer , Ehrenreich Laursen Jonathan , Nehrer Samuel William , Heins Conor , Friston Karl , Mathys Christoph
Published: October 2024

Active inference under the Free Energy Principle has been proposed as an across-scales compatible framework for understanding and modelling behaviour and self-maintenance. Crucially, a collective of active inference agents can, if they maintain a group-level Markov Blanket, constitute a larger group-level active inference agent with a generative model of its own. This potential for computational, scale-free structures speaks to the application of active inference to self-organizing systems across spatiotemporal scales, from cells to human collectives. Due to the difficulty of reconstructing the generative model — that explains the behaviour — of emergent group-level agents, there has been little research on this kind of multi-scale active inference. Here, we propose a data-driven methodology for characterising the relation between the generative model of a group-level agent and the dynamics of its constituent individual agents. We apply methods from computational cognitive modelling and computational psychiatry, applicable for active inference as well as other types of modelling approaches. Using a simple multi-armed bandit task as an example, we employ the new ActiveInference.jl library for Julia to simulate a collective of agents who are equipped with a Markov blanket. We use sampling-based parameter estimation to make inferences about the generative model of the group-level agent and we show that there is a non-trivial relationship between the generative models of individual agents and the group-level agent they constitute, even in this simple setting. Finally, we point to a number of ways in which this methodology might be applied to better understand the relations between nested active inference agents across scales.
Estimating Forest Above-Ground Carbon Stock Combining Landsat 8 OLI and Sentinel-2A Images, Topographic and Climatic Factors
Authors: Luo Kai , Feng Yafei , Liao Yi , Zhang Jialong , Qiu Bo , Yang Kun , Teng Chenkai , Yin Tangyan
Published: October 2024

Forest above-ground carbon stock (AGCS) is one of the primary ecological evaluation indicators, so it is crucial to estimate AGCS accurately. In this research, we added the climatic and topographic factors to the estimation process by a remote sensing approach to explore their impacts and to achieve more precise estimations. We model and predict AGCS by Random Forest (RF) based on sixty field sample plots of Pinus densata pure forests in southwest of China and the factors extracted from Landsat 8 OLI images (Source I), Sentinel-2A images (Source II), combined Landsat 8 OLI and Sentinel-2A images (Source III). We added the topographic and climatic factors to establish AGCS estimation model and compare the results. The topographic factors contain elevation, slope and aspect. Climatic factors contain mean annual temperature, annual precipitation, annual potential evapotranspiration and monthly mean potential evapotranspiration. It was found that the model based on Source III was better than Source I and Source II. Among the models without adding factors, the model based on Source III worked the best, with an R2 of 0.87, an RMSE of 10.81 t/ha, an rRMSE of 23.19%, and a P of 79.71%. Among the models that added topographic factors, the model based on Source III worked best after adding elevation, with an R2 of 0.89, an RMSE of 10.01 t/ha, an rRMSE of 21.47%, and a P of 82.17%. Among the models that added climatic factors, the model that was added the annual precipitation factor had the best modeling result, with an R2 of 0.90, an RMSE of 9.53 t/ha, an rRMSE of 20.59%, and a P of 83.00%. The prediction result exhibited that the AGCS of the Pinus densata forest in 2021 was 9,737,487.52 t. The combination of Landsat 8 OLI and sentinel-2A could improve the prediction accuracy of AGCS. The addition of annual precipitation can effectively improve the accuracy of AGCS estimation. Higher resolution of climate data is needed to enhance the modeling in the future work.
Physical Literacy and Physical Activity in Early Years Education: What’s Known, What’s Done, and What’s Needed?
Authors: Weir Natalie , Pringle Andy , Roscoe Clare M. P.
Published: October 2024

Physical literacy (PL) is increasingly recognised as essential to fostering lifelong physical activity (PA) engagement, particularly when nurtured in early childhood. However, there remains limited understanding of how key stakeholders in early years (EY) education perceive, value, and implement a PL informed approach. This exploratory study aimed to investigate a variety of EY stakeholders' knowledge and beliefs regarding PL and PA in relation to 3-5-year-olds. A concurrent mixed-methods approach was used, incorporating semi-structured expert interviews (n=11), focus groups (n=22), and a survey (n=210) to gather both qualitative and quantitative data. Thematic analysis was applied to identify key themes, and survey data was analysed to complement and triangulate qualitative findings. Findings revealed variation in stakeholders' awareness of PA recommendations, confusion over terminology, and the influence of environmental and policy constraints on practice. Stakeholders acknowledged the importance of PL but expressed uncertainty about the connection between academic theory and practical application. Resource limitations, conflicting priorities, and lack of training and policy support emerged as key barriers. Feedback on an educational PL-EY model was generally positive, emphasising its potential educational value while underscoring the need for clearer guidance and support. Given the pivotal role of EY education in shaping children’s behaviours, health, and well-being, this study highlights the necessity of a holistic approach to interventions, strong stakeholder involvement, and evidence-based practices to foster PL in EY children and raises critical questions about what effective interventions to develop PL in this age group should consider and look like.
Development of an Automotive-Relevant Recycling Process for Paper Fiber-Reinforced Polypropylene Composites
Authors: Grubb Cecile A , Mokhtarnejad Mahshid , Greene John , Misasi John , Keffer David J , Kardos Marton , Mainka Hendrik , Harper David P
Published: October 2024

The automotive industry is under growing pressure from regulatory agencies to improve the recyclability of their plastic components. Simultaneously, manufacturers are adopting natural fiber composites in vehicles to reduce carbon footprints and decrease reliance on petroleum-based materials. This presents a challenge at vehicle end-of-life however, as natural fiber-reinforced polymers are substantially more difficult to recycle than their unreinforced counterparts. This study investigated the development of a mechanical recycling process for paper fiber-reinforced polypropylene composites, focusing on the impact of injection molding parameters—specifically, injection temperature and rate—on the thermal, mechanical, and water uptake properties of the composites. The results showed that processing temperature had a greater influence on composite performance than injection rate, with some limited interaction effects between the two. Higher processing intensity damaged the paper fibers, increasing the number of nucleation sites and resulting in greater polypropylene crystallinity. These structural changes reduced tensile properties at higher intensities, while flexural properties improved. Objective function analysis was applied to identify optimal processing conditions, balancing these competing trends. Overall, the findings demonstrate that paper fiber-reinforced polypropylene composites can be recycled into automotive relevant injection molding compounds using conventional plastic manufacturing techniques, though careful tuning of processing parameters is essential to achieve optimal performance.
Synthesis and Therapeutic Potential of Urolithin-C on Oxidative Stress Induced Tissue Damage
Authors: Manjappa Vani K , Venkatappa Manjula M. , Elhindi Khalid M. , Sannaningaiah Devaraja
Published: October 2024

Ellagitannins (ETs) are the group of tannins found in fruits, nuts and seeds; they undergo hydrolysis in the human digestive tract to form ellagic acid (EA). EA further converted into various forms of Urolithin derivatives (A, B, C, D, M-5, M-6 and M-7) by gut micro biota. Perhaps, the pharmacological properties of said Urolithins were extensively studied, while, little is known about the therapeutic role of synthetic Urolithin-C on oxidative stress induced eryptosis and tissue damage. Therefore, in the current study we investigated the ameliorative role of chemically syn-thesized Urolithin-C on sodium nitrite and Diclofenac (DFC) induced eryptosis and vital organ damage respectively. Urolithin-C was synthesized using chemical method and characterized by High-Performance Liquid Chromatography (HPLC), Nuclear Magnetic Resonance (NMR), Fourier Transform Infrared Spectroscopy (FTIR), and Liquid Chromatography Mass Spectroscopy (LC-MS). The synthesized Urolithin-C scavenged free radicals (DPPH, H2O2) and reduced ferric iron to ferrous iron, revealed its antioxidant activity. The observed antioxidant potential of Uro-lithin-C was investigated in sodium nitrite induced stress in RBC and Diclofenac induced tissue damage in rats. Interestingly, Urolithin-C normalized the sodium nitrate-induced oxidative stress in red blood cells by regulating stress markers, such as lipid peroxidation (LPO), total thiol (TT), and protein carbonyl content (PCC), and endogenous antioxidant enzymes superoxide dis-mutase (SOD) and catalase (CAT) in a dose dependent manner. Similar effect was also observed in the tissue homogenates of liver, kidney, heart and pancreas taken from the Diclofenac injected Sprague Dawley rats. The tissue sections (liver, kidney, heart and pancreas) obtained from the Diclofenac (DFC) received rats showed massive destruction of hepatocytes, nephrons, cardiocytes and pancreas. However, Urolithin-C received rats tissue sections showed normal histology compared to the positive (Silymarin) control treated groups. In addition, Urolithin-C regulated the key tissue specific biochemical markers in DFC injected Sprague Dawley rats serum strengthened its tissue protective role. In conclusion, chemically synthesized Urolithin-C regulated NaNO2 and diclofenac induced oxidative stress in RBC and vital organs through its antioxidant property.
Prospects and Potential Applications of Nanomaterials in PCOS
Authors: Shi Mingqin , Li Xinyao , Xing Liwei , Li Zhenmin , Zhou Sitong , Wang Zihui , Zou Xuelian , She Yuqing , Zhao Rong , Qin Dongdong
Published: October 2024

Polycystic ovary syndrome (PCOS) is the predominant endocrine disorder among women of re-productive age and represents the leading cause of anovulatory infertility, which imposes a con-siderable health and economic burden. Currently, medications used to treat PCOS can lead to certain adverse reactions, such as affecting fertility and increasing the risk of venous thrombosis. Drug delivery systems utilizing nanomaterials, characterized by prolonged half-life, preci-sion-targeted delivery, enhanced bioavailability, and reduced toxicity, are currently being em-ployed in the management of PCOS. This innovative approach is gaining traction as a favored strategy for augmenting the therapeutic efficacy of medications. Consequently, this paper dis-cusses the roles of nanoparticles, nanocarriers, and targeted ligands within nanomaterial-based drug delivery systems, aiming to identify optimal methodologies for treating PCOS using nano-materials. Additionally, prospective research avenues concerning nanomaterial-based delivery systems in the context of PCOS, as well as the implications of existing insights on the advancement of novel therapies for PCOS, are highlighted.
Detection of Tert-Butylhydroquinone in Edible Oils Using Electrochemical Sensor Based on Nickel-Aluminium Layered Double Hydroxide@carbon Spheres Derived Carbon Composite
Authors: Zhang Jin , Chen Jingrong , Li Jiejun , Xie Yixi
Published: October 2024

Phenolic antioxidants such as tert-butylhydroquinone (TBHQ) are widely used by manufacturers to prevent deterioration and more stable preservation of cooking oils. Cooking oil is a necessary substance that everyone needs to consume every day, but the overuse of TBHQ will harm the quality of food and public health, and many countries have set up limited standards for the use of TBHQ, therefore, it is very necessary to research and design an efficient detection technology for TBHQ. In this work, we grew NiAl-LDH, a nickel-aluminium double hydroxide, on glucose carbon spheres (GC), and formed porous carbon nanomaterials (named NiAl-LDH@GC-800) after the pyrolysis process. The NiAl-LDH@GC-800 material was fabricated on GCEs for sensors with remarkable sensitivity to TBHQ, with a low limit of detection (LOD) of 8.2 nM and possessed excellent detection linear range (20 nM ~ 300 µM). The prepared electrochemical sensor successfully detected TBHQ detection in edible oils in life, including chilli oil, peanut oil, and canola oil.
Enhancing Pain Management and Psychological Recovery in Earthquake Victims: The Impact of Catheterization Assessed by QoR-15
Authors: Mendes Ergun , Adiyeke Ozal , Sarban Onur , Civan Melih , Altas Okyar , Korucu Alperen , Ozcan Funda Gumus , Oksuz Gozen
Published: October 2024

Background/Objectives: After the earthquakes in Turkey, many citizens were injured, and a long process requiring physiological and psychological treatments started in the ongoing process. The aim of this study was to observe the pain and psychological changes in earthquake victims in light of the QoR-15 score. Methods: After approval by the local ethics committee (Decision No. 2023-194), earthquake victims with catheters in trauma and reconstructive surgery were retrospectively evaluated. Demographic and catheterization data were collected. Baseline, 24-hour, and 72-hour QoR-15 (Quality of Recovery-15) and VAS (Visual Analog Scala) scores were compared for changes over time. Results: A total of 40 catheters were placed in 29 patients (after the exclusion of children, 36 catheters were evaluated in 26 (15 w/11 m) patients). The mean age of the patients was 35.57 ± 13.69 years, and the duration of catheterization was 8 (4.25–12.75) days. Infusion of 0.1% bupivacaine 0.5–1 mg/kg/24 h was started routinely. The QoR-15 scores of the patients at baseline, 24-hour, and 72-hour were 80.45 ± 17.76, 95.27 ± 15.16, and 101.06 ± 15.52, respectively (p<0.001). The VAS scores of the patients at baseline, 24-hour, and 72-hour were 4.61 ± 1.41, 1.79 ± 1.36, and 0.76 ± 0.86, respectively (p<0.001). Conclusions: In this study, a significant improvement in QoR-15 and VAS scores was achieved as a result of catheter insertion in earthquake victims. Considering that post-traumatic injuries require repeated surgeries and that pain aggravates the existing psychological state, it can be said that catheterization is beneficial.
Adaptive Beamforming, Cell-Free Resource Allocation and NOMA in Large-Scale Wireless Networks
Authors: (P.G.) Panagiotis Gkonis , Lavdas (S.L.) Spyros , (G.V.) George Vardoulias , Trakadas (P.T.) Panagiotis , Sarakis Lambros , Papadopoulos Konstantinos
Published: October 2024

The goal of the study presented in this work is to evaluate the performance of a proposed adaptive beamforming approach when combined with non-orthogonal multiple access (NOMA) in cell-free massive multiple input multiple output (CF m-MIMO) orientations. In this context, cooperative beamforming is employed taking into consideration the geographically adjacent access points (APs) of a virtual cell, aiming to minimize co-channel interference (CCI) among mobile stations (MSs) participating in NOMA transmission. Performance is evaluated statistically via extensive Monte Carlo (MC) simulations in a two-tier wireless orientation. As results indicate, for high data rate services various key performance indicators (KPIs) can be improved compared to orthogonal multiple access, such as the minimum number of users in the topology as well as the available PRBs for downlink transmission. Although in NOMA transmission more directional beamforming configurations are required to compensate for the increased CCI levels, the increase in the number of hardware elements is reduced compared to the corresponding gain in the considered KPIs.
Surgical Management of Thoracic Spinal Extradural Arachnoid Cysts: A Case Report
Authors: Heo Kyu Sik , Kim Sung Jin , Kim Young Jin
Published: October 2024

Spinal extradural arachnoid cysts (SEACs) are exceptionally rare and require advanced imaging for an accurate diagnosis and surgical planning. Magnetic resonance imaging and computed tomography myelography play a pivotal role in delineating cyst characteristics and guiding effective interventions. Laminectomy, coupled with laminoplasty, has emerged as a strategic approach to decompress the spinal cord while preserving spinal alignment. This technique mitigates the risk of postoperative complications and facilitates reoperations if recurrence takes place. The integration of a detailed radiological assessment with meticulous surgical planning is crucial for managing SEACs and optimizing outcomes. This paper presents a case of a 33-year-old man with multiple SEACs at the thoracic level who was successfully treated with a surgical intervention, exemplifying the discussed approach.
Comparative Analysis of Smart and Traditional Evacuation Strategies in Underground Mines Utilizing Virtual Reality Simulations
Authors: Gaab Simone , Moniri-Morad Amin , Harris Frederick C. , Sattarvand Javad
Published: October 2024

Underground mining operations inherently involve significant risks, such as the collapse of surrounding rock or fires. While infrequent, the potentially catastrophic nature of these events highlights the essential need for swift and secure evacuation procedures, ensuring the safety and survival of mineworkers in such situations. The traditional static evacuation strategy, relying on exit signs or guidance markers, may become blocked or barely discernible in low-visibility circumstances resulting from smoke or dust. This paper investigates the feasibility of integrating smart evacuation technology into underground mine operations by examining its effectiveness compared to traditional practices. This procedure involves real-time evacuation guidance of individuals along optimized paths to egress, effectively avoiding danger zones. A virtual simulation environment was built based on the actual layout of a gold mine in Nevada. In this instance, the simulation process involved evacuating a group of participants employing both traditional practices and smart evacuation strategies equipped with live assistance. The findings revealed a notable contrast in the effectiveness of the total evacuation duration between the traditional and smart evacuation strategies. The smart method achieved the most substantial decrease in total evacuation time, almost a 40% reduction. Additionally, 83% of participants expressed a preference for the smart evacuation strategies compared to the traditional practices, with all participants agreeing that the smart evacuation strategy has the potential to improve mine safety.
Advancing community-based conservation in eastern Africa and the determinants of progress
Authors: Mwangi Evans Mungai
Published: October 2024

Success in community-based conservation is pegged on benefits exceeding costs. A recent appraisal based on literature, field analysis and experience led to the realization that divergent interests, uncertainty over access and payback are constant concerns. Resource stewardship and governance are wanting, while the devolution of rights is still primordial. Public involvement is at a decisive point with major initiatives attributable to local actors. The rapid rise of wildlife conservancies marks a key milestone where they are now critical and irreplaceable in addressing biodiversity challenges. Sustained progress will require improved relationships among key stakeholders and strengthening of all local actors.
YOLOX-DW: A Fine-Grained Object Detection Algorithm for Remote Sensing Images
Authors: Gao Meijing , Yan Yonghao , Fan Xiangrui , Sun HuanYu , Chen Sibo , Chen Xu , Sun Bingzhou , Guan Ning
Published: October 2024

Fine-grained aircraft target detection in remote sensing holds significant research value and practical applications, particularly in military defense and precision strikes. Given the complexity of remote sensing images, where targets are often small and similar within categories, detecting these fine-grained targets is challenging. To address this, we constructed a fine-grained dataset of remotely sensed airplanes; for the problems of remote sensing fine-grained targets with obvious head-to-tail distributions and large variations in target sizes, we proposed the YOLOX-DW fine-grained target detection and recognition algorithm. First, for the problem of unbalanced category distribution, we adopt an adaptive sampling strategy. In addition, we construct a deformable convolutional block and improve the decoupling head structure to improve the detection effect of the model on deformed targets. Then, we design a localization loss function, which is used to improve the model's localization ability for targets of different scales. The experimental results show that our algorithm improves the overall accuracy of the model by 4.1% compared to the baseline model, and improves the detection accuracy of small targets by 12.2%. The ablation and comparison experiments also prove the effectiveness of our algorithm.
Harvesting and agro-ecological zones effects on sustainability of Boswellia sacra in Oman.
Authors: Amri Mohsin Al , Shanfari Ahmed Al
Published: October 2024

The frankincense tree (Boswellia sacra) is the most famous economic plant in Oman. Recently, tree populations have rapidly decreased because of incorrect tree-tapping practices. In Oman, the scientific knowledge of frankincense trees is still insufficient, especially in terms of tree yield at different agro-ecological zones, the effect of the resin extraction method and cutting frequency on yield, and plant regeneration. The present study was carried out in four different agro-ecological zones. A total of 180 healthy, non-harvested frankincense trees with four replications were studied. The maximum yield of olibanum from an individual tree was obtained at the fourth tapping pick. The average yields of resin in four locations were 650g, 620g, 360g, and 470g per tree per season in 10 picks. The study showed a positive correlation between olibanum yield and stem diameter, crown size, trunk size, and the number of tapping spots. Whereas, an inverse correlation was found with tree flowering and elevation. Sustainable harvesting of frankincense trees involved limiting cut depth in the phloem, ensuring not to reach hardwood, avoiding cutting in practical places in the tree bole, keeping a distance between cuts, using the traditional tapping method, and specifying periods of time in which tapping is prohibited.
Fuzzy adaptive fractional order PD permanent magnet synchronous motor speed control based on torque compensation
Authors: Liu Deijun , Han Junjie , Chen Guangda , Cheng Yanming , Liang Xinyue , Song Chao
Published: October 2024

The permanent magnet synchronous motor (PMSM) control system is a nonlinear, strongly coupled complex system, and in order to improve the overall control performance of the PMSM, an Fuzzy adaptive fractional order PD(FFPD) control strategy based on torque observation(TO) compensation is proposed. The parameters of the fractional-order PD controller are optimized online using fuzzy logic reasoning, and a graphical design method of the fractional-order PD controller parameters based on frequency domain performance indicators is proposed to obtain the initial values of the fuzzy adaptive fractional-order PD controller parameters graphically and intuitively. A load torque observer is designed to improve the anti-interference capability of the system by converting the observed load torque into compensation current in equal proportion. Simulation and experimental results show that the strategy proposed in this paper has good dynamic and static performance and robustness.
Digital Twin-Assisted Graph Matching Multi-Task Object Detection Method in Complex Traffic Scenarios
Authors: Li Mi , Liu Chuhui , Pan Xiaolong , Li Ziyue
Published: October 2024

Addressing the challenges of time-consuming and labor-intensive traffic data collection and annotation, along with the limitations of current deep learning models in practical applications, this paper proposes a cross-domain object detection transfer method based on digital twins. A digital twin traffic scenario is constructed using a simulation platform, generating a virtual traffic dataset. To address distributional discrepancies between virtual and real datasets, a multi-task object detection algorithm based on graph matching is introduced. The algorithm employs a graph matching module to align the feature distributions of the source and target domains, followed by a multi-task network for object detection. An attention mechanism is then applied for instance segmentation, with the two tasks exhibiting different noise patterns that mutually enhance the robustness of the learned representations. Additionally, a multi-level discriminator is designed, leveraging both low- and high-level features for adversarial training, thus enabling tasks to share useful information, which improves the performance of the proposed method in object detection tasks.