bluuebunny/crossref_metadata_2025 huggingface dataset:
Geospatial Prioritization of Terrains for “Greening” Urban Infrastructure
Authors: Borisova Bilyana , Semerdzhieva Lidiya , Dimitrov Stelian , Valchev Stoyan , Iliev Martin , Georgiev Kristian
Published: September 2024

This study aims to scientifically justify the identification of suitable urban properties for urban green infrastructure (UGI) interventions to optimize its natural regulating functions for long-term pollution mitigation and secondary dust reduction. This study adheres to the perception that planning urban transformations to improve ambient air quality (AQ) requires a thorough understanding of urban structural heterogeneity and its interrelationship with the local microclimate. We apply an approach in which UGI and its potential multifunctionality are explored as a structural–functional element of urban local climatic zones. The same (100 × 100 m) spatial framework is used to develop place-based adapted solutions for intervention in UGI. A complex geospatial analysis of Burgas City, the second largest city (by area) in Bulgaria, was conducted by integrating 12 indicators to reveal the spatial disbalance of AQ regulation’ demand and UGI’s potential to supply ecosystem services. A total of 174 municipally owned properties have been identified, of which 79 are of priority importance, including for transport landscaping, inner-quarter spaces, and social infrastructure. Indicators of population density and location of social facilities were applied with the highest weight in the process of prioritizing sites. The study relies on public data and information from the integrated city platform of Burgas, in cooperation with the city’s government. The results have been discussed with stakeholders and implemented by the Municipality of Burgas in immediate greening measures in support of an ongoing program for Burgas Municipality AQ improvement.
Research on the Correlation between Mechanical Seal Face Vibration and Stationary Ring Dynamic Behavior Characteristics
Authors: Song Yunfeng , Li Hua , Xiao Wang , Li Shuangxi , Wang Qingfeng
Published: September 2024

To address the lack of reliable measurement methods for identifying wear mechanisms and predicting the state of mechanical seal tribo-parts, this study proposes a method for characterizing tribological behavior based on measuring face vibration acceleration. It aims to uncover the source mechanism of mechanical seal face vibration acceleration influenced by tribology and dynamic behavior. This research delves into the dynamic behavior characteristics and vibration acceleration of the mechanical seal stationary ring. We explored the variation pattern of face vibration acceleration root mean square (RMS) with rotation speed, sealing medium pressure, and face surface roughness. The results indicate that under constant medium pressure, an increase in rotation speed leads to a decrease in acceleration RMS and an increase in face temperature. Similarly, under constant rotation speed, an increase in medium pressure results in nonlinear changes in acceleration RMS, forming an “M” shape, along with an increase in face temperature. Furthermore, under conditions of constant medium pressure and rotation speed, an increase in the surface roughness of the rotating ring face corresponds to an increase in acceleration RMS and face temperature. Upon starting the mechanical seal, both acceleration RMS and temperature initially increase before decreasing, a trend consistent with the Stribeck curve.
Analytical Solution for Dynamic Response of a Reinforced Concrete Beam with Viscoelastic Bearings Subjected to Moving Loads
Authors: Sun Liangming , Liu Shuguang , Kong Fan , Zhao Hanbing
Published: September 2024

To provide a theoretical basis for eliminating resonance and optimizing the design of viscoelastically supported bridges, this paper investigates the analytical solutions of train-induced vibrations in railway bridges with low-stiffness and high-damping rubber bearings. First, the shape function of the viscoelastic bearing reinforced concrete (RC) beam is derived for the dynamic response of the viscoelastic bearing RC beam subjected to a single moving load. Furthermore, based on the simplified shape function, the dynamic response of the viscoelastic bearing RC beam under equidistant moving loads is studied. The results show that the stiffness and damping effect on the dynamic response of the supports cannot be neglected. The support stiffness might adversely increase the dynamic response. Further, due to the effect of support damping, the free vibration response of RC beams in resonance may be significantly suppressed. Finally, when the moving loads leave the bridge, the displacement amplitude of the viscoelastic support beam in free vibration is significantly larger than that of the rigid support beam.
Crystal Structures and Piezoelectric Properties of Quenched and Slowly-Cooled BiFeO3-BaTiO3 Ceramics
Authors: Go Su Hwan , Kim Kang San , Choi Ye Rok , Kim Jeong-Seog , Cheon Chae Il
Published: September 2024

The BiFeO3-BaTiO3 (BF-BT) ceramics were here prepared through the solid-state reaction of Bi2O3, Fe2O3 and nano-sized BT powders. The crystal structures and piezoelectric properties were investigated in both quenched (AQ) and slowly cooled (SC) 0.7BF-0.3BT ceramics. Prior work has shown that rhombohedral and pseudo-cubic phases coexist in 0.7BF-0.3BT ceramics. In this work, the crystal structure of the pseudo-cubic phase was refined as a non-polar orthorhombic Pbnm phase in the SC sample and as a polar orthorhombic Pmc21 phase in the AQ sample. In addition to a sharp dielectric peak at about 620 °C, corresponding to the Curie temperature of the rhombohedral phase, a broad dielectric peak with strong frequency dispersion and a sharp frequency-independent dielectric peak were observed at around 500 °C in the SC and AQ samples, respectively. We determine that the dielectric anomalies around 500 °C were caused by a relaxor phase transition of the non-polar orthorhombic phase in the SC sample and a ferroelectric–paraelectric phase transition of the polar orthorhombic phase in the AQ sample. The AQ sample showed better ferroelectric and piezoelectric properties than the SC sample. The 0.7BF-0.3BT ceramic slowly cooled in a nitrogen atmosphere showed a well-saturated P-E curve and a similar temperature-dependent dielectric constant as the AQ sample. Our results indicate that large concentrations of oxygen vacancies produce a more distorted polar orthorhombic phase and better piezoelectric properties in the AQ sample than in the SC sample.
Insulating Innovative Geopolymer Foams with Natural Fibers and Phase-Change Materials—A Review of Solutions and Research Results
Authors: Przybek Agnieszka , Łach Michał
Published: September 2024

Geopolymers are synthesized using anthropogenic raw materials and waste from the energy industry. Their preparation necessitates an alkaline activator, which facilitates the dissolution of raw materials and their subsequent binding. At present, geopolymers are considered a promising material with the potential to replace conventional cement-based products. This research investigates foamed geopolymer materials based on fly ash, natural fibers, and phase-change materials. The study utilized three distinct types of fibers and two phase-change materials manufactured by Rubitherm Technologies GmbH of Germany. This paper presents the results of the thermal conductivity coefficient and specific heat tests on the finished foams. Additionally, compressive strength tests were conducted on the samples after 28 days. Natural fibers decreased the insulation parameter by 12%, while PCM enhanced it by up to 6%. The addition of fibers increased the compressive strength by nearly 30%, whereas PCM reduced this by as little as 14%. Natural fibers and phase-change materials had an increased heat capacity by up to 35%. The results demonstrated the material’s potential in various industrial sectors, with the primary areas of application being building materials and insulations. The findings illustrate the significant potential of these composites as energetically and environmentally sustainable materials.
Improving the Early Age Strength of Eco-Efficient Mortar with Low Clinker Content Considering Binder Granulometry and Chemical Additives
Authors: Schack Tobias , Strybny Bastian , Haist Michael
Published: September 2024

In this study, the impact of binder granulometry as well as chemical additives on the early strength and early age stiffness development of eco-efficient mortars with low clinker content and ternary blended cements with high contents of slag and limestone powder was investigated. With regard to granulometry, the particle size distribution of the slag was varied in two steps. In addition, admixtures based on nano-granular C-S-H seeds were used for the acceleration of the hydration reaction. Both the compressive strength at 1d and the in-situ ultrasound pulse velocity for the first 36 h were determined. The granulometric optimization of the slag leads to an improvement in compressive strength of up to 162% in the early phase of the first 24 h. In addition, C-S-H seeding enhanced the hydration reaction mortars as early as 6 h after water addition (at 20 °C). An increase in the dosage level of the C-S-H seeding admixture further resulted in a corresponding increase in early strength, particularly when the clinker content exceeds 30 wt% up to 103%. The proposed combined granulometric and admixture-based approach significantly improves the reaction of the binder in the early phase, so that the clinker factor can be significantly reduced while maintaining a comparable binder intensity.
Experimental and Numerical Study of Steel–Concrete Composite Beams Strengthened under Load
Authors: Szewczyk Piotr
Published: September 2024

This study analysed the strengthening process of a classical steel–concrete composite beam. The beam consisted of a reinforced concrete slab connected by shear studs to an IPE steel profile. The key idea was that the composite beam was strengthened under load. This process simulated an actual reinforced structure that is always subjected to dead loads, with possible service loads. This study assumed that strengthening was implemented to increase the load-carrying capacity and stiffness, not as a way for simulation a repair. The strengthening consisted of expanding the steel part of the beam by welding an additional plate to the bottom flange of the IPE profile. This study included the results of numerical analyses conducted in Abaqus software and lab results. A three-dimensional numerical model was created, taking into account the non-linear behaviour of concrete and steel, the susceptibility of the composite at the joint plane, and the residual stresses created during welding. A full-scale strengthening of the composite beams under load was carried out. Comparison of the results obtained in the experimental tests and numerical analyses showed a very high convergence of the results, as well as in terms of the non-linear operation of steel and concrete. This confirmed the validity of the created numerical model, which can be the basis for further research into the process of optimal strengthening of composite elements.
Deep Learning-Based Real-Time 6D Pose Estimation and Multi-Mode Tracking Algorithms for Citrus-Harvesting Robots
Authors: Hwang Hyun-Jung , Cho Jae-Hoon , Kim Yong-Tae
Published: September 2024

In the agricultural sector, utilizing robots for tasks such as fruit harvesting poses significant challenges, particularly in achieving accurate 6D pose estimation of the target objects, which is essential for precise and efficient harvesting. Particularly, fruit harvesting relies heavily on manual labor, leading to issues with an unstable labor supply and rising costs. To solve these problems, agricultural harvesting robots are gaining attention. However, effective harvesting necessitates accurate 6D pose estimation of the target object. This study proposes a method to enhance the performance of fruit-harvesting robots, including the development of a dataset named HWANGMOD, which was created using both virtual and real environments with tools such as Blender and BlenderProc. Additionally, we present methods for training an EfficientPose-based model for 6D pose estimation and ripeness classification, and an algorithm for determining the optimal harvest sequence among multiple fruits. Finally, we propose a multi-object tracking method using coordinates estimated by deep learning models to improve the robot’s performance in dynamic environments. The proposed methods were evaluated using metrics such as ADD and ADDS, showing that the deep learning model for agricultural harvesting robots excelled in accuracy, robustness, and real-time processing. These advancements contribute to the potential for commercialization of agricultural harvesting robots and the broader field of agricultural automation technology.
Modelling of Reliability Indicators of a Mining Plant
Authors: Malozyomov Boris V. , Martyushev Nikita V. , Babyr Nikita V. , Pogrebnoy Alexander V. , Efremenkov Egor A. , Valuev Denis V. , Boltrushevich Aleksandr E.
Published: September 2024

The evaluation and prediction of reliability and testability of mining machinery and equipment are crucial, as advancements in mining technology have increased the importance of ensuring the safety of both the technological process and human life. This study focuses on developing a reliability model to analyze the controllability of mining equipment. The model, which examines the reliability of a mine cargo-passenger hoist, utilizes statistical methods to assess failures and diagnostic controlled parameters. It is represented as a transition graph and is supported by a system of equations. This model enables the estimation of the reliability of equipment components and the equipment as a whole through a diagnostic system designed for monitoring and controlling mining equipment. A mathematical and logical model is proposed to calculate availability and downtime coefficients for different structures within the mining equipment system. This analysis considers the probability of failure-free operation of the lifting unit based on the structural scheme, with additional redundancy for elements with lower reliability. The availability factor of the equipment for monitoring and controlling the mine hoisting plant is studied for various placements of diagnostic systems. Additionally, a logistic concept is introduced for organizing preventive maintenance systems and reducing equipment recovery time by optimizing spare parts, integrating them into strategies aimed at enhancing the reliability of mine hoisting plants.
Fault Monitoring Method for the Process Industry System Based on the Improved Dense Connection Network
Authors: Yasenjiang Jiarula , Lan Zhigang , Wang Kai , Lv Luhui , He Chao , Zhao Yingjun , Wang Wenhao , Gao Tian
Published: September 2024

The safety of chemical processes is of critical importance. However, traditional fault monitoring methods have insufficiently studied the monitoring accuracy of multi-channel data and have not adequately considered the impact of noise on industrial processes. To address this issue, this paper proposes a neural network-based model, DSCBAM-DenseNet, which integrates depthwise separable convolution and attention modules to fuse multi-channel data features and enhance the model’s noise resistance. We simulated a real environment by adding Gaussian noise with different signal-to-noise ratios to the Tennessee Eastman process dataset and trained the model using multi-channel data. The experimental results show that this model outperforms traditional models in both fault diagnosis accuracy and noise resistance. Further research on a compressor unit engineering instance validated the superiority of the model.
Discrete Random Renewable Replacements after the Expiration of Collaborative Preventive Maintenance Warranty
Authors: Chen Hui , Chen Jie , Lai Yangyang , Yu Xiaoqi , Shang Lijun , Peng Rui , Liu Baoliang
Published: September 2024

With advanced digital technologies as the key support, many scholars and researchers have proposed various random warranty models by integrating mission cycles into the warranty stage. However, these existing warranty models are designed only from the manufacturer’s subjective perspective, ignoring certain consumer requirements. For instance, they overlook a wide range of warranty coverage, the pursuit of reliability improvement rather than mere minimal repair, and the need to limit the delay in repair. To address these consumer requirements, this paper proposes a novel random collaborative preventive maintenance warranty with repair-time threshold (RCPMW-RTT). This model incorporates terms that are jointly designed by manufacturers and consumers to meet specific consumer needs, thereby overcoming the limitations of existing warranty models. The introduction of a repair-time threshold aims to limit the time delay in repairing failures and to compensate for any losses incurred by consumers. Using probability theory, the RCPMW-RTT is evaluated in terms of cost and time, and relevant variants are derived by analyzing key parameters. As an exemplary representation of the RCPMW-RTT, two random replacement policies named the discrete random renewable back replacement (DRRBR) and the discrete random renewable front replacement (DRRFR) are proposed and modelled to ensure reliability after the expiration of the RCPMW-RTT. In both policies, product replacement is triggered either by the occurrence of the first extreme mission cycle or by reaching the limit on the number of non-extreme mission cycles, whichever comes first. Probability theory is used to present cost rates for both policies in order to determine optimal values for decision variables. Finally, numerical analysis is performed on the RCPMW-RTT to reveal hidden variation tendencies and mechanisms; numerical analysis is also performed on the DRRBR and the DRRFR. The numerical results show that the proposed random replacement policies are feasible and unique; the replacement time within the post-warranty coverage increases as the maintenance quality improves and the cost rate can be reduced by setting a smaller repair-time threshold.
Improving the Diagnosis of Systemic Lupus Erythematosus with Machine Learning Algorithms Based on Real-World Data
Authors: Park Meeyoung
Published: September 2024

This study addresses the diagnostic challenges of Systemic Lupus Erythematosus (SLE), an autoimmune disease with a complex etiology and varied symptoms. The ANA (antinuclear antibody) test, currently the primary diagnostic tool for SLE, exhibits high sensitivity but low specificity, often leading to inaccurate diagnoses. To enhance diagnostic precision, we propose integrating machine learning algorithms with existing clinical classification guidelines to improve SLE diagnosis accuracy, potentially reducing diagnostic errors and healthcare costs. We analyzed real-world data from a cohort of 24,990 patients over a 10-year period at the hospitals, excluding those previously diagnosed with SLE. Patients were categorized into three groups: negative ANA, positive ANA with non-SLE, and positive ANA with SLE. Feature selection was conducted to identify key factors influencing SLE diagnosis, and machine learning algorithms were employed to develop the CDSS. Performance analysis of three machine learning algorithms—decision tree, random forest, and gradient boosting—based on feature sets of 10, 20, and all available features revealed accuracy rates of 70%, 88%, and 87%, respectively, for the 20-feature set. The proposed system, utilizing real-world medical data, demonstrated modest performance in SLE diagnosis, highlighting the potential of machine learning-based CDSS in real clinical settings.
Probabilistic Cellular Automata Monte Carlo for the Maximum Clique Problem
Authors: Troiani Alessio
Published: September 2024

We consider the problem of finding the largest clique of a graph. This is an NP-hard problem and no exact algorithm to solve it exactly in polynomial time is known to exist. Several heuristic approaches have been proposed to find approximate solutions. Markov Chain Monte Carlo is one of these. In the context of Markov Chain Monte Carlo, we present a class of “parallel dynamics”, known as Probabilistic Cellular Automata, which can be used in place of the more standard choice of sequential “single spin flip” to sample from a probability distribution concentrated on the largest cliques of the graph. We perform a numerical comparison between the two classes of chains both in terms of the quality of the solution and in terms of computational time. We show that the parallel dynamics are considerably faster than the sequential ones while providing solutions of comparable quality.
Adaptation of an Eddy Current Model for Characterizing Subsurface Defects in CFRP Plates Using FEM Analysis Based on Energy Functional
Authors: Versaci Mario , Laganà Filippo , Morabito Francesco Carlo , Palumbo Annunziata , Angiulli Giovanni
Published: September 2024

In this work, a known Eddy Current (EC) model is adapted to characterize subsurface defects in carbon fiber-reinforced polymer (CFRP) plates intended for the civil aerospace industry. The considered defects include delaminations, microcracks, porosity, fiber breakage, and the simultaneous presence of these defects. Each defect is modeled as an additive variation in the material’s electrical conductivity tensor, allowing for a detailed mathematical representation of the defect’s influence on the CFRP’s electromagnetic behavior. The additivity of the variations in the conductivity tensor is justified by the assumption that the defects are not visible to the naked eye, implying that the material does not require non-destructive testing. The adapted EC model admits a unique and stable solution by verifying that all analytical steps are satisfied. To reconstruct 2D maps of the magnetic flux density amplitude, a FEM formulation is adopted, based on the energy functional because it ensures a stable and consistent numerical formulation given its coercivity. Moreover, the numerical approach allows precise and reliable numerical solutions, enhancing the capability to detect and quantify defects. The numerical results show that the obtained 2D maps are entirely superimposable on those highlighting the distribution of mechanical stress states known in the literature, offering a clear advantage in terms of detection costs. This approach provides an effective and economical solution for the non-destructive inspection of CFRP, ensuring accurate and timely defect diagnosis for maintaining structural integrity.
Optimizing Antioxidant Potential: Factorial Design-Based Formulation of Fucoidan and Gallic Acid-Conjugated Dextran Blends
Authors: Silva Cynthia Haynara Ferreira , Silva Maylla Maria Correia Leite , Paiva Weslley Souza , de Medeiros Mayara Jane Campos , Queiroz Moacir Fernandes , Matta Luciana Duarte Martins , dos Santos Everaldo Silvino , Rocha Hugo Alexandre Oliveira
Published: September 2024

The role of oxidative stress in health and homeostasis has generated interest in the scientific community due to its association with cardiovascular and neurodegenerative diseases, cancer, and other diseases. Therefore, extensive research seeks to identify new exogenous antioxidant compounds for supplementation. Polysaccharides are recognized for their antioxidant properties. However, polysaccharide chemical modifications are often necessary to enhance these properties. Therefore, dextran was conjugated with gallic acid (Dex-Gal) and later combined with fucoidan A (FucA) to formulate blends aimed at achieving superior antioxidant activity compared to individual polysaccharides. A factorial design was employed to combine FucA and Dex-Gal in different proportions, resulting in five blends (BLD1, BLD2, BLD3, BLD4, and BLD5). An analysis of surface graphs from in vitro antioxidant tests, including total antioxidant capacity (TAC), reducing power, and hydroxyl radical scavenging, guided the selection of BLD4 as the optimal formulation. Tests on 3T3 fibroblasts under various conditions of oxidative stress induced by hydrogen peroxide revealed that BLD4 provided enhanced protection compared to its isolated components. The BLD4 formulation, resulting from the combination of Dex-Gal and FucA, showed promise as an antioxidant strategy, outperforming its individual components and suggesting its potential as a supplement to mitigate oxidative stress in adverse health conditions.
Primary Total Knee Arthroplasty for Treating Osteoarthritic Knees with Neglected Patellar Dislocation
Authors: Kim Sung Eun , Kim Seong Hwan , Lee Jung-In , Han Hyuk-Soo , Lee Myung Chul , Ro Du Hyun
Published: September 2024

Background and Objectives: Neglected patellar dislocation in the presence of end-stage osteoarthritis (OA) is a rare condition characterized by the patella remaining laterally dislocated without reduction. Due to the scarcity of reported cases, the optimal management approach is still uncertain. However, primary total knee arthroplasty (TKA) can serve as an effective treatment option. This study aimed to present the clinical and radiological outcomes achieved using our surgical technique. Materials and Methods: A retrospective review of 12 knees in 8 patients with neglected patellar dislocation and end-stage OA who underwent primary TKA was conducted. The surgical procedure involved conventional TKA techniques (e.g., medial parapatellar arthrotomy) and additional procedures specific to the individual pathologies of neglected patellar dislocation (e.g., lateral release, medial plication, and quadriceps lengthening). Clinical outcomes, including patient-reported outcome measures (PROMs) (Knee Society Scores and the Western Ontario and McMaster Universities Osteoarthritis Index) and knee range of motion (ROM), were assessed preoperatively and two years postoperatively. Radiological measures including mechanical femorotibial angle and patellar tilt angle were assessed preoperatively and until the last follow-up examinations. Any complications were also reviewed. Results: There were significant improvements in all PROMs, knee ROM, and radiological outcomes, including mechanical femorotibial angle and patellar tilt angle (all p < 0.05). At a mean follow-up of 68 months, no major complications requiring revision surgery, including patellar dislocation, were reported. Conclusions: Primary TKA is an effective procedure for correcting various pathologies associated with neglected patellar dislocation in end-stage OA without necessitating additional bony procedures. Satisfactory clinical and radiological outcomes can be expected using pathology-specific procedures.
Gemini-Assisted Deep Learning Classification Model for Automated Diagnosis of High-Resolution Esophageal Manometry Images
Authors: Popa Stefan Lucian , Surdea-Blaga Teodora , Dumitrascu Dan Lucian , Pop Andrei Vasile , Ismaiel Abdulrahman , David Liliana , Brata Vlad Dumitru , Turtoi Daria Claudia , Chiarioni Giuseppe , Savarino Edoardo Vincenzo , Zsigmond Imre , Czako Zoltan , Leucuta Daniel Corneliu
Published: September 2024

Background/Objectives: To develop a deep learning model for esophageal motility disorder diagnosis using high-resolution manometry images with the aid of Gemini. Methods: Gemini assisted in developing this model by aiding in code writing, preprocessing, model optimization, and troubleshooting. Results: The model demonstrated an overall precision of 0.89 on the testing set, with an accuracy of 0.88, a recall of 0.88, and an F1-score of 0.885. It presented better results for multiple categories, particularly in the panesophageal pressurization category, with precision = 0.99 and recall = 0.99, yielding a balanced F1-score of 0.99. Conclusions: This study demonstrates the potential of artificial intelligence, particularly Gemini, in aiding the creation of robust deep learning models for medical image analysis, solving not just simple binary classification problems but more complex, multi-class image classification tasks.
Hypermobile Anterior Horn of the Lateral Meniscus: A Retrospective Case-Series Study of Presentation, Imaging, Treatment, and Outcomes
Authors: Lin Chang-Hao , Chiang Chen-Hao , Hung Wei-Chen , Chih Wei-Hsing
Published: September 2024

Background and Objectives: Hypermobility of the lateral meniscus is typically associated with the posterior part of this structure, with occurrences in the anterior part rarely reported. However, a hypermobile anterior horn of the lateral meniscus can manifest clinical symptoms. This study aimed to increase awareness regarding hypermobility in the anterior horn of the lateral meniscus by presenting its clinical presentations, magnetic resonance imaging (MRI) findings, arthroscopic findings, treatment approaches, postoperative protocols, and clinical outcomes. Materials and Methods: A retrospective case-series involving patients diagnosed as having hypermobile anterior horn of the lateral meniscus through arthroscopy. The clinical presentations, preoperative image findings, arthroscopic findings, treatments, postoperative protocols, and clinical outcomes following meniscal stabilization were all reviewed. Results: A total of 17 patients (17 knees) with a mean age of 45.9 ± 18.4 years were analyzed. The mean follow-up period was 18.2 ± 7.6 months (range, 6–24 months). Primary symptoms included anterior lateral knee pain, tenderness in the lateral joint lines, and a locking sensation in six of the knees. MRI revealed hypodense lesions anterior to the meniscus, fluid accumulation, degenerative changes, and anterior horn deformities. Following meniscal stabilization, the Lysholm Knee Scoring Scale score increased from 65.8 ± 12.7 before surgery to 91.1 ± 9.6 at the final follow-up (p < 0.001). All the analyzed knees achieved a full range of motion by the final follow-up, with no patient experiencing any complication or requiring reoperation. Conclusions: There is no specific sign or test that can be used to detect a hypermobile anterior horn of the lateral meniscus. A thorough arthroscopic examination is essential for diagnosing hypermobility in the anterior horn of the lateral meniscus. Arthroscopic meniscal stabilization yields favorable outcomes.
A Preliminary Study on the Whole-Plant Regulations of the Shrub Campylotropis polyantha in Response to Hostile Dryland Conditions
Authors: Zhang Hua , Jiang Xue , Zhu Lijun , Liu Lei , Liao Zhengqiao , Du Baoguo
Published: September 2024

Drylands cover more than 40% of global land surface and will continue to expand by 10% at the end of this century. Understanding the resistance mechanisms of native species is of particular importance for vegetation restoration and management in drylands. In the present study, metabolome of a dominant shrub Campylotropis polyantha in a dry-hot valley were investigated. Compared to plants grown at the wetter site, C. polyantha tended to slow down carbon (C) assimilation to prevent water loss concurrent with low foliar reactive oxygen species and sugar concentrations at the drier and hotter site. Nitrogen (N) assimilation and turn over were stimulated under stressful conditions and higher leaf N content was kept at the expense of root N pools. At the drier site, roots contained more water but less N compounds derived from the citric acid cycle. The site had little effect on metabolites partitioning between leaves and roots. Generally, roots contained more C but less N. Aromatic compounds were differently impacted by site conditions. The present study, for the first time, uncovers the apparent metabolic adaptations of C. polyantha to hostile dryland conditions. However, due to the limited number of samples, we are cautious about drawing general conclusions regarding the resistance mechanisms. Further studies with a broader spatial range and larger time scale are therefore recommended to provide more robust information for vegetation restoration and management in dryland areas under a changing climate.
Editorial for the Special Issue on Methodology, Microfabrication and Applications of Advanced Sensing and Smart Systems
Authors: Jia Luyu , Ji Shanling , Gao Yuze , Wen Haiying , Zhu Jianxiong
Published: September 2024

Smart sensing and advanced systems have played crucial roles in the modern industrialization of society, which has led to many sensors being used in fabrication methodologies for various applications, such as in medical equipment [...]
Molecular Characterization and Phylogenetic Analysis of Honeybee (Apis mellifera) Mite-Borne Pathogen DWV-A and DWV-B Isolated from Lithuania
Authors: Amšiejūtė-Graziani Paulina , Jurgelevičius Vaclovas , Pilevičienė Simona , Janeliūnas Žygimantas , Radzijevskaja Jana , Paulauskas Algimantas , Butrimaitė-Ambrozevičienė Česlova , Jacevičienė Ingrida
Published: September 2024

Deformed wing virus (DWV) is known as one of the main viruses that affect honeybees’ health all around the world. The virus has two widespread genotypes, DWV-A and DWV-B (VDV-1), transmitted mainly by V. destructor mites. In this study, we collected honeycombs with covered broods from 73 apiaries in eight Lithuanian regions and initially investigated the prevalence of V. destructor mites. Mites were collected from May to the end of July in 2021 from 124 hives. The prevalence of V. destructor infestations in beehives reached 30% and 63% in investigated apiaries. The presence of DWV-A and DWV-B pathogens in mites and broods was examined by RT-qPCR targeting the CRPV-capsid region. The molecular characterization of the virus in mite samples was based on sequence analysis of the RNA-dependent RNA polymerase (RdRp) region. In addition, leader polypeptide (LP), structural protein (Vp3), Helicase, and RdRp genes were used for phylogenetic characterization of dual infection. The prevalences of DWV-B in mites and broods were 56.5% and 31.5%, respectively, while DWV-A was detected in 12.9% of mite samples and 24.7% of brood samples. Some of the examined mite samples harboured dual virus infections. Our findings showed that bee colonies from the same apiary were not always infected by the same viruses. Some bee colonies were virus-free, while others were highly infected. Phylogenetic analysis of 21 sequences demonstrated the presence of highly variable DWV-B and DWV-A genotypes in Lithuania and possible recombinant variants of the virus. This study represents the first molecular characterization of mite-borne pathogens hosted by honeybees (Apis mellifera) in Lithuania.
Large-Scale Sampling Reveals the Strain-Level Diversity of Burkholderia Symbionts in Riptortus pedestris and R. linearis (Hemiptera: Alydidae)
Authors: Hou Xin-Rui , Fu Si-Ying , Wang Yuan , Zhou Jia-Yue , Qi Tian-Yi , Li Yan-Fei , Bu Wen-Jun , Xue Huai-Jun
Published: September 2024

Burkholderia (sensu lato) is a diverse group of β-Proteobacteria that exists worldwide in various environments. The SBE clade of this group was thought to be mutualistic with stinkbugs. Riptortus–Burkholderia was suggested as an ideal model system for studying insect–microbe symbiosis. To explore the strain-level diversity of Burkholderia at the individual and population levels of Riptortus stinkbugs (Hemiptera: Alydidae), and to uncover the factors affecting the Burkholderia community, large-scale sampling of two Riptortus species and deep sequencing data (16S amplicon) were used in the present study. Our results showed that: (1) the proportions of facultative symbiotic bacteria Burkholderia were very high, with an average proportion of 87.1% in the samples; (2) only six out of 1373 Burkholderia amplicon sequence variants (ASVs) did not belong to the SBE clade, accounting for only 0.03% of Burkholderia; (3) a relatively small number of Burkholderia ASVs had a large number of sequences, with 22, 54, and 107 ASVs accounting for more than 1.0%, 0.1%, and 0.01% of the total Burkholderia sequences, respectively; (4) multiple Burkholderia ASVs were present in most Riptortus individuals, but there was one dominant or two codominant ASVs, and codominance was more likely to occur when the genetic distance between the two codominant ASVs was small; and (5) the beta diversity of Burkholderia was significantly different between the two host species (PerMANOVA: both Jaccard and Bray–Curtis, p < 0.001) and among localities (PerMANOVA: both Jaccard and Bray–Curtis, p < 0.001). Two-way PerMANOVA also indicated that both the host (Bray–Curtis, p = 0.020; Jaccard, p = 0.001) and geographical location (Bray–Curtis, p = 0.041; Jaccard, p = 0.045) influence Burkholderia communities; furthermore, Mantel tests showed that the Burkholderia communities were significantly correlated with the geographical distance of sample locations (R = 0.056, p = 0.001). Together, our findings demonstrate the fine-scale diversity of Burkholderia symbionts and suggest a region- and host-dependent pattern of Burkholderia in Riptortus stinkbugs.
Characteristics of Bacterial Community Structure and Function in Artificial Soil Prepared Using Red Mud and Phosphogypsum
Authors: Liu Yong , Yang Zhi , Zhang Lishuai , Wan Hefeng , Deng Fang , Zhao Zhiqiang , Wang Jingfu
Published: September 2024

The preparation of artificial soil is a potential cooperative resource utilization scheme for red mud and phosphogypsum on a large scale, with a low cost and simple operation. The characteristics of the bacterial community structure and function in three artificial soils were systematically studied for the first time. Relatively rich bacterial communities were formed in the artificial soils, with relatively high abundances of bacterial phyla (e.g., Cyanobacteria, Proteobacteria, Actinobacteriota, and Chloroflexi) and bacterial genera (e.g., Microcoleus_PCC-7113, Rheinheimera, and Egicoccus), which can play key roles in various nutrient transformations, resistance to saline–alkali stress and pollutant toxicity, the enhancement of various soil enzyme activities, and the ecosystem construction of artificial soil. There were diverse bacterial functions (e.g., photoautotrophy, chemoheterotrophy, aromatic compound degradation, fermentation, nitrate reduction, cellulolysis, nitrogen fixation, etc.), indicating the possibility of various bacteria-dominated biochemical reactions in the artificial soil, which can significantly enrich the nutrient cycling and energy flow and enhance the fertility of the artificial soil and the activity of the soil life. The bacterial communities in the different artificial soils were generally correlated with major physicochemical factors (e.g., pH, OM, TN, AN, and AP), as well as enzyme activity factors (e.g., S-UE, S-SC, S-AKP, S-CAT, and S-AP), which comprehensively illustrates the complexity of the interaction between bacterial communities and environmental factors in artificial soils, and which may affect the succession direction of bacterial communities, the quality of the artificial soil environment, and the speed and direction of the development and maturity of the artificial soil. This study provides an important scientific basis for the synergistic soilization of two typical industrial solid wastes, red mud and phosphogypsum, specifically for the microbial mechanism, for the further evolution and development of artificial soil prepared using red mud and phosphogypsum.
Kupffer Cells and Hepatocytes: A Key Relation in the Context of Canine Leishmaniasis
Authors: Rodrigues Armanda , Alexandre-Pires Graça , Valério-Bolas Ana , Nunes Telmo , Pereira da Fonseca Isabel , Santos-Gomes Gabriela
Published: September 2024

Human zoonotic visceral leishmaniasis (ZVL) and canine leishmaniasis (CanL) constitute a major public and veterinary health concern and are both caused by the infection with the protozoan parasite Leishmania infantum. One of the main target organs in CanL is the liver. This complex organ, composed of various highly specialized cell types, has garnered significant attention from the scientific community as a crucial player in innate immune functions. In the context of CanL, liver infection by parasites and the host immune response generated strongly influence the disease outcome. Thus, taking advantage of a co-culture system involving canine hepatocytes and L. infantum-infected autologous Kupffer cells (KCs), allowing cell-to-cell interaction, the current report aims to shed light on the hepatocyte-KCs immune interaction. The co-culture of infected KCs with hepatocytes revealed a vital role of these cells in the activation of a local immune response against L. infantum parasites. Although KCs alone can be immunologically silenced by L. infantum infection, the cell-to-cell interaction with hepatocytes in co-culture can lead to local immune activation. In co-culture it was observed gene expression increased the number of innate immune receptors, specifically cell membrane TLR2 and cytoplasmatic NOD1 along with high TNF-α generation. Altogether, these results suggest that the immune response generated in co-culture could induce the recruitment of other circulating cells to contain and contribute to the resolution of the infection in the liver. This work also enhances our understanding of the liver as a vital organ in innate immunity within the context of CanL.
Characterization of Escherichia coli Persisters from Biofilm Culture: Multiple Dormancy Levels and Multigenerational Memory in Formation
Authors: Ikeda Hirona , Maeda Sumio
Published: September 2024

Persister cells (PCs), a subpopulation occurring within normal cells, exhibit a transient tolerance to antibiotics because of their dormant state. PCs are categorized into two types: type I PCs, which emerge during the stationary phase, and type II PCs, which emerge during the logarithmic phase. Using the conventional colony-forming method, we previously demonstrated that type I PCs of Escherichia coli form more frequently in air–solid biofilm culture than in liquid culture. In the current study, we modified a cell filamentation method as a more efficient and rapid alternative for quantifying PCs. This modified method yielded results consistent with those of the conventional method with 103–104 times higher sensitivity and less detection time, within several hours, and further revealed the existence of multiple levels of type I PCs, including a substantial number of deeply dormant cells. This study also discovered a potential epigenetic memory mechanism, spanning several generations (four or six cell divisions), which influences type II PC formation based on prior biofilm experience in E. coli.
Mycobacterium paratuberculosis: A HERV Turn-On for Autoimmunity, Neurodegeneration, and Cancer?
Authors: Dow Coad Thomas , Pierce Ellen S. , Sechi Leonardo A.
Published: September 2024

Human endogenous retroviruses (HERVs) are remnants of ancient retroviral infections that, over millions of years, became integrated into the human genome. While normally inactive, environmental stimuli such as infections have contributed to the transcriptional reactivation of HERV-promoting pathological conditions, including the development of autoimmunity, neurodegenerative disease and cancer. What infections trigger HERV activation? Mycobacterium avium subspecies paratuberculosis (MAP) is a pluripotent driver of human disease. Aside from granulomatous diseases, Crohn’s disease, sarcoidosis and Blau syndrome, MAP is associated with autoimmune disease: type one diabetes (T1D), multiple sclerosis (MS), rheumatoid arthritis (RA) and autoimmune thyroiditis. MAP is also associated with Alzheimer’s disease (AD) and Parkinson’s disease (PD). Autoimmune diabetes, MS and RA are the diseases with the strongest MAP/HERV association. There are several other diseases associated with HERV activation, including diseases whose epidemiology and/or pathology would prompt speculation for a causal role of MAP. These include non-solar uveal melanoma, colon cancer, glioblastoma and amyotrophic lateral sclerosis (ALS). This article further points to MAP infection as a contributor to autoimmunity, neurodegenerative disease and cancer via the un-silencing of HERV. We examine the link between the ever-increasing number of MAP-associated diseases and the MAP/HERV intersection with these diverse medical conditions, and propose treatment opportunities based upon this association.
Spread Spectrum Induced Polarization (SSIP) Survey for the Qiushuwan Copper–Molybdenum Deposits in Southern Henan Province, China
Authors: Ahmad Jawad , Chen Rujun , Ahmed Ijaz , Yaseen Muhammad , Shah Shahid Ali , Rahim Osama Abdul , Ullah Farid , Fahad Shah , Rui Li
Published: September 2024

The Qiushuwan Cu-Mo deposit, situated in the East Qinling molybdenum belt, is a notable mining site renowned for its considerable quantities of medium-sized molybdenum. The goal of this study is to improve comprehension and identify additional mineral resources by conducting a thorough examination of the mine using the spread spectrum-induced polarization (SSIP) technique. Gathering SSIP data, conducting geological investigations, and examining the electrical characteristics of rock and mineral samples along Profile-80 led to significant discoveries. The investigation identified two significant ore bodies with high conductivity: C2, linked to granite porphyry and molybdenum veins, and C4, associated with a skarn deposit containing a concentrated amount of copper ore. This study used resistivity models created from SSIP data to find out how conductivity changed in different parts of the research area. Additional drill verifications validated these findings, indicating the presence of potential mineral resources. The petrographic analysis of core samples showed that minerals like pyrite, molybdenite, chalcopyrite, epidote, calcite, and garnet were present. Notably, the samples frequently contained both pyrite and molybdenite together. Sample 04-2 contained substantial quantities of molybdenite and pyrite; Sample 05-1 had occasional pyrite; and Sample 07-4 included both pyrite and chalcopyrite. These findings offer useful insights for evaluating the magnitude and economic feasibility of the mineral deposits; however, additional investigation is required to completely comprehend the scope of the resources. The integration of borehole data and the alignment of geological sections with inversion models confirmed the validity of the conclusions. The core samples that were retrieved show a lot of different minerals, including valuable ores and minerals that have been changed. Pyrite and molybdenite are always found together. These findings establish a solid basis for further investigation and the sustainable management of resources. This study contributes to the understanding of the Qiushuwan Cu-Mo deposit and advances exploration techniques using the spread spectrum-induced polarization (SSIP) method. It provides useful information for geologists, mining professionals, and stakeholders involved in resource usage.
First Record of Romanechite in the Apulian Karst (Southern Italy) Resulting from the Interaction of Limestones and Clay Minerals
Authors: Fornelli Annamaria , Micheletti Francesca , Acquafredda Pasquale , Mangone Annarosa
Published: September 2024

A new occurrence of the Mn-Ba ore mineral, romanechite, has been discovered in a small paleo-doline of the Apulian karst on Mesozoic carbonate rock successions, characterized by reddish incrustations and nodules made essentially by Fe-bearing calcite. The conditions under which Mn-Ba ore minerals form represent an intriguing area of research, as these minerals can act as scavengers for heavy elements, impacting soils, surface sediments, and even associated aquatic systems. The genesis of romanechite is linked to the progressive interaction of silicate aqueous solutions enriched in Al, Si, and Fe with the limestone substrate. The findings provide new insights into the genetic processes responsible for the formation of reddish Mn incrustations, supporting their polygenetic origin because of the chemical alteration of limestone and allochthonous siliciclastic muds.