bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Leakage Flow Rate and Blow-Down in Brush Seals via 2D CFD Simulation with Porosity Correction
Authors: Kwon Jeong Woo , Ahn Joon
Published: September 2024

Brush seals are extensively used in rotating equipment, such as gas turbines and compressors, providing effective sealing while accommodating radial, axial, and angular movements between components. In this study, the performance of brush seals with and without clearances was predicted through axisymmetric 2D computational fluid dynamic (CFD) simulations using a porous media model. Because the accurate modeling of a brush seal requires the appropriate porosity to be determined and the flow resistance to be calculated, a porosity correction was performed based on the brush seal’s geometry and pressure ratio. The corrected porosity was then used to calculate the flow resistance and the leakage flow rate was predicted. Based on the results, the corrected porosity significantly improved the accuracy of the previously unreliable leakage flow rate predictions, regardless of the presence of clearances. For cases with a clearance, the blow-down effect was determined through CFD simulations for the given geometry and was compared with experimental data. The leakage flow rate predictions were highly accurate, with a relative error of less than 5% across a pressure ratio range of 1.5–4.
A Robust and Optimal Iterative Algorithm Employing a Weight Function for Solving Nonlinear Equations with Dynamics and Applications
Authors: Abdullah Shahid , Choubey Neha , Dara Suresh , Junjua Moin-ud-Din , Abdullah Tawseef
Published: September 2024

This study introduces a novel, iterative algorithm that achieves fourth-order convergence for solving nonlinear equations. Satisfying the Kung–Traub conjecture, the proposed technique achieves an optimal order of four with an efficiency index (I) of 1.587, requiring three function evaluations. An analysis of convergence is presented to show the optimal fourth-order convergence. To verify the theoretical results, in-depth numerical comparisons are presented for both real and complex domains. The proposed algorithm is specifically examined on a variety of polynomial functions, and it is shown by the efficient and accurate results that it outperforms many existing algorithms in terms of speed and accuracy. The study not only explores the proposed method’s convergence properties, computational efficiency, and stability but also introduces a novel perspective by considering the count of black points as an indicator of a method’s divergence. By analyzing the mean number of iterations necessary for methods to converge within a cycle and measuring CPU time in seconds, this research provides a holistic assessment of both the efficiency and speed of iterative methods. Notably, the analysis of basins of attraction illustrates that our proposed method has larger sets of initial points that yield convergence.
Spatio-Functional Nadaraya–Watson Estimator of the Expectile Shortfall Regression
Authors: Alamari Mohammed B. , Almulhim Fatimah A. , Kaid Zoulikha , Laksaci Ali
Published: September 2024

The main aim of this paper is to consider a new risk metric that permits taking into account the spatial interactions of data. The considered risk metric explores the spatial tail-expectation of the data. Indeed, it is obtained by combining the ideas of expected shortfall regression with an expectile risk model. A spatio-functional Nadaraya–Watson estimator of the studied metric risk is constructed. The main asymptotic results of this work are the establishment of almost complete convergence under a mixed spatial structure. The claimed asymptotic result is obtained under standard assumptions covering the double functionality of the model as well as the data. The impact of the spatial interaction of the data in the proposed risk metric is evaluated using simulated data. A real experiment was conducted to measure the feasibility of the Spatio-Functional Expectile Shortfall Regression (SFESR) in practice.
Phytochemistry and Evaluation of the Anti-Inflammatory Activity of the Hydroethanolic Extract of Virola elongata (Benth.) Warb. Stem Bark
Authors: Di Serio Bruna Fioravante , Muller Jessica de Araujo Isaias , Silva Marcelo José Dias , Figueiredo Fabiana de Freitas , Martins Domingos Tabajara de Oliveira
Published: September 2024

Background: Previous studies of the hydroethanolic extract of Virola elongata inner stem bark (HEVe) have demonstrated its antioxidant, gastroprotective, and antiulcer properties, but have not evaluated its anti-inflammatory potential. Methods: HEVe was obtained by maceration and phytochemically analyzed. Its systemic anti-inflammatory activity was assessed by its effect on lipopolysaccharide (LPS)-induced peritonitis in mice. HEVe gel (HEgVe) was employed to evaluate topical anti-inflammatory activity by measuring the ear edema resulting from croton-oil-induced dermatitis in mice. A cell viability assay was conducted to determine the non-cytotoxic concentrations of the HEVe. RAW 264.7 cells were stimulated by LPS to determinate cytokine and nitric oxide production. Results: A phytochemical analysis of the HEVe revealed the presence of phenolic acids, neolignans, flavonoids, and monomeric catechins. The oral treatment of acute peritonitis with HEVe reduced the total leukocytes, neutrophils, TNF-α, and IL-1β and elevated IL-10 levels. The application of the HEgVe reduced local edema. The HEVe on the RAW 264.7 cells exhibited no cytotoxicity, and the cells with HEVe displayed reduced TNF-α, IL-1β, and NO levels and increased IL-13 levels. Conclusions: HEVe demonstrated systemic and topical multitarget anti-inflammatory activity, likely due to the combined effects of secondary metabolites. HEVe emerges as a promising herbal remedy for inflammation with minimal cytotoxicity, emphasizing its potential therapeutic significance.
Enhancing Sex Estimation Accuracy with Cranial Angle Measurements and Machine Learning
Authors: Toneva Diana , Nikolova Silviya , Agre Gennady , Harizanov Stanislav , Fileva Nevena , Milenov Georgi , Zlatareva Dora
Published: September 2024

The development of current sexing methods largely depends on the use of adequate sources of data and adjustable classification techniques. Most sex estimation methods have been based on linear measurements, while the angles have been largely ignored, potentially leading to the loss of valuable information for sex discrimination. This study aims to evaluate the usefulness of cranial angles for sex estimation and to differentiate the most dimorphic ones by training machine learning algorithms. Computed tomography images of 154 males and 180 females were used to derive data of 36 cranial angles. The classification models were created by support vector machines, naïve Bayes, logistic regression, and the rule-induction algorithm CN2. A series of cranial angle subsets was arranged by an attribute selection scheme. The algorithms achieved the highest accuracy on subsets of cranial angles, most of which correspond to well-known features for sex discrimination. Angles characterizing the lower forehead and upper midface were included in the best-performing models of all algorithms. The accuracy results showed the considerable classification potential of the cranial angles. The study demonstrates the value of the cranial angles as sex indicators and the possibility to enhance the sex estimation accuracy by using them.
Itching for Answers: A Comprehensive Review of Cholestatic Pruritus Treatments
Authors: Gabrielli Filippo , Crepaldi Eleonora , Cavicchioli Alessia , Rivi Marco , Costanzo Arianna Carmen , Cursaro Carmela , Andreone Pietro
Published: September 2024

Cholestasis is a clinical and laboratory syndrome indicating impaired bile production or excretion. One of the hallmark symptoms of cholestasis is pruritus. Itch can be severe and debilitating for patients, impacting their quality of life similarly to pain, and, in some cases, it can be refractory. Current therapies like anion exchange resins and rifampicin, offer partial relief but with side effects. Effective, well-tolerated treatments are urgently needed. This literature review examines existing options (bile acid sequestrants, antihistamines, opioid antagonists, sertraline, and rifampicin) and explores novel therapies (monoclonal antibodies, PPAR agonists, and bile-acid-based therapies). We analyze mechanisms, limitations, and adverse effects to aid clinicians and researchers. Novel approaches include monoclonal antibodies to inhibit bile recirculation and PPAR agonists targeting pruritus signaling. Despite the limited current options, ongoing research promises better treatments for cholestatic pruritus, addressing its distressing impact. In summary, cholestasis-associated pruritus poses a significant challenge with limited treatments. Advancements in understanding its pathophysiology offer hope for more effective therapies in the future.
The Important Role of Aquaglyceroporin 7 in Health and Disease
Authors: Liu Jing , Xia Ziwei , Peng Shuhong , Xia Juanjuan , Xu Ruixiang , Wang Xin , Li Fei , Zhu Weifeng
Published: September 2024

Aquaporins (AQPs) are highly conserved small transmembrane proteins that facilitate the transport of water and small solutes across cell membranes. Aquaglyceroporin 7 (AQP7), a significant member of the AQP family, is widely distributed throughout the body. For years, AQP7 was predominantly recognized for its role as a small-molecule transporter, facilitating the passage of small molecular substances. However, growing studies have revealed that AQP7 is also involved in the regulation of lipid synthesis, gluconeogenesis, and energy homeostasis, and it is intimately linked to a variety of diseases, such as obesity, type 2 diabetes mellitus, cardiovascular diseases, cancer, and inflammatory bowel disease. This article presents a comprehensive overview of the structure of AQP7, its regulatory mechanisms, its vital roles in both healthy and diseased states, and potential therapeutic advancements. We hope that these studies will serve as a valuable reference for the development of future treatments and diagnostic protocols targeting AQP7.
Caenorhabditis elegans as a Model to Study Aging and Photoaging
Authors: Jeayeng Saowanee , Thongsroy Jirapan , Chuaijit Sirithip
Published: September 2024

Caenorhabditis elegans (C. elegans) has emerged as an outstanding model organism for investigating the aging process due to its shortened lifespan, well-defined genome, and accessibility of potent genetic tools. This review presents the current findings on chronological aging and photoaging in C. elegans, exploring the elaborate molecular pathways that control these processes. The progression of chronological aging is characterized by a gradual deterioration of physiological functions and is influenced by an interaction of genetic and environmental factors, including the insulin/insulin-like signaling (IIS) pathway. In contrast, photoaging is characterized by increased oxidative stress, DNA damage, and activation of stress response pathways induced by UV exposure. Although the genetic mechanisms of chronological aging in C. elegans have been characterized by extensive research, the pathways regulating photoaging are comparatively less well-studied. Here, we provide an overview of the current understanding of aging research, including the crucial genes and genetic pathways involved in the aging and photoaging processes of C. elegans. Understanding the complex interactions between these factors will provide invaluable insights into the molecular mechanisms underlying chronological aging and photoaging and may lead to novel therapeutic approaches and further studies for promoting healthy aging in humans.
Influence of Excavation Radius on Behavior of Circular Foundation Pits Supported by Prefabricated Recyclable Structures: Full-Scale Experimental and Numerical Analysis
Authors: Chen Lichao , Guo Chengchao , Pan Yanhui , Liang Huqing , Tang Mengxiong , Zhai Kejie
Published: September 2024

A foundation pit’s excavation area, which is determined by its radius in a circular foundation pit, exerts a considerable influence on the pit’s behavior. Using a full-scale experiment on a circular foundation pit retained by a prefabricated recyclable supporting structure (PRSS), this study develops a series of axisymmetric numerical models to systematically investigate the influence of excavation radius on the pit’s deformation, stress, and stability. Furthermore, simulation results from axisymmetric models are compared with those from plane strain models to illustrate the influence mechanism. The results show that at a given excavation depth, the deflection and bending moments of the supporting piles, the earth pressure on the non-excavation side, and ground surface settlement increase with the enlarged excavation radius, but the increase rate progressively decreases. However, the foundation pit’s safety factor decreases with an increasing excavation radius and gradually stabilizes. When the excavation radius exceeds 50 m, its influence on the foundation pit’s behavior significantly diminishes. The axisymmetric model results closely approximate those from the plane strain models, suggesting that the spatial arching effects of the circular foundation pit can be disregarded.
Assessment of Energy Recovery Potential in Urban Underground Utility Tunnels: A Case Study
Authors: Wei Tong , Fan Mingyue , Xu Zijun , Li Weijun , Gu Zhaolin , Luo Xilian
Published: September 2024

Underground spaces contain abundant geothermal energy, which can be recovered for building ventilation, reducing energy consumption. However, current research lacks a comprehensive quantitative assessment of its energy recovery. This research evaluates the energy recovery potential of the Xingfu Forest Belt Urban Underground Utility Tunnels. Field experiments revealed a 7 °C temperature difference in winter and a 2.5 °C reduction during the summer-to-autumn transition. A computational fluid dynamics (CFD) model was developed to assess the impact of design and operational factors such as air exchange rates on outlet temperatures and heat exchange efficiency. The results indicate that at an air change rate of 0.5 h−1, the tunnel outlet temperature dropped by 10.5 °C. A 200 m tunnel transferred 8.7 × 1010 J of heat over 30 days, and a 6 m × 6 m cross-sectional area achieved 1.1 × 1011 J of total heat transfer. Increasing the air exchange rate and cross-sectional area reduces the inlet–outlet temperature difference while enhancing heat transfer capacity. However, the optimal buried depth should not exceed 8 m due to cost and safety considerations. This study demonstrates the potential of shallow geothermal energy as an eco-friendly and efficient solution for enhancing building ventilation systems.
Luxury of Traditional Architecture: Emergence of Hanoks as Luxury Housing
Authors: Yun Jieheerah
Published: September 2024

This study explores the recent emergence of traditional Korean houses and hanoks as markers of cultural capital in Seoul, South Korea. While the ownership of detached houses itself can be a symbol of wealth in Seoul, traditional-style houses have become increasingly associated with luxurious living, particularly after the successful remodeling of hanoks in metropolitan settings such as Bukchon in Seoul. This study employs the critical luxury studies method to analyze the recent rise in hanok construction/remodeling among elites, and illustrates how traditional architectural forms have become status markers. Although the regeneration of traditional houses in cities has been examined from the perspective of gentrification or touristic cultural consumption, less academic attention has been placed on the phenomenon from the perspective of the homeowners’ taste. This study examines how traditional architecture has become a form of acceptable luxury through a media analysis of published articles and interviews with the residents of hanoks. This study argues that protecting endangered traditions and rich sensory experiences function as important moralizing factors in luxury housing, indicating that sociocultural valuation becomes as significant as market valuation.
GFRP-Reinforced Concrete Columns: State-of-the-Art, Behavior, and Research Needs
Authors: Elkafrawy Mohamed , Gowrishankar Prathibha , Aswad Nour Ghazal , Alashkar Adnan , Khalil Ahmed , AlHamaydeh Mohammad , Hawileh Rami
Published: September 2024

This comprehensive review paper delves into the utilization of Glass Fiber-Reinforced Polymer (GFRP) composites within the realm of concrete column reinforcement, spotlighting the surge in structural engineering applications that leverage GFRP instead of traditional steel to circumvent the latter’s corrosion issues. Despite a significant corpus of research on GFRP-reinforced structural members, questions about their compression behavior persist, making it a focal area of this review. This study evaluates the properties of GFRP bars and their impact on the structural behavior of concrete columns, addressing variables such as concrete type and strength, cross-sectional geometry, slenderness ratio, and reinforcement specifics under varied loading protocols. With a dataset spanning over 250 publications from 1988 to 2024, our findings reveal a marked increase in research interest, particularly in regions like China, Canada, and the United States, highlighting GFRP’s potential as a cost-effective and durable alternative to steel. However, gaps in current knowledge, especially concerning Ultra-High-Performance Concrete (UHPC) reinforced with GFRP, underscore the necessity for targeted research. Additionally, the contribution of GFRP rebars to compressive column capacity ranges from 5% to 40%, but current design codes and standards underestimate this, necessitating new models and design provisions that accurately reflect GFRP’s compressive behavior. Moreover, this review identifies other critical areas for future exploration, including the influence of cross-sectional geometry on structural behavior, the application of GFRP in seismic resistance, and the evaluation of the size effect on column strength. Furthermore, the paper calls for advanced studies on the long-term durability of GFRP-reinforced structures under various environmental conditions, environmental and economic impacts of GFRP usage, and the potential of Artificial Intelligence (AI) and Machine Learning (ML) in predicting the performance of GFRP-reinforced columns. Addressing these research gaps is crucial for developing more resilient and sustainable concrete structures, particularly in seismic zones and harsh environmental conditions, and fostering advancements in structural engineering through the adoption of innovative, efficient construction practices.
Modular Universal Tumor and Revision System Prostheses in Patients with Bone Cancer of the Lower Limbs: A Narrative Review of Functional Outcomes
Authors: Ferrara Paola E. , Ariani Mariantonietta , Codazza Sefora , Aprovitola Adelaide , Polisano Daniele , Ronconi Gianpaolo
Published: September 2024

The optimal management of bone tumors requires a multidisciplinary strategy to guarantee high-quality care. At specialized centers, the medical team responsible for managing patients with bone cancer comprises oncologists, surgeons, radiologists, pathologists, and rehabilitation specialists. The goal of treatment is to achieve long-term survival with minimal disability and pain. Postoperative rehabilitation is a fundamental therapeutic approach to enhance functionality and sustain the utmost quality of life following a limb-sparing surgery. Currently, megaprostheses are used for reconstructing bone defects after tumor resection, but in the literature, only a few studies have investigated rehabilitation outcomes in terms of functionality and impact on daily activities. This narrative review explores the functional and quality of life outcomes after the implantation of MUTARS® prostheses in patients with lower extremity bone tumors. A comprehensive search was conducted on PubMed and Scopus using the following MESH terms: “MUTARS”, “Megaprosthesis”, “bone”, “tumors”, “metastasis”, “lower limb”, “rehabilitation”, “outcome”, and “quality of life”, and 10 studies were included. The most frequent oncological pathology was found to be primitive bone tumors treated with modular prostheses. The outcome measures used were the Henderson et al. classification, Harris Hip Scale, Musculoskeletal Tumor Society score, Visual Analog Scale, Range Of Motion, Karnofsky Performance Scale, and quality of life questionnaire. MUTARS® is a well-established treatment option after bone tumor resection, although it involves extensive and complex post-resection reconstruction that exposes joints and tissues to substantial mechanical stress. Proper rehabilitation after MUTARS® surgery is a fundamental therapeutic step, although there is still insufficient evidence in the literature focusing on functional and rehabilitative outcomes. Therefore, more studies and guidelines are needed to define standardized rehabilitation protocols for clinical practice after orthopedic oncologic surgery.
Optimizing Algal Oil Extraction and Transesterification Parameters through RSM, PCA, and MRA for Sustainable Biodiesel Production
Authors: Tang Lingdi , Otho Ali Raza , Laghari Mahmood , Junejo Abdul Rahim , Brohi Sheeraz Aleem , Chandio Farman Ali , Otho Sohail Ahmed , Hao Li , Mari Irshad Ali , Dahri Jahangeer , Channa Jamshed Ali
Published: September 2024

This study presents a comprehensive optimization of algal oil extraction and transesterification for sustainable biodiesel production. Freshwater Spirogyra algae underwent Soxhlet extraction using n-hexane. response surface methodology (RSM), principal component analysis (PCA), and multivariate regression analysis (MRA) were employed to investigate the effects of biomass–solvent ratio (BSR), algae particle size (APS), and extraction-contact time (E-CT) on algal oil yield (AOY). The extracted oil was then converted to biodiesel via transesterification, and the impacts of the methanol–oil ratio (MOR) and transesterification-contact time (T-CT) on biodiesel conversion efficiency (BCE) were analyzed. Results demonstrate that optimal BSR, APS, and E-CT for maximal AOY are 1:7, 400 µm, and 3–4 h, respectively. For transesterification, a MOR of 12:1 and a T-CT of 4 h yielded the highest BCE. Predictive models exhibited exceptional accuracy, with R2 values of 0.916 and 0.950 for AOY and BCE, respectively. The produced biodiesel complied with ASTM D6751 and EN 14214, showcasing its potential for renewable energy applications.
Correction: Pittala et al. The VDAC1-based R-Tf-D-LP4 Peptide as a Potential Treatment for Diabetes Mellitus. Cells 2020, 9, 481
Authors: Pittala Srinivas , Levy Idan , De Soumasree , Pandey Swaroop Kumar , Melnikov Nataly , Hyman Tehila , Shoshan-Barmatz Varda
Published: September 2024

In the original publication [...]
The Effect of Multi-Strategy Nutrition Education Programs on Hedonic Hunger and Nutrition Status in Adolescents
Authors: Bozkurt Osman , Yildiran Hilal
Published: September 2024

Objective: Increasing the awareness of adolescents about hedonic hunger, understanding the difference between homeostatic hunger and hedonic hunger, and adolescents learning to control themselves to stop excessive food consumption are extremely important for a healthy adulthood. The study aimed to evaluate the effects of the multi-strategy nutrition education programs (MSNEP) on hedonic hunger, food addiction, nutrition literacy, and nutritional status in adolescents. Methods: This study was planned using a pre-test and post-test design. The MSNEP was conducted with 132 adolescents (11–15 years; 69 boys, 63 girls) for 4 weeks (45 min–1 h/session). Data were obtained using questionnaires with face-to-face interviews at pre-education (baseline) and post-education (week 4 and week 8). The survey form included sociodemographic information, nine item short version of Children’s Power of Food Scale (C-PFS-9), the Yale Food Addiction Scale for Children 2.0 (YFAS-C 2.0), the Adolescent Nutrition Literacy Scale (ANLS), anthropometric measurements, and 24-hour dietary recall. Results: A decrease in C-PFS-9 total scores was found compared to the baseline (p < 0.001). While the YFAS-C 2.0 score decreased in boys compared to the baseline (p < 0.05), no significant difference was found in girls (p > 0.05). A difference was found in the ANLS scores for girls (p = 0.01), but no difference was found in the scores for boys during the study (p > 0.05). At week 4, the consumption of dairy products, legumes, vegetables and fruits, bread and grains, nuts, and hard-shelled seeds increased compared to the baseline (p < 0.05). Also, daily protein and fiber intake increased (p < 0.05). Accordingly, a higher YFAS-C 2.0 score predicted greater hedonic hunger. A lower ANLS score was a predictor for higher food taste and food available scores. Conclusions: In conclusion, the MSNEP was found to have positive effects on hedonic hunger, food addiction, nutritional literacy, and healthy eating behaviors. The study revealed differences between girls and boys. In order to maintain healthy body weights in adolescents, it is recommended that the MSNEP be provided in schools.
Study of Dynamic Modulus of Asphalt Mix after Reinforcement of Sandstone
Authors: Zhang Bowen , Jiang Shuangquan , Zheng Nanxiang , Liu Jinduo , Wang Yuxing
Published: September 2024

Sandstone has poor mechanical properties. To facilitate the application of sandstone into asphalt mixtures, sandstone was treated by immersion in sodium silicate solution, and the dynamic modulus after reinforcement was used as a criterion. The results showed that the mechanical properties of the sandstone aggregate treated with sodium silicate were improved, and the dynamic modulus was increased by 18.2%, which will help to reduce rutting. The dynamic modulus and phase angle can be effectively predicted over a wide frequency range using the sigma function and the Kramers–Kronig relationship. Sandstone asphalt mixtures basically conform to linear viscoelasticity, but the phase angle changes are more complicated at high temperatures and do not vary monotonically with frequency. By calculating the rutting coefficient, fatigue coefficient, and DSRFn parameters for performance prediction, it was found that an increase in dynamic modulus resulted in a significant increase in the rutting coefficient but a decrease in the cracking resistance.
Traction MRI of the Elbow: Age-Based Effects and Implications
Authors: Kohyama Sho , Ikeda Kazuhiro , Okamoto Yoshikazu , Yoshii Yuichi
Published: September 2024

Background/Objectives: We previously reported that traction magnetic resonance imaging (MRI) of the elbow without arthrography increases the width of the radiocapitellar joint (RC) and improves articular cartilage visibility. However, the effects of axial traction on different age groups have not yet been evaluated. We hypothesized that the effect of traction would decrease as the participants’ age increased. Methods: We enrolled 30 healthy volunteers, ten each in their 20s, 30s, and 40s. The male-to-female ratio in each age group was 1:1. Elbow MRI was performed without traction and with 3, 5, and 7 kg axial traction. We evaluated joint space width (JW), humeral articular cartilage visibility, and intraprocedural pain/discomfort. We measured JW and cartilage visibility at the RC and the lateral and medial thirds of the ulnohumeral joint. Results: The older age groups exhibited narrower JWs without traction. Axial traction increased the JW and improved the visibility of the RC in all age groups. No significant differences were observed in the ulnohumeral joint’s lateral or medial thirds, but pain and discomfort increased with heavier traction weights. Conclusions: For participants in their 20s and 30s, axial traction of 3 kg seemed appropriate, while 7 kg traction was considered for those in their 40s.
Single-Cell Analysis of Bone-Marrow-Disseminated Tumour Cells
Authors: So Kevin Wang Leong , Su Zezhuo , Cheung Jason Pui Yin , Choi Siu-Wai
Published: September 2024

Metastasis frequently targets bones, where cancer cells from the primary tumour migrate to the bone marrow, initiating new tumour growth. Not only is bone the most common site for metastasis, but it also often marks the first site of metastatic recurrence. Despite causing over 90% of cancer-related deaths, effective treatments for bone metastasis are lacking, with current approaches mainly focusing on palliative care. Circulating tumour cells (CTCs) are pivotal in metastasis, originating from primary tumours and circulating in the bloodstream. They facilitate metastasis through molecular interactions with the bone marrow environment, involving direct cell-to-cell contacts and signalling molecules. CTCs infiltrate the bone marrow, transforming into disseminated tumour cells (DTCs). While some DTCs remain dormant, others become activated, leading to metastatic growth. The presence of DTCs in the bone marrow strongly correlates with future bone and visceral metastases. Research on CTCs in peripheral blood has shed light on their release mechanisms, yet investigations into bone marrow DTCs have been limited. Challenges include the invasiveness of bone marrow aspiration and the rarity of DTCs, complicating their isolation. However, advancements in single-cell analysis have facilitated insights into these elusive cells. This review will summarize recent advancements in understanding bone marrow DTCs using single-cell analysis techniques.
Oral and Gingival Crevicular Fluid Biomarkers for Jawbone Turnover Diseases: A Scoping Review
Authors: Fadli Nurfatima Azzahra , Abdul Rahman Mariati , Karsani Saiful Anuar , Ramli Roszalina
Published: September 2024

Gingival crevicular fluid (GCF) and oral fluid have emerged as promising diagnostic tools for detecting biomarkers. This review aimed to evaluate the existing literature on using oral fluids as a source of biomarkers for bone turnover diseases affecting the jawbone. A comprehensive search strategy was executed between August 2014 and August 2024 across five major databases (Web of Science, EBSCOhost Dentistry & Oral Sciences Source, Cochrane Library, Scopus, and PubMed) and grey literature sources. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) was applied. The screening was facilitated using Rayyan at rayyan.ai and Endnote X20 software tools, culminating in the evaluation of 14,965 citations from databases and 34 from grey literature. Following rigorous scrutiny, 37 articles were selected for inclusion in this review, encompassing diseases such as periodontitis, medication-related osteonecrosis of the jaw (MRONJ), and osteoporosis. The quality of the included observational studies was assessed using the Revised Risk of Bias Assessment Tool for Non-Randomized Studies (RoBANS 2). Interleukin-1 beta (IL-1β), sclerostin, osteoprotegerin (OPG), and interleukin-34 (IL-34) emerged as significant biomarkers in GCF, and they were mainly from periodontitis and osteoporosis. Osteocalcin (OC), IL-1β, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), OPG, and matrix metalloproteinase-9 (MMP-9) were significant in oral fluid or saliva, and they were from periodontitis, MRONJ, and osteoporosis. These findings underscore the potential use of oral fluids, which are regarded as non-invasive tools for biomarker identification in bone turnover. Many biomarkers overlap, and it is important to identify other specific biomarkers to enable accurate diagnosis of these conditions.
Visual Analytics for Sustainable Mobility: Usability Evaluation and Knowledge Acquisition for Mobility-as-a-Service (MaaS) Data Exploration
Authors: Delfini Lorenzo , Spahiu Blerina , Vizzari Giuseppe
Published: September 2024

Urban mobility systems generate a massive volume of real-time data, providing an exceptional opportunity to understand and optimize transportation networks. To harness this potential, we developed UrbanFlow Milano, an interactive map-based dashboard designed to explore the intricate patterns of shared mobility use within the city of Milan. By placing users at the center of the analysis, UrbanFlow empowers them to visualize, filter, and interact with data to uncover valuable insights. Through a comprehensive user study, we observed how individuals interact with the dashboard, gaining critical feedback to refine its design and enhance its effectiveness. Our research contributes to the advancement of user-centric visual analytics tools that facilitate data-driven decision-making in urban planning and transportation management.
An Evaluation of the Accuracy of Digital Models—An In Vitro Study
Authors: Jánosi Kinga Mária , Cerghizan Diana , Bai Eszter Elza , Mureșan Izabella Éva , Kovács Alpár , Szász Andrea , Hulpe Adrian , Markovics Emese Rita , Mártha Krisztina Ildikó , Pop Silvia Izabella
Published: September 2024

Background: Intraoral scanning technology has opened new perspectives in dental practice, and combined with CAD/CAM technology, contributes significantly to fabricating high-quality prosthetic restorations. Our in vitro study aims to assess the accuracy of digital models obtained from one laboratory and two less commonly used intraoral scanners by conducting 3D measurements on the digital models obtained. Methods: An articulated simulator cast was used. Forty-eight scans were performed before and after tooth preparation with each scanner. The Zeiss Inspect software (Version: 2023.3.0.969) was used for measurements in sagittal and transversal planes. The obtained values were compared to reference values resulting from manual measurements. Results: Digital impressions provided discrepancies compared to the reference model. The lowest differences at the A2-L2 (the diagonal dimension of the models from the distal fossa of the second right maxillary molar and the maximum oral convexity of the artificial gingiva at the first left premolar) and the A1-B1 (transversal dimension of the model in the posterior area, from the right second molar’s occlusal central fossa to the left second molar central fossa) distances were obtained for the upper models, and at the a1-b1 distance for all the lower models, except the non-prepared models scanned with the intraoral scanners (the discrepancies were not statistically significant). The discrepancies increased with the distance from the starting point of the scan. Conclusion: The number and position of prepared teeth can influence the accuracy of the scans. Distortions can appear in the case of multiple preparations. The scanning protocol and calibration must be optimized for the highest accuracy. Furthermore, in vivo studies are necessary to evaluate the clinical applicability of these findings.
Supporting the Mental Health Needs of Neurodivergent Students: Outcomes of a Mental Health Literacy Program for Primary School Educators
Authors: Terlich Rebecca , Krishnamoorthy Govind , Fein Erich C.
Published: September 2024

This study evaluated the effectiveness of neurodiversity training modules from a mental health literacy program for primary school staff offered over a three-year period (2013–2015), entitled ‘Teaching and Mental Health’. Using archival data, this study aimed to identify how much teachers learned, how confident they were about using this newly acquired knowledge, and how well the training met the teachers’ learning needs. This study also aimed to explore the relationship between knowledge and confidence, and how satisfaction indicators affected this relationship. Key ethical considerations of neurodiversity training and outcome measurement are discussed. A pre-test and post-test survey design was conducted with 99 primary school teachers from the Brisbane region in Australia. Analyses included three paired-samples t-tests, descriptive statistics, a linear regression analysis, and a mediation analysis. Significant increases of knowledge and confidence were found compared to baseline, and mean satisfaction ratings were high. Knowledge was a significant predictor of confidence, and mental health presenter ratings partially mediated this relationship. It is proposed that future delivery of the program should invest in improving presenter effectiveness.
Miniaturized Multiband Substrate-Integrated Waveguide Bandpass Filters with Multi-Layer Configuration and High In-Band Isolation
Authors: Zhan Yu , Wu Yi , Ma Kaixue , Yeo Kiat Seng
Published: September 2024

This article presents a multiband bandpass filter structure with an in-line topology based on substrate-integrated waveguide (SIW) technology. A multi-layer configuration is employed to achieve circuit miniaturization. By constructing the coupling matrix, the coupling relationships among all resonators are quantitatively characterized, enabling the extraction of the theoretical frequency response and guiding circuit modeling and optimization. We designed and fabricated a third-order tri-band SIW filter and a third-order quad-band SIW filter, achieving a return loss of nearly 20 dB across all passbands. The close agreement between simulated and measured results validates the proposed design model. Additionally, the high in-band isolation of over 40 dB is demonstrated between all adjacent bands, highlighting the potential applicability of this technology in multiband scenarios.
Energy Efficiency Evaluation of Artificial Intelligence Algorithms
Authors: Penev Kalin , Gegov Alexander , Isiaq Olufemi , Jafari Raheleh
Published: September 2024

This article advances the discourse on sustainable and energy-efficient software by examining the performance and energy efficiency of intelligent algorithms within the framework of green and sustainable computing. Building on previous research, it explores the theoretical implications of Bremermann’s limit on efforts to enhance computer performance through more extensive methods. The study presents an empirical investigation into heuristic methods for search and optimisation, demonstrating the energy efficiency of various algorithms in both simple and complex tasks. It also identifies key factors influencing the energy consumption of algorithms and their potential impact on computational processes. Furthermore, the article discusses cognitive concepts and their interplay with computational intelligence, highlighting the role of cognition in the evolution of intelligent algorithms. The conclusion offers insights into the future directions of research in this area, emphasising the need for continued exploration of energy-efficient computing methodologies.
Typhoon Trajectory Prediction by Three CNN+ Deep-Learning Approaches
Authors: Lin Gang , Liang Yanchun , Tavares Adriano , Lima Carlos , Xia Dong
Published: September 2024

The accuracy in predicting the typhoon track can be key to minimizing their frequent disastrous effects. This article aims to study the accuracy of typhoon trajectory prediction obtained by combining several algorithms based on current deep-learning techniques. The combination of a Convolutional Neural Network with Long Short-Term Memory (CNN+LSTM), Patch Time-Series Transformer (CNN+PatchTST) and Transformer (CNN+Transformer) were the models chosen for this work. These algorithms were tested on the best typhoon track data from the China Meteorological Administration (CMA), ERA5 data from the European Centre for Medium-Range Weather Forecasts (ECMWF), and structured meteorological data from the Zhuhai Meteorological Bureau (ZMB) as an extension of existing studies that were based only on public data sources. The experimental results were obtained by testing two complete years of data (2021 and 2022), as an alternative to the frequent selection of a small number of typhoons in several years. Using the R-squared metric, results were obtained as significant as CNN+LSTM (0.991), CNN+PatchTST (0.989) and CNN+Transformer (0.969). CNN+LSTM without ZMB data can only obtain 0.987, i.e., 0.004 less than 0.991. Overall, our findings indicate that appropriately augmenting data near land and ocean boundaries around the coast improves typhoon track prediction.
Optimizing the Effectiveness of Moving Target Defense in a Probabilistic Attack Graph: A Deep Reinforcement Learning Approach
Authors: Li Qiuxiang , Wu Jianping
Published: September 2024

Moving target defense (MTD) technology baffles potential attacks by dynamically changing the software in use and/or its configuration while maintaining the application’s running states. But it incurs a deployment cost and various performance overheads, degrading performance. An attack graph is capable of evaluating the balance between the effectiveness and cost of an MTD deployment. In this study, we consider a network scenario in which each node in the attack graph can deploy MTD technology. We aim to achieve MTD deployment effectiveness optimization (MTD-DO) in terms of minimizing the network security loss under a limited budget. The existing related works either considered only a single node for deploying an MTD or they ignored the deployment cost. We first establish a non-linear MTD-DO formulation. Then, two deep reinforcement learning-based algorithms are developed, namely, deep Q-learning (DQN) and proximal policy optimization (PPO). Moreover, two metrics are defined in order to effectively evaluate MTD-DO algorithms with varying network scales and budgets. The experimental results indicate that both PPO- and DQN-based algorithms perform better than Q-learning-based and random algorithms. The DQN-based algorithm converges more quickly and performs, in terms of reward, marginally better than the PPO-based algorithm.
Target Trajectory Prediction-Based UAV Swarm Cooperative for Bird-Driving Strategy at Airport
Authors: Wang Xi , Zhang Xuan , Lu Yi , Zhang Hongqiang , Li Zhuo , Zhao Pengliang , Wang Xing
Published: September 2024

This study presents a novel cooperative bird-driving strategy utilizing unmanned aerial vehicles (UAV) swarms, specifically designed for airport environments, to mitigate the risks posed by bird interference with aircraft operations. Our approach introduces a target trajectory prediction framework that integrates Long Short-Term Memory (LSTM) networks with Kalman Filter algorithms (KF), improves the response speed of UAV swarms in bird-driving tasks, optimizes task allocation, and improves the accuracy and precision of trajectory prediction, making the entire bird-driving process more efficient and accurate. Within this framework, UAV swarms collaborate to drive birds that encroach upon designated protected areas, thereby optimizing bird-driving operations. We present a distributed collaborative bird-driving strategy to ensure effective coordination among UAV swarm members. Simulation experiments demonstrate that our strategy effectively drives dynamically changing targets, preventing them from remaining within the protected area. The proposed solution integrates dynamic target trajectory prediction using LSTM and Kalman Filter, task assignment optimization through the Hungarian algorithm, and 3D Dubins path planning. This innovative approach not only improves the operational efficiency of bird-driving in airport environments but also highlights the potential of UAV swarms to perform airborne missions in complex scenarios. Our work makes a significant contribution to the field of UAV swarm collaboration and provides practical insights for real-world applications.
Improved JPEG Lossless Compression for Compression of Intermediate Layers in Neural Networks Based on Compute-In-Memory
Authors: Hua Junyong , Xu Hang , Du Yuan , Du Li
Published: September 2024

With the development of Convolutional Neural Networks (CNNs), there is a growing requirement for their deployment on edge devices. At the same time, Compute-In-Memory (CIM) technology has gained significant attention in edge CNN applications due to its ability to minimize data movement between memory and computing units. However, the deployment of complex deep neural network models on edge devices with restricted hardware resources continues to be challenged by a lack of adequate storage for intermediate layer data. In this article, we propose an optimized JPEG Lossless Compression (JPEG-LS) algorithm that implements serial context parameter updating alongside parallel encoding. This method is designed for the global prediction and efficient compression of intermediate data layers in neural networks employing CIM techniques. The results indicate average compression ratios of 6.44× for VGG16, 3.62× for ResNet34, 1.67× for MobileNetV2, and 2.31× for InceptionV3. Moreover, the implementation achieves a data throughput of 32 bits per cycle at 600 MHz on the TSMC 28 nm, with a hardware cost of 122 K Gate Count.
Low-Light Image Enhancement Network Using Informative Feature Stretch and Attention
Authors: Chun Sung Min , Park Jun Young , Eom Il Kyu
Published: September 2024

Low-light images often exhibit reduced brightness, weak contrast, and color distortion. Consequently, enhancing low-light images is essential to make them suitable for computer vision tasks. Nevertheless, addressing this task is particularly challenging because of the inherent constraints posed by low-light environments. In this study, we propose a novel low-light image enhancement network using adaptive feature stretching and informative attention. The proposed network architecture mainly includes an adaptive feature stretch block designed to extend the narrow range of image features to a broader range. To achieve improved image restoration, an informative attention block is introduced to assign weight to the output features from the adaptive feature stretch block. We conduct comprehensive experiments on widely used benchmark datasets to assess the effectiveness of the proposed network. The experimental results show that the proposed low-light image enhancement network yields satisfactory results compared with existing state-of-the-art methods from both subjective and objective perspectives while maintaining acceptable network complexity.
Kinetics of Hydrolytic Depolymerization of Textile Waste Containing Polyester
Authors: Aneja Arun , Kupka Karel , Militký Jiří , Venkataraman Mohanapriya
Published: September 2024

Textile products comprise approximately 10% of the total global carbon footprint. Standard practice is to discard apparel textile waste after use, which pollutes the environment. There are professional collectors, charity organizations, and municipalities that collect used apparel and either resell or donate them. Non-reusable apparel is partially recycled, mainly through incineration or processed as solid waste during landfilling. More than 60 million tons of textiles are burnt or disposed of in landfills annually. The main aim of this paper is to model the heterogeneous kinetics of hydrolysis of multicomponent textile waste containing polyester (polyethylene terephthalate (PET) fibers), by using water without special catalytic agents or hazardous and costly chemicals. This study aims to contribute to the use of closed-loop technology in this field, which will reduce the associated negative environmental impact. The polyester part of waste is depolymerized into primary materials, namely monomers and intermediates. Reaction kinetic models are developed for two mechanisms: (i) the surface reaction rate controlling the hydrolysis and (ii) the penetrant in terms of the solid phase rate controlling the hydrolysis. A suitable kinetic model for mono- and multicomponent fibrous blends hydrolyzed in neutral and acidic conditions is chosen by using a regression approach. This approach can also be useful for the separation of cotton/polyester or wool/polyester blends in textile waste using the acid hydrolysis reaction, as well as the application of high pressure and the neutral hydrolysis of polyester to recover primary monomeric constituents.