bluuebunny/crossref_metadata_2025 huggingface dataset:
Ibuprofen Removal by Aluminum-Modified Activated Carbon (AC@Al) Derived from Coconut Shells
Authors: Malouchi Natalia , Tolkou Athanasia K. , Kyzas George Z. , Katsoyiannis Ioannis A.
Published: October 2024

In this study, a new composite adsorbent consisting of aluminum-modified activated carbon (abbreviated hereafter AC@Al) was synthesized for the removal of the Ibuprofen compound (IBU), a non-steroidal anti-inflammatory drug (NSAID). Coconut shells were used as a source material for activated carbon, which was then modified with AlCl3 to improve its properties. Adsorbent dosage, pH and initial IBU concentration, as well as contact time and temperature, are some of the factors affecting adsorption that were investigated in this work. Specifically, at pH 2.0 ± 0.1 with the application of 0.5 g/L of AC@Al in 100 mg/L of IBU, more than 90% was removed, reaching 100% with the addition of 1.0 g/L of the adsorbent. The IBU kinetic data followed the pseudo-second-order kinetic model. Non-linear Langmuir, Freundlich, Sips and Redlich–Peterson isotherm models were used to interpret the adsorption. According to the correlation coefficient (R2), the Langmuir model was found to best match the experimental data. The maximum adsorption capacity (Qmax) according to the Langmuir model was found to be as high as 2053 mg/g. The positive values of ΔH0 (42.92 kJ/mol) confirmed the endothermic nature of the adsorption. Due to the increasing values of ΔG0 with temperature, the adsorption of IBU onto AC@Al proved to be spontaneous. Also, the adsorbent was regenerated and reused for five cycles. This study shows that AC@Al could be used as a cost-effective adsorbent.
Evaluating Clear Aligners Versus Fixed Appliances for Periodontal Patients: A Comprehensive Narrative Review of Current Evidence
Authors: Samulak Renata , Suwała Mariusz , Górski Bartłomiej , Machoy Monika
Published: October 2024

Periodontal patients may face orthodontic problems because of bone support loss, such as maxillary incisor proclination, spacing, rotation, extrusion, pathologic tooth migration (PTM) or traumatic occlusion. Orthodontic treatment is therefore an element within the comprehensive treatment of periodontitis after the periodontal condition has stabilized. The presence of fixed appliances (FAs) promotes the accumulation of bacterial biofilm and impedes hygiene procedures. The increasing popularity of clear aligner (CA) treatment is due to the convenience of use, less discomfort, better esthetics, easier hygiene, lower failure rate, and shorter, less frequent visits. Therefore, the question arises whether treatment with aligners is a good solution for periodontal patients. To answer this question, the PubMed/Medline, Cochrane Library and EMBASE databases were searched using the following keywords: periodontitis, orthodontic treatment, clear aligners, multibracket orthodontic appliances, fixed appliance, root resorption, gingival recession and pathologic tooth migration. The search strategy identified 18 relevant studies. A total of 1090 participants took part in the analyzed studies. The available literature was analyzed in terms of the occurrence of root apex resorption, the possibility of treating pathologic tooth migration, the occurrence of gingival recession, periodontal health status and occlusal stability in patients treated with CAs and FAs. Despite statistically significant differences in terms of Plaque Index (PI), probing depth (PD), apical root resorption and gingival recession favor the use of CAs. However, these values are mostly of no clinical significance. It is possible to treat PTM with CAs, but it is limited by the high degree of tooth mobility and incisor inclination. Obtaining perfect occlusion is comparably difficult in both CA and FA treatment. When planning orthodontic treatment in patients with reduced periodontium, the use of both CAs and FAs should be considered. The choice of method would ultimately depend on the patient’s dental condition.
Mechanical Properties of Fully-Grouted Bolts Support Based on Compression Tests of Anchored Rock Mass
Authors: Han Tao , Jin Changyu , Li Guang , Wang Qiang , Hou Lingyue , Liu Huiyang
Published: October 2024

The mechanical properties of fully-grouted bolt support are critical for the safety of support engineering works. To study the influences of factors including the bolt length and diameter, strength of the rock, and fracture angle on the mechanical properties of fully-grouted bolt support, compression tests were conducted on an anchored rock mass, considering the shortcomings of pullout tests on bolts. The discrete element software PFC2D (4.0) was adopted for numerical simulation and analysis from two aspects, namely, the stress distribution and anchorage force supplied by such bolts. The research found that by increasing the bolt diameter and length as well as the strength of the rock, the maximum anchorage force of bolts increases. Whereas the stress distribution of all bolts increases at first and then decreases along the bolts, and there is only one peak on the stress distribution curves, which also gradually shifts to a greater depth. In a fractured rock mass, the maximum anchorage force of bolts decreases, then increases (and is minimized at a fracture angle of 45°) with the decrease in fracture angle. The influence of fractures with different angles on the stress distribution of bolts is mainly reflected in the fracture zone. The bolt stress decreases abruptly in the zone with a fracture angle of 90°, forming a valley. The bolt stress increases suddenly in the zones with fracture angles of 60° and 45°, thus forming peaks. The bolt stress does not increase or decrease suddenly in the zone with a fracture angle of 30°. Therefore, it necessitates consideration of the influences of fractures on the anchorage force and the selection of bolts of appropriate size during anchorage design. After installation, the bolt stress should be monitored for stability and early warning of anchored rock mass according to changes in the stress provided.
Incorporation of Cyanobacteria and Microalgae in Yogurt: Formulation Challenges and Nutritional, Rheological, Sensory, and Functional Implications
Authors: Albuquerque Rosana Correia Vieira , Silva Carlos Eduardo de Farias , Carneiro Wanderson dos Santos , Andreola Kaciane , da Gama Brígida Maria Villar , Silva Albanise Enide da
Published: October 2024

This review presents an approach to the incorporation of cyanobacteria and microalgae in yogurts and explores their impact on the nutritional, rheological, sensory, and antioxidant qualities of these products. First, the yogurt market context and its relationship with nutritional quality are outlined, emphasizing the quest for functional foods that meet consumer demands for healthy and nutritious products. A discussion of the incorporation of cyanobacteria and microalgae, especially Spirulina platensis, in foods, particularly yogurt, is then presented, highlighting the nutritional and functional benefits that this type of biomass can provide to the final product. The fermentation process and the quantity of algae to be incorporated are discussed to understand their fundamental role in the characteristics of the final product. In addition, this article considers some challenges such as sensory and rheological changes in the product resulting from the interaction of milk, algal biomass, and the fermentation process. Addressing these challenges involves delineating how these interactions contribute to changes in the traditionally consumed product, while obtaining a pro- and prebiotic product is crucial for creating an innovative dairy product that diversifies the market for derived dairy products with increased functional properties.
Invariance Principle and Berry–Esseen Bound for Error Variance Estimator for Pth-Order Nonlinear Autoregressive Models
Authors: Liang Kaiyu , Zhang Yong , Ding Xue
Published: October 2024

The invariance principle and Berry–Esseen bound for an error variance estimator based on the residuals are established by using a Taylor expansion and the classical invariance principle and Berry–Esseen bound for independent random variables. Some examples are given to illustrate their applications.
Exchange Formulae for the Stieltjes–Poisson Transform over Weighted Lebesgue Spaces
Authors: Srivastava Hari M. , Negrín Emilio Ramón , Maan Jeetendrasingh
Published: October 2024

This paper aims to develop exchange formulae for the Stieltjes–Poisson transform by using Mellin-type convolutions in the context of weighted Lebesgue spaces. A key result is the introduction of bilinear and continuous Mellin-type convolutions, expanding the scope of the analysis to include the space of weighted L1 functions and the space of continuous functions vanishing at infinity.
Slow H2S-Releasing Donors and 3D Printable Arrays Cellular Models in Osteo-Differentiation of Mesenchymal Stem Cells for Personalized Therapies
Authors: Arciero Ilaria , Buonvino Silvia , Melino Sonia
Published: October 2024

The effects of the hydrogen sulfide (H2S) slow-releasing donor, named GSGa, a glutathione-conjugate water-soluble garlic extract, on human mesenchymal stem cells (hMSCs) in both bidimensional (2D) and three-dimensional (3D) cultures were investigated, demonstrating increased expression of the antioxidant enzyme HO-1 and decreased expression of the pro-inflammatory cytokine interleukin-6 (IL-6). The administration of the H2S donor can therefore increase the expression of antioxidant enzymes, which may have potential therapeutic applications in osteoarthritis (OA). Moreover, GSGa was able to promote the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs), but not of cardiac mesenchymal stem cells (cMSCs) in a 2D culture system. This result highlights the varying sensitivity of hMSCs to the H2S donor GSGa, suggesting that the induction of osteogenic differentiation in stem cells by chemical factors is dependent on the tissue of origin. Additionally, a 3D-printable mesenchymal stem cells–bone matrix array (MSCBM), designed to closely mimic the stiffness of bone tissue, was developed to serve as a versatile tool for evaluating the effects of drugs and stem cells on bone repair in chronic diseases, such as OA. We demonstrated that the osteogenic differentiation process in cMSCs can be induced just by simulating bone stiffness in a 3D system. The expression of osteocalcin, RUNX2, and antioxidant enzymes was also assessed after treating MSCs with GSGa and/or increasing the stiffness of the culture environment. The printability of the array may enable better customization of the cavities, enabling an accurate replication of real bone defects. This could optimize the BM array to mimic bone defects not only in terms of stiffness, but also in terms of shape. This culture system may enable a rapid screening of antioxidant and anti-inflammatory compounds, facilitating a more personalized approach to regenerative therapy.
Efficacy of Back Bracing in Treating Chronic Low Back Pain
Authors: Vick John S. , Zimmerman Jessica , Hicks Stephanie , Biekert Abigail , Abd-Elsayed Alaa
Published: October 2024

Chronic low back pain (CLBP) negatively impacts quality of life and contributes to a significant economic burden. One conservative management strategy for CLBP is lumbar back bracing. Despite the benefits of back bracing for improving pain and function, there remains hesitance to use the therapy long term due to unfounded fear related to muscle weakness, deconditioning, or joint contracture. Objective: The purpose of this study was to examine the outcomes for patients with CLBP who were managed with lumbar back bracing and physical therapy. Methods: This was a single-site, retrospective chart review. Results: Patients were included in the study if they were treated for CLBP with back bracing for at least one hour daily and physical therapy for twelve weeks. Pain was assessed at three, six, and twelve months using the 11-point Visual Analogue Scale (VAS). Function was assessed at three months using the Oswestry Disability Index (ODI). The VAS score reduced from 6.28 +/− 2.32 to 3.96 +/− 2.66 at three months (p < 0.001) for 198 patients. At six and twelve months, the VAS score reduced to 3.74 +/− 2.73 (p < 0.001) and 3.23 +/− 2.29 (p < 0.001), respectively. The total ODI score for 199 patients improved from 46.56 +/− 15.30 to 33.13 +/− 19.99 (p < 0.001) at three months. Conclusion: Back bracing in combination with physical therapy is effective for treating low back pain.
Study on Mechanical Properties and Safety of Ultra-Thin Reactive Powder Concrete Prefabricated Slabs Applied to I-Beam Joints of Bridges
Authors: Liu Bin , Liu Xiang , Jia Buyu , Yan Quansheng , Yang Zheng
Published: October 2024

Conventional methods for constructing bridge I-beam joints face several challenges, including heavy precast slabs, complicated transportation and lifting procedures, strict accuracy requirements, lengthy construction timelines, and increased safety risks. The use of ultra-thin, high-performance reactive powder concrete (RPC) prefabricated slabs can effectively resolve these issues. However, research in this area is limited, leaving our understanding of the strength and feasibility of ultra-thin RPC slabs for I-beam joints incomplete. Therefore, this study conducts a thorough examination of the strength and safety aspects of these slabs to assess their practical suitability. First, 11 numerical models are generated to evaluate the bearing capacity of ultra-thin RPC slabs, determining key factors such as cracking load, ultimate load, and safety factor according to relevant codes and standards. This establishes a theoretical foundation for practical engineering applications. Next, several sets of ultra-thin RPC slabs that meet material performance criteria are prefabricated to study the mechanical properties under equivalent concentrated load. Finally, two types of in situ temporary construction loads are encountered in the safety calculations of the RPC slabs. This study aims to provide a robust theoretical framework and technical support for the application and advancement of ultra-thin RPC prefabricated slabs in bridge I-beam joints.
Avian Models for Human Carcinogenesis—Recent Findings from Molecular and Clinical Research
Authors: Niebora Julia , Data Krzysztof , Domagała Dominika , Józkowiak Małgorzata , Barrett Saoirse , Norizadeh Abbariki Tannaz , Bryja Artur , Kulus Magdalena , Woźniak Sławomir , Ziemak Hanna , Piotrowska-Kempisty Hanna , Antosik Paweł , Bukowska Dorota , Mozdziak Paul , Dzięgiel Piotr , Kempisty Bartosz
Published: October 2024

Birds, especially the chick and hen, have been important biomedical research models for centuries due to the accessibility of the avian embryo and the early discovery of avian viruses. Comprehension of avian tumor virology was a milestone in basic cancer research, as was that of non-viral genesis, as it enabled the discovery of oncogenes. Furthermore, studies on avian viruses provided initial insights into Kaposi’s sarcoma and EBV-induced diseases. However, the role of birds in human carcinogenesis extends beyond the realm of virology research. Utilization of CAM, the chorioallantoic membrane, an easily accessible extraembryonic tissue with rich vasculature, has enabled studies on tumor-induced angiogenesis and metastasis and the efficient screening of potential anti-cancer compounds. Also, the chick embryo alone is an effective preclinical in vivo patient-derived xenograft model, which is important for the development of personalized therapies. Furthermore, adult birds may also closely resemble human oncogenesis, as evidenced by the laying hen, which is the only animal model of a spontaneous form of ovarian cancer. Avian models may create an interesting alternative compared with mammalian models, enabling the creation of a relatively cost-effective and easy-to-maintain platform to address key questions in cancer biology.
Synthesis and Bioactivity Assessment of N-Aryl-Azasesamins
Authors: Wu Jiri , Qi Xubing , Jaiswal Yogini S. , Lin Cui , Song Xun , Xie Xinrong , Su Shaoyang , Guan Yifu , Williams Leonard L. , Bian Hedong
Published: October 2024

Sesamin, a tetrahydrofuran lignan, has gained significant attention over the past few decades due to its versatile medicinal activities. However, until now, the research on sesamin analogues has not been explored extensively. In this study, a series of new N-aryl-azasesamins were synthesized for the first time using sesamin as a raw material. The mechanism of the key breakage of the ethereal bond of the tetrahydrofuran ring in sesamin has been studied. The configuration of C6 in N-aryl-azasesamins was confirmed through NMR and X-ray single crystal refraction analyses. The results showed that the configuration of N-aryl-azasesamins was opposite to sesamin in C6. Subsequently, the N-aryl-azasesamins were evaluated for their antifungal and antitumor activities via micro-broth dilution and MTT assays. It was observed that none of the N-aryl-azasesamins exhibited inhibitory activity against the growth of C. albicans and C. neoformans at a concentration of 100 μg/mL. Most analogues showed no activity against HepG2 cells. However, 21c and 21k demonstrated antitumor activity after 24 h of incubation with IC50 values of 6.49 μM and 4.73 μM, respectively. These results suggest that some N-aryl-azasesamins exhibit significantly enhanced antitumor activity compared with sesamin.
Switch/Sucrose Non-Fermentable (SWI/SNF) Complex—Partial Loss in Sinonasal Squamous Cell Carcinoma: A High-Grade Morphology Impact and Progression
Authors: Cruz-Tapia Roberto Onner , Cano-Valdez Ana María , Meneses-García Abelardo , Correa-Arzate Lorena , Molotla-Fragoso Adriana , Villagómez-Olea Guillermo , Sevilla-Lizcano Diana Brisa , Portilla-Robertson Javier
Published: October 2024

Sinonasal carcinomas are aggressive neoplasms that present a high morbidity and mortality rate with an unfavorable prognosis. This group of tumors exhibits morphological and genetic diversity. Genetic and epigenetic alterations in these neoplasms are the current targets for diagnosis and treatment. The most common type of cancer originating in the sinonasal tract is sinonasal squamous cell carcinomas (SNSCCs), which present different histological patterns and variable histological aggressiveness. A significant number of alterations have been reported in sinonasal tumors, including deficiencies in the Switch/Sucrose non-fermentable (SWI/SNF) chromatin remodeling complex. In the sinonasal tract, deficiencies of the subunits SMARCB1/INI1, SMARCA4/BRG1, and SMARCA2 have been noted in carcinomas, adenocarcinomas, and soft tissue tumors with a distinctive high-grade morphology and a fatal prognosis. Objective: The objective of this study is to identify the status of the SWI/SNF complex using immunohistochemistry in sinonasal squamous cell carcinomas and their association with morphology and survival. Methods: A total of 103 sinonasal carcinomas with different grades of squamous differentiation were analyzed; the selection was based on those cases with high-grade morphology. The carcinomas were then evaluated immunohistochemically for SMARCB1 and SMARCA4 proteins. Their expression was compared with the biological behavior and survival of the patients. Results: Among the SNSCCs, 47% corresponded to the non-keratinizing squamous cell carcinoma (NKSCC) type with high-grade characteristics, 40% were keratinizing squamous cell carcinomas (KSCCs), 9% were SMARCB1-deficient carcinomas, and 4% were SMARCA4-deficient carcinomas. Mosaic expression for SMARCB1 (NKSCC—33%; KSCC—21.9%) and SMARCA4 (NKSCC—14.6%; KSCC—12.2%) was identified, showing an impact on tumor size and progression. Conclusions: We identified that that the partial loss (mosaic expression) of SMARCB1 in SNSCCs is associated with high-grade malignant characteristics and a negative effect on patient survival; meanwhile, SMARCA4-mosaic expression in SNSCCs is associated with high-grade malignant characteristics and an increase in tumor size concerning the intact SMARCA4.
Targeting PGK1: A New Frontier in Breast Cancer Therapy Under Hypoxic Conditions
Authors: Cui Jiayong , Chai Shengjun , Liu Rui , Shen Guoshuang
Published: October 2024

Breast cancer represents one of the most prevalent malignant neoplasms affecting women, and its pathogenesis has garnered significant scholarly interest. Research indicates that the progression of breast cancer is intricately regulated by glucose metabolism. Under hypoxic conditions within the tumor microenvironment, breast cancer cells generate ATP and essential biosynthetic precursors for growth via the glycolytic pathway. Notably, phosphoglycerate kinase 1 (PGK1) is intimately associated with the regulation of hypoxia-inducible factors in breast cancer and plays a crucial role in modulating glycolytic processes. Further investigation into the role of PGK1 in breast cancer pathogenesis is anticipated to identify novel therapeutic targets and strategies. This review consolidates current research on the regulation of glucose metabolism and the function of PGK1 in breast cancer within hypoxic conditions. It aims to offer a significant theoretical foundation for elucidating the mechanisms underlying breast cancer progression and metastasis, thereby facilitating the development of innovative treatment approaches.
Dystocia in Dairy Cows and Heifers: A Review with a Focus on Future Perspectives
Authors: Tsaousioti Angeliki , Basioura Athina , Praxitelous Anastasia , Tsousis Georgios
Published: October 2024

Dairy cow management has evolved tremendously in recent decades, particularly regarding reproductive techniques. The widespread adoption of synchronization protocols, sexed semen, beef semen in dairy cows, reproductive biotechnologies such as in vivo-derived (IVD) or in vitro-produced embryos (IVP), and precision livestock farming is transforming the daily practices of dairy farmers and veterinarians. These implementations are typically adapted in different ways when applied to the breeding of heifers or cows. Considering these developments, dystocia—a significant welfare and productivity concern—may warrant reevaluation. The aforementioned changes are likely to have a substantial impact on its prevalence, severity, and outcome. This review aims to address the main aspects of dystocia in dairy cows and heifers, with a particular focus on the potential impact of recent advances in reproductive and calving management.
Prevention of Overhead Shoulder Injuries in Throwing Athletes: A Systematic Review
Authors: Moiroux--Sahraoui Ayrton , Mazeas Jean , Delgado Numa , Le Moteux Cécile , Acco Mickael , Douryang Maurice , Bjerregaard Andreas , Forelli Florian
Published: October 2024

(1) Background: Shoulder pathologies are mostly found in overhead sports. Many risk factors have been identified, in particular a deficit in the kinetic chain. The aim of this review was to find out whether prevention by strengthening the kinetic chain can have an impact on the rate of shoulder injury in overhead pitching athletes. (2) Methods: A systematic review of the literature was carried out, including studies on the role of the kinetic chain in the prevention of overhead athletes. The studies used were works published over the last 10 years searched on PubMed, Cochrane Library, PEDro and Science Direct. They were also analyzed by methodological quality scales: the PEDro scale and the Newcastle–Ottawa scale. (3) Results: Eight studies met the inclusion criteria. The studies analyzed revealed a significant correlation between the use of the kinetic chain and the prevention of shoulder injuries, associating factors such as muscle strength, physical performance in tests (CMJ, FMS), static and dynamic balance and the ability to transfer energy from the lower to the upper body. (4) Conclusions: It is important to integrate core stability work and lower limb strengthening to minimize excessive stress on the shoulder complex, while optimizing force production and performance.
Development of a Short-Form Hwa-Byung Symptom Scale Using Machine Learning Approaches
Authors: Kwon Chan-Young , Lee Boram , Kim Sung-Hee , Jeong Seok Chan , Kim Jong-Woo
Published: October 2024

Background/Objectives: Hwa-byung (HB), also known as “anger syndrome” or “fire illness”, is a culture-bound syndrome primarily observed among Koreans. This study aims to develop a short-form version of the HB symptom scale using machine learning approaches. Methods: Utilizing exploratory factor analysis (EFA) and various machine learning techniques (i.e., XGBoost, Logistic Regression, Random Forest, Support Vector Machine, Decision Tree, and Multi-Layer Perceptron), we sought to create an efficient HB assessment tool. A survey was conducted on 500 Korean adults using the original 15-item HB symptom scale. Results: The EFA revealed two distinct factors: psychological symptoms and somatic manifestations of HB. Statistical testing showed no significant differences between using different numbers of items per factor (ANOVA: F = 0.8593, p = 0.5051), supporting a minimalist approach with one item per factor. The resulting two-item short-form scale (Q3 and Q10) demonstrated high predictive power for the presence of HB. Multiple machine learning models achieved a consistent accuracy (90.00% for most models) with high discriminative ability (AUC = 0.9436–0.9579), with the Multi-Layer Perceptron showing the highest performance (AUC = 0.9579). The models showed balanced performance in identifying both HB and non-HB cases, with precision and recall values consistently around 0.90. Conclusions: The findings of this study highlighted the effectiveness of integrating EFA and artificial intelligence via machine learning in developing practical assessment tools. This study contributes to advancing methodological approaches for scale development and offers a model for creating efficient assessments of Korean medicine.
Quantifying Well Clear Thresholds for UAV in Conjunction with Trajectory Conformity
Authors: Meng Linghang , Zhang Hongyang , Zhao Yifei , Low Kin Huat
Published: October 2024

The rapid advancement of unmanned aerial vehicles (UAVs) has introduced new challenges in overseeing and managing their flight operations due to their diverse flight dynamics and performance metrics. To address these complexities, this study introduces a concept of trajectory conformity aimed at enhancing the supervision and control of UAV flights. Trajectory conformity, from a regulatory perspective, is defined as the distribution of deviations between a UAV’s actual flight path and its intended trajectory, offering a measure of system-wide operational error. The concept of conformity is hoped to simplify and strengthen the monitoring process to ensure conflict-free drone flying. The present work is also concerned with the development of a comprehensive UAV collision risk model grounded in trajectory conformity analysis. The normality and homogeneity of UAV trajectory deviations are validated by evaluating the trajectory data obtained from real-world UAV flights. Well clear thresholds between two UAVs operating in three orthogonal directions within the same airspace have been established by the developed model. The results obtained demonstrate the effectiveness in omni-encounter scenarios, underscoring the potential to strengthen safety measures. The present work is expected to enhance UAV safety systems, such as detect and avoid (DAA) and unmanned aircraft system traffic management (UTM), by enabling real-time collision warnings within predefined safety thresholds, supporting proactive risk mitigation. Furthermore, the model’s versatility allows it to be applied to various UAV operational aspects in future works, including route planning, flight procedure design, airspace capacity assessments, and establishment of separation minima.
Propagation Speeds of Relativistic Conformal Particles from a Generalized Relaxation Time Approximation
Authors: Kandus Alejandra , Calzetta Esteban
Published: October 2024

The propagation speeds of excitations are a crucial input in the modeling of interacting systems of particles. In this paper, we assume the microscopic physics is described by a kinetic theory for massless particles, which is approximated by a generalized relaxation time approximation (RTA) where the relaxation time depends on the energy of the particles involved. We seek a solution of the kinetic equation by assuming a parameterized one-particle distribution function (1-pdf) which generalizes the Chapman–Enskog (Ch-En) solution to the RTA. If developed to all orders, this would yield an asymptotic solution to the kinetic equation; we restrict ourselves to an approximate solution by truncating the Ch-En series to the second order. Our generalized Ch-En solution contains undetermined space-time-dependent parameters, and we derive a set of dynamical equations for them by applying the moments method. We check that these dynamical equations lead to energy–momentum conservation and positive entropy production. Finally, we compute the propagation speeds for fluctuations away from equilibrium from the linearized form of the dynamical equations. Considering relaxation times of the form τ=τ0(−βμpμ)−a, with −∞<a<2, where βμ=uμ/T is the temperature vector in the Landau frame, we show that the Anderson–Witting prescription a=1 yields the fastest speed in all scalar, vector and tensor sectors. This fact ought to be taken into consideration when choosing the best macroscopic description for a given physical system.
Patent Keyword Analysis Using Regression Modeling Based on Quantile Cumulative Distribution Function
Authors: Park Sangsung , Jun Sunghae
Published: October 2024

Patents contain detailed information of researched and developed technologies. We analyzed patent documents to understand the technology in a given domain. For the patent data analysis, we extracted the keywords from the patent documents using text mining techniques. Next, we built a patent document–keyword matrix using the patent keywords and analyzed the matrix data using statistical methods. Each element of the matrix represents the frequency of a keyword that occurs in a patent document. In general, most of the elements were zero because the keyword becomes a column of the matrix even if it occurs in only one document. Due to this zero-inflated problem, we experienced difficulty in analyzing patent keywords using existing statistical methods such as linear regression analysis. The purpose of this paper is to build a statistical model to solve the zero-inflated problem. In this paper, we propose a regression model based on quantile cumulative distribution function to solve this problem that occurs in patent keyword analysis. We perform experiments to show the performance of our proposed method using patent documents related to blockchain technology. We compare regression modeling based on a quantile cumulative distribution function with convenient models such as linear regression modeling. We expect that this paper will contribute to overcoming the zero-inflated problem in patent keyword analysis performed in various technology fields.
Advancing Sustainable Mobility: A Data Acquisition System for Light Vehicles and Active Mobility
Authors: Verzeroli Matteo , Gaioni Luigi , Galliani Andrea , Ghislotti Luca , Lazzaroni Paolo , Re Valerio
Published: October 2024

Active mobility and light vehicles, such as e-bikes, are gaining increasing attention as sustainable transportation alternatives to internal combustion solutions. In this context, collecting comprehensive data on environmental conditions, vehicle performance, and user interaction is crucial for improving system efficiency and user experience. This paper presents a data acquisition system designed to collect data from multiple sensor platforms. The architecture is optimized to maintain low power consumption and operate within limited computational resources, making it suitable for real-time data acquisition on light vehicles. To achieve this, a data acquisition module was developed using a single-board computer integrated with a custom shield, which also captures data related to the assistance of an e-bike motor through a wireless interface. The paper provides an in-depth discussion of the architecture and software development, along with a detailed overview of the sensors used. A demonstrator was created to verify the system architecture idea and prove the potentialities of the system overall. The demonstrator has been qualified by professional and semi-professional riders in the framework of the Giro-E, a cyclist event which took place in May 2024, on the same roads of the Giro d’Italia. Finally, some preliminary analyses on the data acquired are provided to show the performance of the system, particularly in reconstructing the user behavior, the environmental parameters, and the type of road.
An Enhanced Multiscale Retinex, Oriented FAST and Rotated BRIEF (ORB), and Scale-Invariant Feature Transform (SIFT) Pipeline for Robust Key Point Matching in 3D Monitoring of Power Transmission Line Icing with Binocular Vision
Authors: Nusantika Nalini Rizkyta , Xiao Jin , Hu Xiaoguang
Published: October 2024

Power transmission line icing (PTLI) poses significant threats to the reliability and safety of electrical power systems, particularly in cold regions. Accumulation of ice on power lines can lead to severe consequences, such as line breaks, tower collapses, and widespread power outages, resulting in economic losses and infrastructure damage. This study proposes an enhanced image processing pipeline to accurately detect and match key points in PTLI images for 3D monitoring of ice thickness using binocular vision. The pipeline integrates established techniques such as multiscale retinex (MSR), oriented FAST and rotated BRIEF (ORB) and scale-invariant feature transform (SIFT) algorithms, further refined with m-estimator sample consensus (MAGSAC)-based random sampling consensus (RANSAC) optimization. The image processing steps include automatic cropping, image enhancement, feature detection, and robust key point matching, all designed to operate in challenging environments with poor lighting and noise. Experiments demonstrate that the proposed method significantly improves key point matching accuracy and computational efficiency, reducing processing time to make it suitable for real-time applications. The effectiveness of the pipeline is validated through 3D ice thickness measurements, with results showing high precision and low error rates, making it a valuable tool for monitoring power transmission lines in harsh conditions.
An Applied Analysis of Securing 5G/6G Core Networks with Post-Quantum Key Encapsulation Methods
Authors: Scalise Paul , Garcia Robert , Boeding Matthew , Hempel Michael , Sharif Hamid
Published: October 2024

Fifth Generation (5G) cellular networks have been adopted worldwide since the rollout began around 2019. It brought with it many innovations and new services, such as Enhanced Mobile Broadband (eMBB), Ultra Reliable and Low-Latency Communications (URLLC), and Massive Internet of Things (mIoT). Furthermore, 5G introduced a more scalable approach to network operations using fully software-based Virtualized Network Functions (VNF) in Core Networks (CN) rather than the prior hardware-based approach. However, while this shift towards a fully software-based system design provides numerous significant benefits, such as increased interoperability, scalability, and cost-effectiveness, it also brings with it an increased cybersecurity risk. Security is crucial to maintaining trust between vendors, operators, and consumers. Cyberattacks are rapidly increasing in number and sophistication, and we are seeing a shift towards zero-trust approaches. This means that even communications between VNFs inside a 5G core must be scrutinized and hardened against attacks, especially with the advent of quantum computers. The National Institute of Standards and Technology (NIST), over the past 10 years, has led efforts to standardize post-quantum cryptography (PQC) to protect against quantum attacks. This paper covers a custom implementation of the open-source free5GC CN, to expand its HTTPS capabilities for VNFs by introducing PQC Key Encapsulation Methods (KEM) for Transport Layer Security (TLS) v1.3. This paper provides the details of this integration with a focus on the latency of different PQC KEMs in initial handshakes between VNFs, on packet size, and the implications in a 5G environment. This work also conducts a security comparison between the PQC-equipped free5GC and other open-source 5G CNs. The presented results indicate a negligible increase in UE connection setup duration and a small increase in connection setup data requirements, strongly indicating that PQC KEM’s benefits far outweigh any downsides when integrated into 5G and 6G core services. To the best of our knowledge, this is the first work incorporating PQC into an open-source 5G core. Furthermore, the results from this effort demonstrate that employing PQC ciphers for securing VNF communications results in only a negligible impact on latency and bandwidth usage, thus demonstrating significant benefits to 5G cybersecurity.
Dynamic Modeling of a HeXe-Cooled Mobile Nuclear Reactor with Closed Brayton Cycle
Authors: Deng Jiaolong , Guan Chaoran , Liu Xiaojing , Chai Xiang
Published: October 2024

Helium-xenon (HeXe)-cooled mobile nuclear reactors have promising potential in future low-carbon energy systems. However, there is currently a lack of fast and reliable tools for analyzing the complicated dynamic characteristics of such systems. In this study, we developed a comprehensive dynamic modeling approach for a HeXe-cooled nuclear power system coupled with a closed Brayton cycle (CBC). The system’s key components, including the reactor, printed circuit heat exchanger (PCHE), and turbomachinery, are lumped-modeled to capture their time-varying behavior. A step-solving algorithm that incorporates HeXe mass conservation iteration is designed. The verification results demonstrate that the dynamic program is robust and reliable, with each time step converging within 25 iterations and the HeXe mass remaining within the range of 3.755 ± 0.01 kg throughout the simulation meeting the law of mass conservation. Then, a 1500 s frozen start-up simulation for the coupled system is conducted, in which the CBC is started in the first 500 s by increasing the main shaft speed to 40% of the rated value, and then the reactor is started by inserting external reactivity between 500 and 800 s. Both the dynamic process and the steady-state performance after the start-up are analyzed. The results show that the system achieved a stable electrical output of 5.7 MWe with a thermal efficiency of 32.5%. This study lays a solid foundation for future work aimed at improving the overall efficiency and performance of HeXe-cooled nuclear power systems.
Experimental Study of a Silica Sand Sensible Heat Storage System Enhanced by Fins
Authors: Niksiar Paniz , Rogillio Claire , Torab Hamid , Tiari Saeed
Published: October 2024

This study aims to assess the thermal performance of silica sand as a heat storage medium within a shell-and-tube sensible heat storage thermal energy system that operates using water as the heat transfer fluid. Two types of silica sand were analyzed, fine sand and coarse sand, to determine which was the best for heat transfer and storage. It was found that the fine sand, which had smaller particles compared to the coarse sand, enhanced the heat transfer in the system. The fine sand required 11.86 h to charge using the benchmark case and 17.58 h to discharge, whereas the coarse sand required 13.36 h to charge and 16.55 h to discharge. Methods of enhancement are also explored by comparing the system performance with the inclusion of four different configurations of copper fins to investigate against a benchmark case without fins in the system with fine sand. When equipped with four radial fins, the system demonstrated a significant enhancement, reducing charging and discharging times by 59.02% and 69.17%, respectively, compared to the baseline. Moreover, the system exhibited an even greater improvement with eight radial fins, cutting charging and discharging times by 63.74% and 78.5%, respectively, surpassing the improvements achieved with four radial fins. The ten annular fins decreased the charging time by 42.58% and the discharge by 62.4%, whereas the twenty annular fins decreased the charging by 56.24% and the discharging by 68.26% when compared to the baseline.
Energy Optimization in Ultrasound Tomography Through Sensor Reduction Supported by Machine Learning Algorithms
Authors: Baran Bartłomiej , Rymarczyk Tomasz , Majerek Dariusz , Szyszka Piotr , Wójcik Dariusz , Cieplak Tomasz , Gąsior Marcin , Marczuk Marcin , Wąsik Edmund , Gauda Konrad
Published: October 2024

This paper focuses on reducing energy consumption in ultrasound tomography by utilizing machine learning techniques. The core idea is to investigate the feasibility of minimizing the number of measurement sensors without sacrificing prediction accuracy. This article evaluates the quality of reconstructions derived from data collected through two or three measurement channels. In subsequent steps, machine learning models are developed to predict the number, location, and size of the objects. A reliable object detection method is introduced, requiring less information than traditional signal analysis from multiple channels. Various machine learning models were tested and compared to validate the approach, with most demonstrating high accuracy or R2 scores in their respective tasks. By reducing the number of sensors, the goal is to lower energy usage while maintaining high precision in localization. This study contributes to the ongoing research on energy efficiency in sensing and localization, especially in environments where resource optimization is crucial, such as remote or resource-limited settings.
Distribution of Salts in Milk and Cheese: Critical Methodological Aspects
Authors: Deshwal Gaurav Kr , van der Meulen Liesbeth , Huppertz Thom
Published: October 2024

The salt fractions of milk consist of cations (e.g., Ca, Mg, and Na) and anions (e.g., phosphate, citrate, and chloride). These salts are present as free ions or in complexes with other ions or proteins, primarily the caseins. Furthermore, significant levels of Ca and phosphate are also found in insoluble form, inside the casein micelles. The distribution of salts between this micellar phase and the soluble phase is important for the stability and properties of milk and dairy products. Various processes, such as (ultra-)centrifugation, (ultra-)filtration, dialysis, and selective precipitation have been used to separate the micellar and soluble phases in milk and dairy products to allow for studying the salts’ distribution between these phases. These different methods can lead to different levels of soluble salts because the salts in the supernatant from centrifugation, the permeate from ultrafiltration, and the diffusate from dialysis can differ notably. Hence, understanding which components are fractionated with these techniques and how this affects the levels of the soluble salts determined is critical for milk and dairy products. Applying the aforementioned methods to cheese products is further challenging because these methods are primarily developed for fractionating the soluble and micellar phases of milk. Instead, methods that analyze salts in water-soluble extracts, or soluble phases expressed from cheese by pressing or centrifugation are typically used. This review focuses on the significance of salt distribution and variations in salt fractions obtained using different methodologies for both milk and cheese.
A Fractal Study on Random Distribution of Recycled Concrete and Its Influence on Failure Characteristics
Authors: Guo Lixia , Liu Qingxiang , Zhong Ling , Yang Yuqing , Zhang Jianwei
Published: October 2024

In order to quantitatively describe the influence of aggregate distribution on crack development and peak stress of recycled aggregate concrete, a multifractal spectrum theory was proposed to quantitatively characterize aggregate distribution in specimens. A mesomechanical model of reclaimed aggregate concrete mixed with natural aggregate and artificial aggregate was constructed. Numerical simulation tests were conducted on the uniaxial compression mechanical behavior of 25 groups of sample models with the same proportion and different aggregate distribution forms. Based on the box dimension theory, the multiple fractal spectrum method was used to quantitatively characterize the aggregate distribution form, and the key factors affecting cracks were explored based on the gray correlation degree. The research results show that the aggregate distribution in recycled aggregate concrete has multifractal characteristics. The multifractal spectrum was used to effectively characterize the aggregate distribution pattern, which can enlarge local details and provide new ideas for the quantitative analysis of the damage mode of recycled concrete. Secondly, by establishing a statistical model of the correlation between the multifractal spectrum width of the aggregate distribution pattern and the crack distribution box dimension, it was found that there was a positive correlation between the two, that is, the greater the multifractal spectrum width of the aggregate distribution pattern, the greater the crack box dimension, and the more complex the crack distribution. The complexity of aggregate distribution is closely related to the irregularity and complexity of mesoscopic failure crack propagation in recycled concrete specimens. In addition, gray correlation theory was applied to analyze the key factors affecting the formation of cracks in the specimens. The results showed that aggregate distribution had a first-order correlation with crack formation, and changes in aggregate distribution were an important factor affecting the performance of recycled concrete. Secondly, the poor mechanical properties of NAITZ led to obvious material damage, while NCA and MZ had a significant impact on the skeleton effect in the stress–strain process due to their large areas. This study deepens people’s understanding of the damage characteristics and cracking failure modes of recycled concrete. The study verifies the feasibility of the application of recycled aggregates and provides a valuable reference for engineering practice.