bluuebunny/crossref_metadata_2025 huggingface dataset:
Successful Transvenous Extraction of Adult Dirofilaria immitis Parasites from a Naturally Infected Domestic Ferret (Mustela putorius furo)
Authors: Mohr-Peraza Eva , Matos Jorge Isidoro , García-Rodríguez Sara Nieves , Santana-González Alexis José , Carretón Elena , Montoya-Alonso José Alberto
Published: August 2024

Heartworm disease caused by Dirofilaria immitis is a serious and underdiagnosed cardiovascular condition in domestic ferrets. Hemodynamic changes caused by parasitization in ferrets cause a potentially fatal syndrome, but its clinical findings and treatment have not yet been standardized. The objective of this study was to describe the clinical case of a successful surgical extraction in a ferret infected by D. immitis. The patient was a 2-year-old, 1.5 kg asymptomatic male domestic ferret. The infection was diagnosed using a commercial test for the detection of D. immitis antigens. Subsequently, their clinical status was evaluated using serological and imaging diagnostic tests, and it was finally decided to perform surgical extraction of the adult worms. The ferret was anesthetized and placed in the left lateral decubitus position to perform a venotomy in the right jugular vein. Endoscopic extraction basket-shaped devices were used in the right atrial cavity under fluoroscopic guidance following the Seldinger endovascular surgery technique. With careful handling, two adult parasites were manually removed. A transthoracic echocardiogram performed after the procedure confirmed the absence of heartworms. The ferret recovered without complications and was discharged within 24 h. In the clinical review, 30 days after surgery, no notable alterations or symptoms were observed. This case report describes the first complete surgical removal of adult D. immitis parasites in a naturally infected ferret.
Heat Stress Induces Alterations in Gene Expression of Actin Cytoskeleton and Filament of Cellular Components Causing Gut Disruption in Growing–Finishing Pigs
Authors: Choi Yohan , Park Hyunju , Kim Joeun , Lee Hyunseo , Kim Minju
Published: August 2024

We aimed to investigate the impact of heat stress (HS) on the expression of tight junction (TJ) proteins and the interaction between genes affecting intestinal barrier function using transcriptomics in the porcine jejunum. Twenty-four barrows (crossbred Yorkshire × Landrace × Duroc; average initial body weight, 56.71 ± 1.74 kg) were placed in different temperatures (normal temperature [NT]; HS) and reared for 56 days. At the end of the experiment, jejunal samples were collected from three pigs per treatment for transcriptome and reverse-transcription quantitative polymerase chain reaction (RT-qPCR) analyses. We identified 43 differentially expressed genes, involving five Kyoto Encyclopedia of Genes and Genomes pathways, eight molecular functions, seven cellular components (CCs), and nine biological processes, using gene ontology enrichment analysis. Genes associated with the actin cytoskeleton, filament-binding pathways, and TJ proteins were selected and analyzed by RT-qPCR. Significant differences in relative mRNA expression showed that downregulated genes in the HS group included ZO1, CLDN1, OCLN, PCK1, and PCK2, whereas ACTG2, DES, MYL9, MYLK, TPM1, TPM2, CNN1, PDLIM3, and PCP4 were upregulated by HS (p < 0.05). These findings indicate that HS in growing-finishing pigs induces depression in gut integrity, which may be related to genes involved in the actin cytoskeleton and filaments of CC.
Phytochemical Study of Ethanol Extract of Gnaphalium uliginosum L. and Evaluation of Its Antimicrobial Activity
Authors: Davydova Lilia , Menshova Angelina , Shumatbaev Georgiy , Babaev Vasily , Nikitin Evgeny
Published: August 2024

This study evaluates the antibacterial and antifungal effects of ethanol extracts from Gnaphalium uliginosum L. derived from freshly harvested plant biomass, including stems, leaves, flowers, and roots. The extract was analyzed using gas chromatography-mass spectrometry (GC-MS) to determine its antimicrobial activity against phytopathogenic bacteria and fungi. Two methods were used in the experiments: agar well diffusion and double serial dilution. Extraction was carried out using the maceration method with different temperature regimes (25 °C, 45 °C, and 75 °C) and the ultrasonic method at various powers (63–352 W) for different durations (5 and 10 min). It was found that the 70% ethanol extract obtained through the ultrasonic experiment at 189 W power for 10 min and at 252 W power for 5 min had the highest antimicrobial activity compared to the maceration method. The most sensitive components of the extracts were the Gram-positive phytopathogenic bacteria Clavibacter michiganensis and the Gram-negative phytopathogenic bacteria Erwinia carotovora spp., with MIC values of 156 μg/mL. Among the fungi, the most sensitive were Rhizoctonia solani and Alternaria solani (MIC values in the range of 78–156 µg/mL). The evaluation of the antimicrobial activity of extracts using the diffusion method established the presence of a growth suppression zone in the case of C. michiganensis (15–17 mm for flowers, leaves, and total biomass), which corresponds to the average level of antimicrobial activity. These findings suggest that G. uliginosum has potential as a source of biologically active compounds for agricultural use, particularly for developing novel biopesticides.
Artificial Intelligence-Driven Analysis of Antimicrobial-Resistant and Biofilm-Forming Pathogens on Biotic and Abiotic Surfaces
Authors: Mishra Akanksha , Tabassum Nazia , Aggarwal Ashish , Kim Young-Mog , Khan Fazlurrahman
Published: August 2024

The growing threat of antimicrobial-resistant (AMR) pathogens to human health worldwide emphasizes the need for more effective infection control strategies. Bacterial and fungal biofilms pose a major challenge in treating AMR pathogen infections. Biofilms are formed by pathogenic microbes encased in extracellular polymeric substances to confer protection from antimicrobials and the host immune system. Biofilms also promote the growth of antibiotic-resistant mutants and latent persister cells and thus complicate therapeutic approaches. Biofilms are ubiquitous and cause serious health risks due to their ability to colonize various surfaces, including human tissues, medical devices, and food-processing equipment. Detection and characterization of biofilms are crucial for prompt intervention and infection control. To this end, traditional approaches are often effective, yet they fail to identify the microbial species inside biofilms. Recent advances in artificial intelligence (AI) have provided new avenues to improve biofilm identification. Machine-learning algorithms and image-processing techniques have shown promise for the accurate and efficient detection of biofilm-forming microorganisms on biotic and abiotic surfaces. These advancements have the potential to transform biofilm research and clinical practice by allowing faster diagnosis and more tailored therapy. This comprehensive review focuses on the application of AI techniques for the identification of biofilm-forming pathogens in various industries, including healthcare, food safety, and agriculture. The review discusses the existing approaches, challenges, and potential applications of AI in biofilm research, with a particular focus on the role of AI in improving diagnostic capacities and guiding preventative actions. The synthesis of the current knowledge and future directions, as described in this review, will guide future research and development efforts in combating biofilm-associated infections.
Bacteriophage Therapy on an In Vitro Wound Model and Synergistic Effects in Combination with Beta-Lactam Antibiotics
Authors: Santamaría-Corral Guillermo , Aguilera-Correa John Jairo , Esteban Jaime , García-Quintanilla Meritxell
Published: August 2024

One of the primary opportunistic pathogens that can cause a wide range of diseases is Pseudomonas aeruginosa. This microorganism can become resistant to practically every antibacterial currently in use, including beta-lactam antibiotics. Its ability to proliferate as biofilm has been linked to, among other things, the failure of antimicrobial therapies. Due to a variety of virulence factors and host immune system modifications, P. aeruginosa is one of the most significant and common bacteria that colonize wounds and burns. A novel therapeutic option for treating these multidrug-resistant (MDR) bacterial infections is the combination of antibiotics and bacteriophages. This approach has been linked to improved biofilm penetration, a decreased selection of antibiotic and bacteriophage resistance, and an enhanced antibacterial impact. Combining the F1Pa bacteriophage and beta-lactam antibiotics reduced the viability of the mature biofilm of MDR P. aeruginosa strains and suppressed bacterial growth in vitro. F1Pa critically reduced the amount of biofilm that MDR P. aeruginosa clinical strains formed in the in vitro wound model. These findings highlight the bacteriophage F1Pa’s therapeutic potential as a prophylactic topical treatment against MDR pseudomonal infections in wounds and burns.
Antibiotic Susceptibility of Aerobic and Facultative Anaerobic Gram-Negative Rods in Hong Kong and Implications on Usefulness of Ceftazidime-Avibactam and Ceftolozane-Tazobactam
Authors: Teng Jade L. L. , Chan Elaine , Li Tsz Tuen , Kwan Tsz Ying , Chan Ka Fai , Li Wing Ho , Tang Viki W. K. , Yeung Man Lung , Lau Susanna K. P. , Woo Patrick C. Y.
Published: August 2024

Due to the increasing resistance of aerobic and facultative anaerobic Gram-negative rods, ceftazidime-avibactam and ceftolozane-tazobactam have been launched in the market in the last few years. In this study, we analyzed the susceptibility pattern of the major aerobic and facultative anaerobic Gram-negative rods in Hong Kong for ceftazidime-avibactam, ceftolozane-tazobactam, four other broad-spectrum antibiotics commonly used in Hong Kong and colistin. For 300 isolates collected from January to December 2021, non-ESBL-producing Enterobacterales, ESBL-producing Enterobacterales and Pseudomonas aeruginosa were highly susceptible to ceftazidime-avibactam (all 100%) and ceftolozane-tazobactam (98.7%, 99.7% and 94.3%). For 32 archived ESBL-producing Klebsiella pneumoniae isolates collected between January 2014 and March 2023, all were susceptible to ceftazidime-avibactam and ceftolozane-tazobactam. For 101 archived carbapenemase-producing Enterobacterales, their susceptibilities to ceftazidime-avibactam and ceftolozane-tazobactam varied depending on the type of carbapenemase produced. Both had high activities against OXA-producing strains (97.1% and 76.5%, respectively) but were 100% resistant for NDM-producing and NDM+OXA-producing strains. All KPC-producing strains were susceptible to ceftazidime-avibactam but resistant to ceftolozane-tazobactam. Ceftazidime-avibactam and ceftolozane-tazobactam are good alternatives for the management of infections caused by ESBL-producing Enterobacterales and selective strains of carbapenemase-producing Enterobacterales in Hong Kong.
Days of Antibiotic Spectrum Coverage (DASC) as a Metric for Evaluating the Impact of Prospective Audit and Feedback (PAF) against Long-Term Broad-Spectrum Antibiotic Use
Authors: Shibata Yuichi , Hirai Jun , Mori Nobuaki , Asai Nobuhiro , Hagihara Mao , Mikamo Hiroshige
Published: August 2024

The present study aimed to evaluate the impact of prospective audit and feedback (PAF) on the use of inpatient broad-spectrum antibiotics for more than 10 days using days of therapy (DOT) and a novel metric called days of antibiotic spectrum coverage (DASC) to assess whether the antimicrobial spectrum was narrowed. Conducted at Aichi Medical University Hospital in Japan, the study compared a six-month baseline period (April to September 2022) with a six-month intervention period (April to September 2023). The primary outcome measures were changes in DOT/patient and DASC/patient for broad-spectrum antibiotics. Propensity score matching was performed between two periods and a total of 172 patients were included in the study (pre-intervention, n = 86; intervention, n = 86). The DASC/patient of broad-spectrum antibiotics was statistically decreased in the intervention period compared to that in the baseline period (153.3 vs. 122.7, p < 0.05). Additionally, our PAF intervention led to a switch to narrow-spectrum antimicrobial therapy without increasing all-cause 30-day mortality (5.8% vs. 5.8%, p = 1.0). However, the DOT/patient, DASC/patient, and DASC/DOT of all antimicrobials were not significantly changed. Our study concluded that we should reconsider the timing of PAF intervention by evaluating the effort of PAF by using DOT and DASC.
Comparison of Hypervirulent and Non-Hypervirulent Carbapenem-Resistant Acinetobacter baumannii Isolated from Bloodstream Infections: Mortality, Potential Virulence Factors, and Combination Therapy In Vitro
Authors: Yao Likang , Liu Ningjing , Guo Yingyi , Zhuo Chuyue , Yang Xu , Wang Yijing , Wang Jiong , Li Feifeng , Li Jiahui , He Nanhao , Chen Jiakang , Lin Yexin , Xiao Shunian , Zhuo Chao
Published: August 2024

Hypervirulent carbapenem-resistant Acinetobacter baumannii (hv-CRAB) has emerged in bloodstream infections (BSI). Cases of BSI caused by hv-CRAB (hv-CRAB-BSI) had posed a significant threat to hospitalized patients. In this study, 31 CRAB strains isolated from Chinese BSI patients were analyzed, of which 24 were identified as hv-CRAB-BSI and 7 as non-hv-CRAB-BSI, using the Galleria mellonella infection model. Patients with hv-CRAB-BSI had higher rates of septic shock (79.2% vs. 14.3%, p = 0.004) and mortality (66.7% vs. 14.3%, p = 0.028). All strains were resistant to most antibiotics but sensitive to colistin. Hv-CRAB-BSI showed lower resistance to minocycline than non-hv-CRAB-BSI (54.2% vs. 100%, p = 0.03). Whole-genome sequencing revealed that the detection rates of immune modulation genes ptk and epsA in hv-CRAB-BSI were significantly higher than in non-hv-CRAB-BSI (91.7% vs. 28.6%, p = 0.002). Additionally, all ST457 hv-CRAB-BSI lacked abaR, and all ST1486 non-hv-CRAB-BSI lacked adeG. The checkerboard dilution method assessed the efficacies of various antibiotic combinations, revealing that although synergism was rarely observed, the combination of colistin and minocycline showed the best efficacy for treating CRAB-BSI, regardless of whether the infections were hv-CRAB-BSI or non-hv-CRAB-BSI. These findings highlight the importance of analyzing molecular characteristics and exploring effective treatment strategies for hv-CRAB-BSI.
5-Fluorouracil in Combination with Calcium Carbonate Nanoparticles Loaded with Antioxidant Thymoquinone against Colon Cancer: Synergistically Therapeutic Potential and Underlying Molecular Mechanism
Authors: Deng Xi , Yang Zhongming , Chan Kim Wei , Ismail Norsharina , Abu Bakar Md Zuki
Published: August 2024

Colon cancer is the third most common cancer worldwide, with high mortality. Adverse side effects and chemoresistance of the first-line chemotherapy 5-fluorouracil (5-FU) have promoted the widespread use of combination therapies. Thymoquinone (TQ) is a natural compound with potent antioxidant activity. Loading antioxidants into nano delivery systems has been a major advance in enhancing their bioavailability to improve clinical application. Hence, this study aimed to prepare the optimal TQ-loaded calcium carbonate nanoparticles (TQ-CaCO3 NPs) and investigate their therapeutic potential and underlying molecular mechanisms of TQ-CaCO3 NPs in combination with 5-FU against colon cancer. Firstly, we developed purely aragonite CaCO3 NPs with a facile mechanical ball-milling method. The pH-sensitive and biocompatible TQ-CaCO3 NPs with sustained release properties were prepared using the optimal synthesized method (a high-speed homogenizer). The in vitro study revealed that the combination of TQ-CaCO3 NPs (15 μM) and 5-FU (7.5 μM) inhibited CT26 cell proliferation and migration, induced cell apoptosis and cell cycle arrest in the G0/G1 phase, and suppressed the CT26 spheroid growth, exhibiting a synergistic effect. Finally, network pharmacology and molecular docking results indicated the potential targets and crucial signaling pathways of TQ-CaCO3 NPs in combination with 5-FU against colon cancer. Therefore, TQ-CaCO3 NPs combined with 5-FU could enhance the anti-colon cancer effects of 5-FU with broader therapeutic targets, warranting further application for colon cancer treatment.
Research on Predicting the Mechanical Characteristics of Deep-Sea Mining Transportation Pipelines
Authors: Hu Qiong , Qin Yu , Zhu Jingyan , Zheng Meiling , Huang Junqiang , Ou Yujia
Published: August 2024

Deep-sea mining, as a critical direction for the future development of mineral resources, places significant importance on the mechanical characteristics of its transportation pipelines for the safety and efficiency of the entire mining system. This paper establishes a simulation model of the deep-sea mining system based on oceanic environmental loads and the mechanical theory of deep-sea mining transportation pipelines. Through a static analysis, the effective tension along the pipeline length, the maximum values of bending moment, and the minimum values of bending radius are determined as critical points for the dynamic analysis of pipeline mechanical characteristic monitoring. A dynamic simulation analysis of the pipeline’s mechanical characteristics was conducted, and simulation sensor data were obtained as inputs for the prediction model construction. A prediction model of pipeline mechanical characteristics based on the BP neural network was constructed, with the model’s prediction correlation coefficients all exceeding 0.95, enabling an accurate prediction of pipeline state parameters.
Conceptual Design of Seismic Retrofit of Existing Bridges by Deck Isolation: Assessment of Effectiveness
Authors: Pettorruso Carlo , Quaglini Virginio
Published: August 2024

The creation of an isolation layer between decks and substructures has turned out to be a viable method for reducing the seismic vulnerability of existing bridges. However, to the Authors’ knowledge, a practical approach for a preliminary verification of the effectiveness of this intervention is lacking. The paper introduces a practical tool for a preliminary assessment of the needs of the rehabilitation of the bridge and of the effectiveness of the deck isolation to improve its seismic performance by comparing the demands of the as-built structure and of the piers alone, expressed in terms of equivalent accelerations, to the maximum seismic acceleration allowed to maintain the substructure behavior in the elastic range. A practical implementation of the criterion is illustrated in a parametric study, considering prototypes of simply supported and continuous deck bridges with features common to the bridges of the Italian stock. The results of the study provide some indications about the inherent weaknesses of the examined pier typologies and the positive effect of the dead load of the deck on the effectiveness of deck isolation.
Artificial Intelligence Advancements for Accurate Groundwater Level Modelling: An Updated Synthesis and Review
Authors: Pourmorad Saeid , Kabolizade Mostafa , Dimuccio Luca Antonio
Published: August 2024

Artificial Intelligence (AI) methods, including Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference Systems (ANFISs), Support Vector Machines (SVMs), Deep Learning (DL), Genetic Programming (GP) and Hybrid Algorithms, have proven to be important tools for accurate groundwater level (GWL) modelling. Through an analysis of the results obtained in numerous articles published in high-impact journals during 2001–2023, this comprehensive review examines each method’s capabilities, their combinations, and critical considerations about selecting appropriate input parameters, using optimisation algorithms, and considering the natural physical conditions of the territories under investigation to improve the models’ accuracy. For example, ANN takes advantage of its ability to recognise complex patterns and non-linear relationships between input and output variables. In addition, ANFIS shows potential in processing diverse environmental data and offers higher accuracy than alternative methods such as ANN, SVM, and GP. SVM excels at efficiently modelling complex relationships and heterogeneous data. Meanwhile, DL methods, such as Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNNs), are crucial in improving prediction accuracy at different temporal and spatial scales. GP methods have also shown promise in modelling complex and nonlinear relationships in groundwater data, providing more accurate and reliable predictions when combined with optimisation techniques and uncertainty analysis. Therefore, integrating these methods and optimisation techniques (Hybrid Algorithms), tailored to specific hydrological and hydrogeological conditions, can significantly increase the predictive capability of GWL models and improve the planning and management of water resources. These findings emphasise the importance of thoroughly understanding (a priori) the functionalities and capabilities of each potentially beneficial AI-based methodology, along with the knowledge of the physical characteristics of the territory under investigation, to optimise GWL predictive models.
Characterization of Shallow Sedimentary Layers in the Oran Region Using Ambient Vibration Data
Authors: Saadi Ahmed , Galiana-Merino Juan José , Semmane Fethi , Yelles-Chaouche Abdelkrim , Issaadi Abdelouahab
Published: August 2024

This study investigates the structure of shear-wave velocities (Vs) in the shallow layers of the Oran region, north-west of Algeria, using non-invasive techniques based on ambient vibration arrays. The region has experienced several moderate earthquakes, including the historical Oran earthquake of 1790. Ambient vibration measurements were carried out at 15 sites throughout the study area. Two methods were used: spatial autocorrelation (SPAC) and frequency–wavenumber analysis (f-k), which allowed us to better constrain Rayleigh wave dispersion curves. The inversion of the dispersion curves derived from the f-k analysis allowed for estimating the shear-wave velocity profiles and the Vs30 value at the sites under study. The other important result of the present study is an empirical equation that has been proposed to predict Vs30 in the Oran region. The determination of near-surface shear-wave velocity profiles is an important step in the assessment of seismic hazard. This study has demonstrated the effectiveness of using ambient vibration array techniques to estimate the soil Vs structure.
Considerations Regarding Sandblasting of Ti and Ti6Al4V Used in Dental Implants and Abutments as a Preconditioning Stage for Restorative Dentistry Works
Authors: Ciobotaru Ioana-Alina , Stoicanescu Maria , Budei Roxana , Cojocaru Anca , Vaireanu Danut-Ionel
Published: August 2024

Sandblasting materials used for dental restoration are a valuable preconditioning technique that enhances the physical properties and promotes osseointegration and cell adhesion. Triplicate groups of Ti medical grade 4 and Ti6Al4V were blasted with 16 series of various naturally occurring and synthetically produced spraying materials of controlled granulometry at three spraying durations each and two spraying pressures, and the results were tested for the determination of the surface roughness taken as an average of 80 points ±5 points for each particular series of operating parameters. SEM analysis and specific tests to see whether or not cell cultures proliferate on the treated materials were also conducted. It was found that in all cases, regardless of the spraying material or working conditions, the roughness profile achieved is a uniformly distributed one. A reduction in the blasting pressure by half led to a decrease in the roughness between 30 and 35%. The use of glass balls as blasting material led to decreased roughness and more uniformly distributed roughness values for Ti as well as for Ti6Al4V, regardless of spraying duration or applied pressure compared to other spraying materials. Blasting with olivine led to increased, as well as uniformly distributed, values, and hence the conclusion that one may control the roughness size by choosing one or another of the above materials without the need to change any other operating parameters. In the case of Ti, the achieved roughness is greater than in the case of Ti4Al6V, regardless of the blasting material; the differences are smaller the softer the sandblasting material due to the fact that Ti alloys have better mechanical properties and increased hardness compared to pure Ti. SEM analysis showed that the use of sintered hydroxyapatite as an additive to the blasting material does not necessarily lead to a substantial deposition of hydroxyapatite on the substrate materials; only traces of it were identified during the analysis. As a general conclusion, this study showed that by sandblasting Ti and Ti6Al4V with different spraying materials, one may control the surface roughness, and this technique may be an attractive method for preconditioning these materials for restorative dentistry.
Enhancing Depression Detection: A Stacked Ensemble Model with Feature Selection and RF Feature Importance Analysis Using NHANES Data
Authors: Selvaraj Annapoorani , Mohandoss Lakshmi
Published: August 2024

Around the world, 5% of adults suffer from depression, which is often inadequately treated. Depression is caused by a complex relationship of cultural, psychological, and physical factors. This growing issue has become a significant public health problem globally. Medical datasets often contain redundant characteristics, missing information, and high dimensionality. By using an iterative floating elimination feature selection algorithm and considering various factors, we can reduce the feature set and achieve optimized outcomes. The research utilizes the 36-Item Short Form Survey (SF-36) from the NHANES 2015–16 dataset, which categorizes data into seven groups relevant to quality of life and depression. This dataset presents a challenge due to its imbalance, with only 8.08% of individuals diagnosed with depression. The Depression Ensemble Stacking Generalization Model (DESGM) employs stratified k-fold cross-validation and oversampling for training data. DESGM enhances the classification performance of both base learners (linear support vector machine, perceptron, artificial neural network, linear discriminant analysis, and K-nearest neighbor) and meta-learners (logistic regression). The model achieved an F1 score of 0.9904 and an accuracy of 98.17%, with no instances of depression misdiagnosed.
Analysis of Damage and Permeability Evolution of Sandstone under Compression Deformation
Authors: Rong Yao , Sun Yang , Chen Xiangsheng , Ding Haibin , Xu Changjie
Published: August 2024

A large number of experimental studies have demonstrated that the permeability and damage of rock are not constant but rather functionally dependent on stresses or stress-induced deformation. Neglecting the influence of damage and permeability evolution on rock mechanics and sealing properties can result in an overestimation of the safety and stability of underground engineering, leading to an incomplete assessment of the risks associated with surrounding rock failure. To address this, the damage and permeability evolution functions of rock under compression were derived through a combination of experimental results and theoretical analysis, unifying the relationship between porosity and permeability in both porous media flow and fractured flow. Based on this, a fluid–solid coupled seepage model considering rock damage and permeability evolution was proposed. More importantly, this model was utilized to investigate the behavior of deformation, damage, and permeability, as well as their coupled effects. The model’s validity was verified by comparing its numerical results with experimental data. The analysis results show that the evolution of permeability and porosity resulted from a competitive interaction between effective mean stress and stress-induced damage. When the effective mean stress was dominant, the permeability tended to decrease; otherwise, it followed an increasing trend. The damage evolution was primarily related to stress- and pressure-induced crack growth and irreversible deformation. Additionally, the influence of the seepage pressure on the strength, damage, and permeability of the investigated rock was evaluated. The model results reveal the damage and permeability evolution of the rock under compression, which has a certain guiding significance for the stability and safety analysis of rock in underground engineering.
Light It Up: Boarding for Automated Low-Capacity Shuttles through Ambient Visual Cues
Authors: Wallner Vivien , Meschtscherjakov Alexander , Mirnig Alexander G.
Published: August 2024

Once public transport is fully automated, human operators will no longer be needed for tasks like manoeuvring, paying, and boarding. Interfaces must evolve to cover the entire interaction chain from booking to boarding. We present a user-centred design of a mobile-based booking application and an LED-based boarding interface for automated shuttles. Our approach included comprehensive requirements and feasibility analyses to ensure technical viability and user satisfaction. Laboratory study results highlight the advantages and challenges of the boarding interface, underscoring the importance of early user requirements and feasibility assessments in designing automated shuttle systems.
Game-Based Flexible Merging Decision Method for Mixed Traffic of Connected Autonomous Vehicles and Manual Driving Vehicles on Urban Freeways
Authors: Du Zhibin , Xie Hui , Zhai Pengyu , Yuan Shoutong , Li Yupeng , Wang Jiao , Wang Jiangbo , Liu Kai
Published: August 2024

Connected Autonomous Vehicles (CAVs) have the potential to revolutionize traffic systems by autonomously handling complex maneuvers such as freeway ramp merging. However, the unpredictability of manual-driven vehicles (MDVs) poses a significant challenge. This study introduces a novel decision-making approach that incorporates the uncertainty of MDVs’ driving styles, aiming to enhance merging efficiency and safety. By framing the CAV-MDV interaction as an incomplete information static game, we categorize MDVs’ behaviors using a Gaussian Mixture Model–Support Vector Machine (GMM-SVM) method. The identified driving styles are then integrated into the flexible merging decision process, leveraging the concept of pure-strategy Nash equilibrium to determine optimal merging points and timing. A deep reinforcement learning algorithm is employed to refine CAVs’ control decisions, ensuring efficient right-of-way acquisition. Simulations at both micro and macro levels validate the method’s effectiveness, demonstrating improved merging success rates and overall traffic efficiency without compromising safety. The research contributes to the field by offering a sophisticated merging strategy that respects real-world driving behavior complexity, with potential for practical applications in urban traffic scenarios.
PRISMA on Machine Learning Techniques in Smart City Development
Authors: Ionescu Ștefan-Alexandru , Jula Nicolae Marius , Hurduzeu Gheorghe , Păuceanu Alexandrina Maria , Sima Alexandra-Georgiana
Published: August 2024

This article investigates the innovative role of machine learning (ML) in the development of smart cities, emphasizing the critical interrelationship between ML and urban environments. While existing studies address ML and urban settings separately, this work uniquely examines their intersection, highlighting the transformative potential of ML in urban development. Utilizing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, a systematic and reproducible approach was employed to review 42 relevant studies. The analysis reveals four key themes: transportation and traffic optimization, people and event flow tracking, sustainability applications, and security use cases. These findings underscore ML’s ability to revolutionize smart city initiatives by enhancing efficiency, sustainability, and security. This review identifies significant research gaps and proposes future directions, positioning ML as a cornerstone in the evolution of intelligent urban environments.
Balancing Staff Finishing Times vs. Minimizing Total Travel Distance in Home Healthcare Scheduling
Authors: Saksuriya Payakorn , Likasiri Chulin
Published: August 2024

Cost reduction and staff retention are important optimization objectives in home healthcare (HHC) systems. Home healthcare operators need to balance their objectives by optimizing resource use, service delivery and profits. Minimizing total travel distances to control costs is a common routing problem objective while minimizing total finishing time differences is a scheduling objective whose purpose is to enhance staff satisfaction. To optimize routing and scheduling, we propose mixed integer linear programming with a bi-objective function, which is a subset of the vehicle routing problem with time windows (VRPTWs). VRPTWs is a known NP-hard problem, and optimal solutions are very hard to obtain in practice. Metaheuristics offer an alternative solution to this type of problem. Our metaheuristic uses the simulated annealing algorithm and weighted sum approach to convert the problems to single-objective problems and is equipped with operators including swapping, moving, path exchange and ruin and recreate. The results show, firstly, that the algorithm can effectively find the Pareto front, and secondly, that minimizing total finishing time differences to balance the number of jobs per caretaker is an efficient way to tackle HHC scheduling. A statistical test shows that the algorithm can obtain the Pareto front with a lower number of weighted sum problems.
Spectral and Wavelet Analysis in the Assessment of the Impact of Corrosion on the Structural Integrity of Mining Equipment
Authors: Radu Sorin Mihai , Vîlceanu Florin , Toderas Mihaela , Dinescu Stela
Published: August 2024

Corrosion is a major problem in the mining industry, significantly affecting the durability and reliability of mining equipment. In order to better evaluate and understand these effects, in the first part of this study, the analysis by the finite element method of the metallic structure of the rotary arm of an ERc 1400-30/7 bucket excavator type, produced in Romania in 1985, is presented. This paper presents an analysis of the impact of corrosion on the structural integrity of mining equipment. The focus of the research is on the use of advanced spectral analysis methods and the implementation of wavelet analysis. These methods allow an increase in the degree of accuracy of the information and results obtained. The study also focused on the impact of corrosion on the natural frequencies and structural changes in mining equipment, which were evaluated based on advanced methods of structural analysis. The obtained results show that corrosion deeply affects the dynamic behaviour of the metallic structure, leading to significant changes in the dominant frequencies. It was found that the measured dominant frequencies show a tendency to increase with the increase of structural degradation, an observation that is consistent with the physical aspects of the phenomenon.
Credit Card Fraud: Analysis of Feature Extraction Techniques for Ensemble Hidden Markov Model Prediction Approach
Authors: Ogundile Olayinka , Babalola Oluwaseyi , Ogunbanwo Afolakemi , Ogundile Olabisi , Balyan Vipin
Published: August 2024

In the face of escalating credit card fraud due to the surge in e-commerce activities, effectively distinguishing between legitimate and fraudulent transactions has become increasingly challenging. To address this, various machine learning (ML) techniques have been employed to safeguard cardholders and financial institutions. This article explores the use of the Ensemble Hidden Markov Model (EHMM) combined with two distinct feature extraction methods: principal component analysis (PCA) and a proposed statistical feature set termed MRE, comprising Mean, Relative Amplitude, and Entropy. Both the PCA-EHMM and MRE-EHMM approaches were evaluated using a dataset of European cardholders and demonstrated comparable performance in terms of recall (sensitivity), specificity, precision, and F1-score. Notably, the MRE-EHMM method exhibited significantly reduced computational complexity, making it more suitable for real-time credit card fraud detection. Results also demonstrated that the PCA and MRE approaches perform significantly better when integrated with the EHMM in contrast to the conventional HMM approach. In addition, the proposed MRE-EHMM and PCA-EHMM techniques outperform other classic ML models, including random forest (RF), linear regression (LR), decision trees (DT) and K-nearest neighbour (KNN).
Comparative Electromyographic Analysis in Leg Press of Traditional Fitness Equipment, Traditional Outdoor Fitness Equipment, and a New Model of Outdoor Fitness Equipment in Trained Young Men
Authors: Abelleira-Lamela Tomás , Marcos-Pardo Pablo Jorge , Abraldes José Arturo , González-Gálvez Noelia , Espeso-García Alejandro , Esparza-Ros Francisco , Vaquero-Cristóbal Raquel
Published: August 2024

This study compares the electromyographic activity (EMG) of different muscle groups (rectus femoris, vastus lateralis, biceps femoris, tibialis anterior, and gastrocnemius) of the lower limbs when performing a traditional seated leg press (SLP) with a classic piece of outdoor fitness equipment (OFE-SLP), and with a new OFE leg press that allows the user to adjust the intensity of the exercise by means of a selectorized system (BIOFIT-LP). It was found that the EMG of the OFE-SLP was significantly lower than that of the SLP, but similar activations to those of the SLP were achieved with the BIOFIT-LP. In conclusion, the inclusion of a system to be able to change intensity of the exercise in OFE achieves an EMG activity similar to traditional machinery in trained young men.
Effect of Helix aspersa Mucus on the Regeneration of Skin with Photoaging Features in Different Methods of Application
Authors: Marchlewicz Mariola , Wojnarowicz Justyna , Wilk Aleksandra , Misiakiewicz-Has Kamila , Wiszniewska Barbara , Szumilas Kamila , Duchnik Ewa
Published: August 2024

Skin aging is associated with both intrinsic and extrinsic aging, with extrinsic aging caused by environmental factors and overlaying the effects of chronological aging. The main aim of this study was to evaluate the effect of preparations containing Helix aspersa snail mucus on skin regeneration with photoaging features. Before and 3 months after the series of treatments, skin biopsy specimens from the right preauricular region of the face were taken from six women. Histological, morphometric, and immunohistochemical analyses were performed. Positive changes, indicating a reduction in photoaging related to the reduction in epidermis thickness 3 months after the end of the treatments, were noted in each group. A statistically significant increase in the thickness of the collagen fiber bundles was also observed in the patients 3 months after a series of micro-needle mesotherapy treatments with snail mucus and 0.9% NaCl. There was a significant increase in the immuno-expression of Ki-67 and PCNA in the dermis. The aforementioned significance applies to patients in whom snail mucus was introduced with the use of micro-needle mesotherapy and needle-free mesotherapy. Moreover, a statistically significant increased area with the immunoexpression of MMP-2 in the dermis was observed in the above-mentioned groups of patients, who were treated with the preparation containing snail filtrate. The results of the study suggest that the use of snail mucus preparations for skincare, as well as its introduction by micro-needle and needleless mesotherapy, had a beneficial effect on the condition of the skin.
Fluoride Risk Assessment of Different Brands of Coffee Commercialized in the Canary Islands
Authors: Alejandro-Vega Samuel , Ruiz-Benitez-de-Lugo Sara , Hevia-Loredo Dachel , Paz-Montelongo Soraya , Hardisson Arturo , Rubio-Armendariz Carmen , Gutiérrez-Fernández Ángel J. , Jáudenes-Marrero Juan R.
Published: August 2024

Coffee is part of our daily lives since it is a drink with a symbolic value, both in our social relationships and as a stimulating drink. The main objective of this paper is to conduct a risk characterization of fluoride overexposure from the consumption of these beverages; for this purpose, in the present study, the fluoride concentration was determined in 80 samples of different brands of coffee commonly consumed in the Canary Islands, and the risk derived from their intake was then evaluated. Significant differences (p < 0.05) were found between the coffee brands soluble Nescafé Classic®, Saimaza®, Auchan®, Tirma® soft blend, and Hacendado® and the other analyzed brands. The brand that recorded the highest mean fluoride levels is “Hacendado descafeinado®” (0.308 mg/L). The problem with coffee is not the fluoride it contains but the fact that, according to the survey results, most coffee drinkers brew their coffee with tap water (over 51% of respondents use tap water). The results of the fluoride content in coffee prepared with tap water from the different areas of Tenerife in the Canary Islands (metropolitan, northern, and southern areas) have reported higher concentrations of fluoride: north (max. concentration found of 16.68 mg/L), south (max. concentration found of 8.47 mg/L) and metropolitan (max. concentration found of 4.73 mg/L). Coffee has not been identified as a risk of dietary overexposure to fluoride; however, the use of tap water for its brewing has been identified as a factor that considerably increases its concentration. Therefore, the use of bottled water is recommended, especially in regions such as the Canary Islands, which have high concentrations of fluoride in their water.
Application of Explosive Equivalency Approach in Blast-Induced Seismic Effect Prediction Using EXPLO5 Thermochemical Code
Authors: Stanković Siniša , Olivani Josip , Dobrilović Ivana , Sućeska Muhamed
Published: August 2024

Blasting is a key process that plays a significant role in various industries, including mining and construction. To measure the effectiveness and potential impact of a blast generated by different explosives, industry professionals use a widely accepted parameter known as TNT (trinitrotoluene) equivalent. This manuscript provides an overview of the approach based on the application of the explosive equivalency principle in the prediction of the seismic effects caused by the detonation of different explosives. The explosive equivalents of studied explosives are derived from the results of thermochemical calculations using the EXPLO5 code and compared to field tests. The results have demonstrated that the equivalency approach can potentially be a useful tool in the assessment of blast-induced seismic effects.
GenAI-Assisted Database Deployment for Heterogeneous Indigenous–Native Ethnographic Research Data
Authors: Wang Reen-Cheng , Yang David , Hsieh Ming-Che , Chen Yi-Cheng , Lin Weihsuan
Published: August 2024

In ethnographic research, data collected through surveys, interviews, or questionnaires in the fields of sociology and anthropology often appear in diverse forms and languages. Building a powerful database system to store and process such data, as well as making good and efficient queries, is very challenging. This paper extensively investigates modern database technology to find out what the best technologies to store these varied and heterogeneous datasets are. The study examines several database categories: traditional relational databases, the NoSQL family of key-value databases, graph databases, document databases, object-oriented databases and vector databases, crucial for the latest artificial intelligence solutions. The research proves that when it comes to field data, the NoSQL lineup is the most appropriate, especially document and graph databases. Simplicity and flexibility found in document databases and advanced ability to deal with complex queries and rich data relationships attainable with graph databases make these two types of NoSQL databases the ideal choice if a large amount of data has to be processed. Advancements in vector databases that embed custom metadata offer new possibilities for detailed analysis and retrieval. However, converting contents into vector data remains challenging, especially in regions with unique oral traditions and languages. Constructing such databases is labor-intensive and requires domain experts to define metadata and relationships, posing a significant burden for research teams with extensive data collections. To this end, this paper proposes using Generative AI (GenAI) to help in the data-transformation process, a recommendation that is supported by testing where GenAI has proven itself a strong supplement to document and graph databases. It also discusses two methods of vector database support that are currently viable, although each has drawbacks and benefits.
Mechanism of Rejuvenation in Aged SBS-Modified Asphalt by Density Functional Theory
Authors: Li Ping , Li Zhanghui , Cao Shenyang
Published: August 2024

As a large area of SBS-modified asphalt pavement entered the maintenance period, the aging and rejuvenation of SBS-modified asphalt have attracted attention in recent years. In order to further study the rejuvenation of aged SBS-modified asphalt, both rheological experiments and quantum mechanical simulations were used. Complex shear modulus (G*) and phase angle (δ) were used to analyze the rejuvenation effect of aged SBS-modified asphalt. Electron density, binding energy (Ebinding), and charge transfer number (Qtransfer) were used to observe the process of rejuvenation in aged SBS-modified asphalt. The results show that compared to asphalt components, SBS polymer was the least stable and most susceptible to breaking. After oxidative aging, SBS polymer with its aging products could impair the rejuvenation in aged asphalt. The interaction between aromatic components in rejuvenator and asphaltenes in aged asphalt was unstable and could be influenced by asphalt aging level. The interaction between heavy component molecules in aged asphalt with saturate component molecules in rejuvenator are closer than those with aromatic components molecules. The binding energies between saturate components in rejuvenator and asphaltenes in aged asphalt could be served as an evaluation indicator of rejuvenation.
Simulation Analysis and Experiment of Piezoelectric Pump with Tapered Cross-Section Vibrator
Authors: Hu Caiqi , Jiang Wei , Hu Xiaoqi , Ji Jing , Li Shengduo , Zhang Qingbo
Published: August 2024

In order to meet the requirements of microfluidic transport in the fields of medical, health, and microelectromechanical integration, a valve-less piezoelectric pump with a tapered cross-sectional vibrator was designed according to the bionic principles of fish swimming. Through theoretical analysis, the pattern of fluid flow in the pump chamber caused by the vibration of the piezoelectric vibrator was derived. The flow field of the piezoelectric pump was analyzed through simulation based on multiple physical fields coupling using the software of COMSOL Multiphysics (version 6.1). The velocity field distribution and its change law were obtained, and the fluid disturbance and instantaneous motion suppression phenomena were acquired as well. Based on the analysis of flow field streamline, the rule of generating vortexes was found. Thus, the driving mechanism of the vibrator with the tapered cross-section, which was consistent with the swimming principle of a fish tail, was verified. A prototype pump was made, and the pump performance was tested. The experimental data showed that the tested flow rate changed in the same trend as the simulated flow rate. When the driving voltage was 150 V and the driving frequency was 588 Hz, the pump achieved a maximum output flow rate of 367.7 mL/min. These results indicated that the piezoelectric pump with the tapered cross-sectional vibrator has great potential of fluid transportation.