bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Clinical Pharmacist-Driven Weekend Antimicrobial Stewardship Coverage at a Quaternary Hospital
Authors: Elrefaei Hazem , El Nekidy Wasim S. , Nasef Rama , Motasem Manal , Mkarim Yara , Al Quteimat Osama , Hisham Mohamed , Ismail Rami , Abidi Emna , Afif Claude , El Lababidi Rania
Published: October 2024

Background and objective: Extending a consistent pharmacy antimicrobial stewardship weekend service was a newly implemented initiative. We sought to evaluate the impact of incorporating an Infectious Diseases (ID)-trained clinical pharmacist into an antimicrobial stewardship program (AMS) during weekends. Results: The number of documented interventions was 451 on 362 patients compared to 115 interventions on 108 patients during the pre-implementation period (p = 0.04), with interventions primarily targeting Watch antibiotics, as classified by the WHO AWaRe classification. A reduction in the LOS was observed, with a median of 16 days (8–34) during the post-implementation period compared to 27.5 days (10–56) during the pre-implementation period (p = 0.001). The median DOT increased during the post-implementation period to 8 (6–11), versus the increase to 7 (4–11) during the pre-implementation period (p ≤ 0.001). Finally, there was no significant difference observed in healthcare-associated CDI and infection-related readmission. Methods: This is a retrospective single-center, pre–post quasi-experimental study. Data including the documented pharmacist interventions were collected from the electronic medical record (EMR), the pre-implementation phase was in 2020, and post-implementation was in 2021. The primary outcome was to identify the number of AMS interventions through prospective audit and feedback review analysis. Secondary outcomes included antibiotic days of therapy (DOT), length of hospital stay (LOS), healthcare-associated Clostridioides difficile infection (CDI), and infection-related readmission. Conclusions: The pharmacist-driven weekend AMS is an opportunity for pharmacists to intervene and optimize patients’ care plans. This initiative demonstrated significant increased AMS-related interventions, promoted judicious antimicrobial use, and contributed to a reduced length of hospital stay. Our findings need to be replicated in a larger prospective study.
Molecular Mechanisms of Biofilm Formation in Helicobacter pylori
Authors: Fauzia Kartika Afrida , Effendi Wiwin Is , Alfaray Ricky Indra , Malaty Hoda M. , Yamaoka Yoshio , Mifthussurur Muhammad
Published: October 2024

Background: Biofilm formation in Helicobacter pylori (H. pylori) helps bacteria survive antibiotic exposure and supports bacterial colonization and persistence in the stomach. Most of the published articles have focused on one aspect of the biofilm. Therefore, we conducted the current study to better understand the mechanism of biofilm formation, how the biofilm contributes to antibiotic resistance, and how the biofilm modifies the medication delivery mechanism. Methods: We conducted a literature review analysis of the published articles on the Helicobacter pylori biofilm between 1998 and 2024 from the PubMed database to retrieve eligible articles. After applying the inclusion and exclusion criteria, two hundred and seventy-three articles were eligible for our study. Results: The results showed that biofilm formation starts as adhesion and progresses through micro-colonies, maturation, and dispersion in a planktonic form. Moreover, specific genes modulate each phase of biofilm formation. Few studies have shown that mechanisms, such as quorum sensing and diffusible signal factors, enhance coordination among bacteria when switching from biofilm to planktonic states. Different protein expressions were also observed between planktonic and biofilm strains, and the biofilm architecture was supported by exopolysaccharides, extracellular DNA, and outer membrane vesicles. Conclusions: This infrastructure is responsible for the increased survival of bacteria, especially in harsh environments or in the presence of antibiotics. Therefore, understanding the biofilm formation for H. pylori is crucial. This study illustrates biofilm formation in H. pylori to help improve the treatment of H. pylori infection.
Investigation of the Impact of Antibiotic Administration on the Preterm Infants’ Gut Microbiome Using Next-Generation Sequencing—Based 16S rRNA Gene Analysis
Authors: Aktaş Ahmet , Ekren Berkay , Yaşa Beril , Sezerman Osman , Nakipoğlu Yaşar
Published: October 2024

Background: The human gut microbiota is an extensive population of microorganisms, and it shows significant variations between periods of optimal health and periods of illness. Vancomycin-resistant Enterococcus (VRE) and carbapenem-resistant Klebsiella pneumoniae (CRKP) are both pathogenic agents (BPAs) that can colonize in the gut after dysbiosis of microbiotal composition following antibiotic treatment. Methods: This study aimed to investigate the impact of antibiotics on the microbiotal composition of the gut. For this purpose, the first pass meconiums of 20 patients and the first rectal swabs containing BPAs of the same patients after antibiotic treatment were studied using next-generation sequencing-based 16S rRNA gene analysis. The V1–V9 region of 16S rRNA was sequenced with Oxford Nanopore. Results: Twenty-five phyla were detected in the meconiums, and 12 of them were absent after antibiotic treatment. The four most prevalent phyla in meconiums were Bacillota, Pseudomonadota, Bacteroidota, and Actinomycetota. Only the relative abundance of Pseudomonadota was increased, while a significant decrease was observed in the other three phyla (p < 0.05). A significant decrease was observed in alpha-diversity in rectal swabs containing BPAs versus meconiums (p = 0.00408), whereas an increased variance was observed in beta-diversity in all samples (p < 0.05). As a result of a LEfSe analysis, Pseudomonadota was found to have a higher relative abundance in rectal swabs, and Bacillota was significantly higher in the meconiums of the twins. Conclusions: Our study strongly verified the relationship between the administration of antibiotics, dysbiosis, and colonization of BPAs in the infants’ gut microbiota. Further research would be beneficial and needed, comprising the natural development process of the infants’ gut microbiota.
Multitarget Phytocomplex: Focus on Antibacterial Profiles of Grape Pomace and Sambucus ebulus L. Lyophilisates Against Extensively Drug-Resistant (XDR) Bacteria and In Vitro Antioxidative Power
Authors: Kurćubić Vladimir S. , Đurović Vesna , Stajić Slaviša B. , Dmitrić Marko , Živković Saša , Kurćubić Luka V. , Mašković Pavle Z. , Mašković Jelena , Mitić Milan , Živković Vladimir , Jakovljević Vladimir
Published: October 2024

Objectives: This study was conceived with the aim of translating the experience and knowledge of the research group into the design and creation of multi-active phytocomplex cocktails from lyophilised winery by-products (Grape Pomace—GP) and weeds (Sambucus ebulus L., Dwarf Elder—DE). Methods: Quantification of bioactive molecules was performed by high-performance liquid chromatography (HPLC) method. Results: In the extract obtained from lyophilised GP, the most dominant component that was quantified was petunidin-3-glucoside. Prominent compounds that were quantified in DE extract were cyanidin derivatives. The total number of microorganisms in lyophilisates is low, but some of them still survive lyophilisation. Antibacterial activity was determined by microdilution, the minimum inhibitory concentration (MIC) of the tested bacteria ranged from 0.78 mg/mL to 25.00 mg/mL. Antibacterial susceptibility testing (AST) revealed that Klebsiella spp. and Acinetobacter baumannii complex are extensively drug-resistant (XDR). Conclusions: The GP + DE cocktail showed very strong AB power against both tested XDR bacteria. The total phenolic content and antioxidative effect (determined spectrophotometrically) indicate their linear correlation.
Point-Prevalence Survey of Antimicrobial Use and Healthcare-Associated Infections in Four Acute Care Hospitals in Kazakhstan
Authors: Semenova Yuliya , Yessmagambetova Aizhan , Akhmetova Zaure , Smagul Manar , Zharylkassynova Akniyet , Aubakirova Bibigul , Soiak Kateryna , Kosherova Zhanar , Aimurziyeva Ainur , Makalkina Larissa , Ikhambayeva Ainur , Lim Lisa
Published: October 2024

Background/Objectives: Few studies have examined the prevalence of healthcare-associated infections (HAIs) and antimicrobial use (AMU) in acute care hospitals in Kazakhstan. This study aimed to address this gap by conducting a point-prevalence survey (PPS) of HAIs and AMU, as well as evaluating hospital antibiotic consumption via internationally recognized methodologies. Methods: PPS was conducted in four acute care hospitals in Kazakhstan on 11 May 2022, following the methodology of the European Center for Disease Prevention and Control, and included 701 patients. Antibiotic consumption in the same hospitals was assessed via the Global Antimicrobial Resistance and Use Surveillance System methodology. Results: HAIs were observed in 3.8% of patients (27/701), with intensive care unit wards accounting for 48.1% of these cases (13/27). Pseudomonas aeruginosa was the most frequently identified pathogen (5 out of 14 documented cases, 35.7%). Resistance to carbapenems was the most common resistance, followed by resistance to glycopeptides and third-generation cephalosporins. The rate of AMU was 38.2%, with an average of 1.37 antibiotics administered per patient. Surgical prophylaxis lasting more than one day was the most common indication for antimicrobial prescription (44.8%). Ceftriaxone and cefazolin are the most commonly used antibiotics. Conclusions: The results of this study are important for understanding the current situation in Kazakhstan and for informing national antimicrobial stewardship and infection control strategies.
Aged Gut Microbiome Induces Metabolic Impairment and Hallmarks of Vascular and Intestinal Aging in Young Mice
Authors: Cheng Chak-Kwong , Ye Lianwei , Zuo Yuanyuan , Wang Yaling , Wang Li , Li Fuyong , Chen Sheng , Huang Yu
Published: October 2024

Aging, an independent risk factor for cardiometabolic diseases, refers to a progressive deterioration in physiological function, characterized by 12 established hallmarks. Vascular aging is driven by endothelial dysfunction, telomere dysfunction, oxidative stress, and vascular inflammation. This study investigated whether aged gut microbiome promotes vascular aging and metabolic impairment. Fecal microbiome transfer (FMT) was conducted from aged (>75 weeks old) to young C57BL/6 mice (8 weeks old) for 6 weeks. Wire myography was used to evaluate endothelial function in aortas and mesenteric arteries. ROS levels were measured by dihydroethidium (DHE) staining and lucigenin-enhanced chemiluminescence. Vascular and intestinal telomere function, in terms of relative telomere length, telomerase reverse transcriptase expression and telomerase activity, were measured. Systemic inflammation, endotoxemia and intestinal integrity of mice were assessed. Gut microbiome profiles were studied by 16S rRNA sequencing. Some middle-aged mice (40–42 weeks old) were subjected to chronic metformin treatment and exercise training for 4 weeks to evaluate their anti-aging benefits. Six-week FMT impaired glucose homeostasis and caused vascular dysfunction in aortas and mesenteric arteries in young mice. FMT triggered vascular inflammation and oxidative stress, along with declined telomerase activity and shorter telomere length in aortas. Additionally, FMT impaired intestinal integrity, and triggered AMPK inactivation and telomere dysfunction in intestines, potentially attributed to the altered gut microbial profiles. Metformin treatment and moderate exercise improved integrity, AMPK activation and telomere function in mouse intestines. Our data highlight aged microbiome as a mechanism that accelerates intestinal and vascular aging, suggesting the gut-vascular connection as a potential intervention target against cardiovascular aging and complications.
α-Terpineol Induces Shelterin Components TRF1 and TRF2 to Mitigate Senescence and Telomere Integrity Loss via A Telomerase-Independent Pathway
Authors: Kapetanou Marianna , Athanasopoulou Sophia , Goutas Andreas , Makatsori Dimitra , Trachana Varvara , Gonos Efstathios
Published: October 2024

Cellular senescence is a hallmark of aging characterized by irreversible growth arrest and functional decline. Progressive telomeric DNA shortening in dividing somatic cells, programmed during development, leads to critically short telomeres that trigger replicative senescence and thereby contribute to aging. Therefore, protecting telomeres from DNA damage is essential in order to avoid entry into senescence and organismal aging. In several organisms, including mammals, telomeres are protected by a protein complex named shelterin that prevents DNA damage at the chromosome ends through the specific function of its subunits. Here, we reveal that the nuclear protein levels of shelterin components TRF1 and TRF2 decline in fibroblasts reaching senescence. Notably, we identify α-terpineol as an activator that effectively enhances TRF1 and TRF2 levels in a telomerase-independent manner, counteracting the senescence-associated decline in these crucial proteins. Moreover, α-terpineol ameliorates the cells’ response to oxidative DNA damage, particularly at the telomeric regions, thus preserving telomere length and delaying senescence. More importantly, our findings reveal the significance of the PI3K/AKT pathway in the regulation of shelterin components responsible for preserving telomere integrity. In conclusion, this study deepens our understanding of the molecular pathways involved in senescence-associated telomere dysfunction and highlights the potential of shelterin components to serve as targets of therapeutic interventions, aimed at promoting healthy aging and combating age-related diseases.
Assessing Soil Physical Quality in a Layered Agricultural Soil: A Comprehensive Approach Using Infiltration Experiments and Time-Lapse Ground-Penetrating Radar Surveys
Authors: Di Prima Simone , Fernandes Gersende , Burguet Maria , Ribeiro Roder Ludmila , Giannini Vittoria , Giadrossich Filippo , Lassabatere Laurent , Comegna Alessandro
Published: October 2024

Time-lapse ground-penetrating radar (GPR) surveys, combined with automated infiltration experiments, provide a non-invasive approach for investigating the distribution of infiltrated water within the soil medium and creating three-dimensional images of the wetting bulb. This study developed and validated an experimental protocol aimed at quantifying and visualizing water distribution fluxes in layered soils under both unsaturated and saturated conditions. The 3D images of the wetting bulb significantly enhanced the interpretation of infiltration data, enabling a detailed analysis of water movement through the layered system. We used the infiltrometer data and the Beerkan Estimation of Soil Transfer parameters (BEST) method to determine soil capacitive indicators and evaluate the physical quality of the upper soil layer. The field survey involved conducting time-lapse GPR surveys alongside infiltration experiments between GPR repetitions. These experiments included both tension and ponding tests, designed to sequentially activate the soil matrix and the full pore network. The results showed that the soil under study exhibited significant soil aeration and macroporosity (represented by AC and pMAC), while indicators related to microporosity (such as PAWC and RFC) were notably low. The RFC value of 0.55 m3 m−3 indicated the soil’s limited capacity to retain water relative to its total pore volume. The PAWC value of 0.10 m3 m−3 indicated a scarcity of micropores ranging from 0.2 to 30 μm in diameter, which typically hold water accessible to plant roots within the total porosity. The saturated soil hydraulic conductivity, Ks, values ranged from 192.2 to 1031.0 mm h−1, with a mean of 424.4 mm h−1, which was 7.9 times higher than the corresponding unsaturated hydraulic conductivity measured at a pressure head of h = −30 mm (K−30). The results indicated that the upper soil layer supports root proliferation and effectively drains excess water to the underlying limestone layer. However, this layer has limited capacity to store and supply water to plant roots and acts as a restrictive barrier, promoting non-uniform downward water movement, as revealed by the 3D GPR images. The observed difference in hydraulic conductivity between the two layers suggests that surface ponding and overland flow are generated through a saturation excess mechanism. Water percolating through the soil can accumulate above the limestone layer, creating a shallow perched water table. During extreme rainfall events, this water table may rise, leading to the complete saturation of the soil profile.
GAN-Based Generation of Synthetic Data for Vehicle Driving Events
Authors: Tamayo-Urgilés Diego , Sanchez-Gordon Sandra , Valdivieso Caraguay Ángel Leonardo , Hernández-Álvarez Myriam
Published: October 2024

Developing solutions to reduce traffic accidents requires experimentation and much data. However, due to confidentiality issues, not all datasets used in previous research are publicly available, and those that are available may be insufficient for research. Building datasets with real data is costly. Given this reality, this paper proposes a procedure to generate synthetic data sequences of driving events using the Time series GAN (TimeGAN) and Real-world time series (RTSGAN) frameworks. First, a 15-feature driving event dataset is constructed with real data, which forms the basis for generating datasets using the two mentioned frameworks. The generated datasets are evaluated using the qualitative metrics PCA and T-SNE, as well as the discriminative and predictive score quantitative metrics defined in TimeGAN. The generated synthetic data are then used in an unsupervised algorithm to identify clusters representing vehicle crash risk levels. Next, the generated data are used in a supervised classification algorithm to predict risk level categories. Comparison results between the data generated by TimeGAN and RTSGAN show that the data generated by RTSGAN achieve better scores than the the data generated with TimeGAN. On the other hand, we demonstrate that the use of datasets trained with synthetic data to train a supervised classification model for predicting the level of accident risk can obtain accuracy comparable to that of models that use datasets with only real data in their training, proving the usefulness of the generated data.
A Tour Recommendation System Considering Implicit and Dynamic Information
Authors: Tsai Chieh-Yuan , Chuang Kai-Wen , Jen Hen-Yi , Huang Hao
Published: October 2024

Tourism has become one of the world’s largest service industries. Due to the rapid development of social media, more people like self-guided tours than package itineraries planned by travel agencies. Therefore, how to develop itinerary recommendation systems that can provide practical tour suggestions for tourists has become an important research topic. This study proposes a novel tour recommendation system that considers the implicit and dynamic information of Point-of-Interest (POI). Our approach is based on users’ photo information uploaded to social media in various tourist attractions. For each check-in record, we will find the POI closest to the user’s check-in Global Positioning System (GPS) location and consider the POI as the one they want to visit. Instead of using explicit information such as categories to represent POIs, this research uses the implicit feature extracted from the textual descriptions of POIs. Textual description for a POI contains rich and potential information describing the POI’s type, facilities, or activities, which makes it more suitable to represent a POI. In addition, this study considers visiting sequences when evaluating user similarity during clustering so that tourists in each sub-group hold higher behavior similarity. Next, the Non-negative Matrix Factorization (NMF) dynamically derives the staying time for different users, time slots, and POIs. Finally, a personalized itinerary algorithm is developed that considers user preference and dynamic staying time. The system will recommend the itinerary with the highest score and the longest remaining time. A set of experiments indicates that the proposed recommendation system outperforms state-of-the-art next POI recommendation methods regarding four commonly used evaluation metrics.
Theoretical Prediction and Safety Evaluation of Adjacent Pipeline Deformation Caused by Connecting Channel Excavation Reinforced with Freezing Method
Authors: Zhang Jun , Liu Jiguo , Fu Shuoren , Hong Zequn
Published: October 2024

Underground excavation by freezing method can ensure the safety of the surrounding structures. The influence of excavation of a connecting channel between two tunnels by freezing method on adjacent pipelines is studied in this paper. Combined with field measurement, numerical simulation, and theoretical analysis, the stress and deformation law of the whole process of channel excavation by freezing method is studied. Based on Euler–Bernoulli beam theory prediction, the influence of temperature field and excavation parameters on the longitudinal deformation of pipeline is analyzed. The results show that the excavation rate significantly affects the pipeline settlement, and the settlement surges when the excavation rate exceeds 1.0 m/d. At the same time, the thick frozen soil wall formed by low freezing temperatures enhances the supporting ability and effectively reduces the formation disturbance and settlement. The study focuses on the influence of connecting channel excavation on the pipelines under uniform formation conditions, and puts forward the evaluation method of pipeline safety to provide a theoretical reference for engineering practice.
Diagnostics of Rotating Machinery through Vibration Monitoring: Signal Processing and Pattern Analysis
Authors: Daga Alessandro Paolo , Garibaldi Luigi
Published: October 2024

Rotating machinery, ubiquitous in industrial applications, is vital for numerous processes, so ensuring their reliability, efficiency and safety is of primary importance [...]
Design and Analyses of Passive Continuous Distraction Osteogenesis Device for Oral and Maxillofacial Reconstruction
Authors: Hatefi Shahrokh , Alizargar Javad , Smith Farouk
Published: October 2024

Distraction Osteogenesis (DO) revolutionizes bone lengthening without donor sites, which is crucial in maxillofacial reconstruction (MRA). Manual DO devices are standard, but continuous DO devices promise faster treatments and better outcomes. Current continuous distractors lack ideal MRA due to size, force generation, and power source limitations. This study introduces a passive distractor system for continuous DO in MRA, aiming to bridge existing gaps and provide an ideal solution for human MRA use. It utilizes a miniaturized mechanism powered by a passive energy source, eliminating the need for active power. Advanced manufacturing methods enable the reduction of device size while hydraulic systems ensure controlled and smooth movement. The system includes a proximal bone fixture, movable distractor components, and passive drive means for distraction force application. Results show promising potential to address existing limitations. By utilizing passive energy for continuous force generation, the device size is reduced, and the need for force transition mechanisms is minimized. This innovative system and method offer an ideal treatment environment for MRA in humans. Further research and clinical evaluation are essential to validate its efficacy and safety in clinical practice.
Test and Numerical Study on Blast Resistance of Main Girders Coated with Polyurea in Self-Anchored Suspension Bridges
Authors: Wang Rong , Zhou Guangpan , Zuo Xiaobao
Published: October 2024

This study investigates the blast-resistant performance of a polyurea-coated suspension bridge girder under explosive loads. The Hunan Road Bridge of Shandong was used as a case study through combined test and numerical simulation methods. Two 3 kg TNT charges and one 5 kg TNT charge were used to conduct two single-blast tests and one repeated blast test on a 1:3 scaled segment of a box girder. The tests were labeled as G (box girder without polyurea), PCG (first blast on box girder coated with polyurea), and PCGR (second blast on box girder coated with polyurea). A 1.5 mm polyurea layer was uniformly applied to the top surface. Numerical simulations of the explosion response were performed and validated using LS-DYNA software. The results indicate that under 3 kg of TNT detonation directly above the top plate, sample G exhibited an elliptical perforation, whereas sample PCG only experienced minor local dents without penetration. After a second detonation of 5 kg of TNT above the box chambers, sample PCGR displayed a nearly circular perforation in the top plate, along with cracks near the supports of chambers 1 and 3. For the main girder of the suspension bridge, multiple detonation points caused severe damage, rendering it impassable. However, after polyurea coating, the blast resistance significantly improved, with only minor spalling of concrete on the top plate and no other notable damage, allowing for continued passage. The polyurea layer effectively reduced the vertical displacement of the girder, and this reduction plateaued with increasing coating thickness. Under a 500 kg TNT blast, the optimal polyurea thickness to enhance blast resistance was determined to be 9 mm.
An Ultra-Thin Composite Metasurface with Hybrid-Damping Modes for Broadband Sound Absorption
Authors: Liu Chongrui , Xie Zexiang , Liu Xiaoli
Published: October 2024

In this paper, we proposed an ultra-thin composite metasurface for broadband sound absorption, in which a compound Helmholtz structure and porous materials are coupled in a parallel-series arrangement. The Helmholtz structure comprises multiple compound cells with hybrid-damping modes, in which the over-damping and matched-damping impedance are integrated for a lower and broader absorption spectrum. By coupling the porous materials, the metasurface obtains above 85% average absorption over 750–10,000 Hz with a thickness of 31 mm, and the performance below 1600 Hz is significantly enhanced compared to the pure porous materials. This metasurface could possess broad applications in modern equipment considering its extraordinary absorption and compact structure.
Extracellular Haloalkalophilic Pectinase Produced by Virgibacillus salarius Strain 434—A Useful Tool for Biotechnological Applications
Authors: Boyadzhieva Ivanka , Berberov Kaloyan , Atanasova Nikolina , Krumov Nikolay , Kabaivanova Lyudmila
Published: October 2024

The interest in microbial pectinases is increasing due to their use in the biotechnological and food industries in response to global demand. In this study, among the 22 halophilic bacterial strains screened, 20 showed pectinase activity. The highest activity was measured for Virgibacillus salarius strain 434. As pectinase production meets many parameter optimization constraints, optimal production conditions for maximizing the yield of the pectinase synthesized using the investigated strain were followed. Enzyme purification was accomplished at up to 11.5-fold via ultrafiltration and gel filtration chromatography, until the enzyme’s specific activity had increased 10-fold (104.3 U/mg). The enzyme’s molecular weight was determined to be 68 kDa. Km and Vmax values of 0.38 mg/mL and 120 U/mg, respectively, were determined. The purified pectinase from Virgibacillus salarius strain 434 showed good thermal stability. A half-life of 20 min at 70 °C and high catalytic activity under haloalkaline conditions (pH 9 and 70 g L−1 NaCl) were observed. Its storage stability at −20 °C exceeded 2 months. This demonstrates its potential for application in industries where these extremes are present, as the harsh conditions in industrial processes require novel pectinases with unique properties instead of the use of hazardous chemicals.
Advances in Finite Element Modeling of Fatigue Crack Propagation
Authors: Alshoaibi Abdulnaser M. , Fageehi Yahya Ali
Published: October 2024

Fatigue crack propagation is a critical phenomenon that affects the structural integrity and lifetime of various engineering components. Over the years, finite element modeling (FEM) has emerged as a powerful tool for studying fatigue crack propagation and predicting crack growth behavior. This study offers a thorough overview of recent advancements in finite element modeling (FEM) of fatigue crack propagation. It highlights cutting-edge techniques, methodologies, and developments, focusing on their strengths and limitations. Key topics include crack initiation and propagation modeling, the fundamentals of finite element modeling, and advanced techniques specifically for fatigue crack propagation. This study discusses the latest developments in FEM, including the Extended Finite Element Method, Cohesive Zone Modeling, Virtual Crack Closure Technique, Adaptive Mesh Refinement, Dual Boundary Element Method, Phase Field Modeling, Multi-Scale Modeling, Probabilistic Approaches, and Moving Mesh Techniques. Challenges in FEM are also addressed, such as computational complexity, material characterization, meshing issues, and model validation. Additionally, the article underscores the successful application of FEM in various industries, including aerospace, automotive, civil engineering, and biomechanics.
High-Sensitivity Displacement Sensor Using Few-Mode Optical Fibers and the Optical Vernier Effect
Authors: Guillen-Ruiz Luis E. , Anzueto-Sánchez Gilberto , Martínez-Rios Alejandro , Jiménez-Mares Myriam C. , Martin-Vela Javier A.
Published: October 2024

This paper presents a displacement sensor designed to achieve the Optical Vernier Effect (OVE) through a simple yet robust configuration, enhancing sensitivity and precision in small displacement measurements. The sensor structure comprises a few-mode fiber (FMF) placed between two single-mode fibers (SMF) in an SMF-FMF-SMF (SFS) configuration. A series of distinct configurations of concatenated Mach–Zehnder fiber interferometers (MZFI) were examined, with the lengths of the reference FMF (FMFRef) and sensing FMF (FMFSen) adjusted to track the spectral envelope shifts. The results demonstrate that the direction of the spectral shift is governed by the ratio between the FMFRef and FMFSen lengths. The sensor achieved a sensitivity of up to 39.07 nm/mm and a magnification factor (M factor) of up to 50.09, demonstrating exceptional precision and adaptability across a range of applications. The proposed configuration also enhances the overall sensor performance, highlighting its potential for broader use in fields requiring precise displacement monitoring.
In Silico Investigation of Taurodispacamide A and Strepoxazine A from Agelas oroides S. as Potential Inhibitors of Neuroblastoma Targets Reveals Promising Anticancer Activity
Authors: Linani Abderahmane , Bensenouci Sabrina , Hafsa Ben lahbib , Benarous Khedidja , Serseg Talia , Bou-Salah Leila , Alhatlani Bader Y.
Published: October 2024

This study investigated the potential of five pyrrole-imidazole alkaloids from the marine sponge Agelas sp. to inhibit key targets in neuroblastoma, the most common pediatric malignant solid tumor. Molecular docking analysis using GOLD software (v4.1.2) revealed that Strepoxazine A (Mol3) and Taurodispacamide A (Mol5) exhibited the strongest inhibition of focal adhesion kinase 1 (FAK), caspase-3 (ca3), phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit gamma isoform (PI3K), telomerase reverse transcriptase (TERT), osm-9-like TRP channel 1 (TRPV1), and RAC-alpha serine/threonine-protein kinase (AKT1). Normal mode analysis using iMODS server confirmed the stability of the best complexes and pharmacokinetics, such as toxicity and predictions of biological activity as inhibitors of anticancer targets, indicating a balance between efficacy and safety for bothMol3 and Mol5. The remaining compounds (Ageladine A, Oroidine, and Cyclooroidine) showed moderate effects, with significant toxicity, suggesting limited therapeutic potential. The promising results of our in silico-study suggest that Strepoxazine A and Taurodispacamide A could serve as novel therapeutic agents for neuroblastoma, potentially leading to more effective treatment options and improved survival rates for pediatric patients suffering from this challenging malignancy, although further in vitro and in vivo validation is needed.
Intra- and Interpatient ECG Heartbeat Classification Based on Multimodal Convolutional Neural Networks with an Adaptive Attention Mechanism
Authors: Di Paolo Ítalo Flexa , Castro Adriana Rosa Garcez
Published: October 2024

Echocardiography (ECG) is a noninvasive technology that is widely used for recording heartbeats and diagnosing cardiac arrhythmias. However, interpreting ECG signals is challenging and may require substantial time from medical specialists. The evolution of technology and artificial intelligence has led to advances in the study and development of automatic arrhythmia classification systems to aid in medical diagnoses. Within this context, this paper introduces a framework for classifying cardiac arrhythmias on the basis of a multimodal convolutional neural network (CNN) with an adaptive attention mechanism. ECG signal segments are transformed into images via the Hilbert space-filling curve (HSFC) and recurrence plot (RP) techniques. The framework is developed and evaluated using the MIT-BIH public database in alignment with AAMI guidelines (ANSI/AAMI EC57). The evaluations accounted for interpatient and intrapatient paradigms, considering variations in the input structure related to the number of ECG leads (lead MLII and V1 + MLII). The results indicate that the framework is competitive with those in state-of-the-art studies, particularly for two ECG leads. The accuracy, precision, sensitivity, specificity and F1 score are 98.48%, 94.15%, 80.23%, 96.34% and 81.91%, respectively, for the interpatient paradigm and 99.70%, 98.01%, 97.26%, 99.28% and 97.64%, respectively, for the intrapatient paradigm.
Accurate Power Consumption Predictor and One-Class Electricity Theft Detector for Smart Grid “Change-and-Transmit” Advanced Metering Infrastructure
Authors: Bondok Atef , Abdelsalam Omar , Badr Mahmoud , Mahmoud Mohamed , Alsabaan Maazen , Alsaqhan Muteb , Ibrahem Mohamed I.
Published: October 2024

The advanced metering infrastructure (AMI) of the smart grid plays a critical role in energy management and billing by enabling the periodic transmission of consumers’ power consumption readings. To optimize data collection efficiency, AMI employs a “change and transmit” (CAT) approach. This approach ensures that readings are only transmitted when there is enough change in consumption, thereby reducing data traffic. Despite the benefits of this approach, it faces security challenges where malicious consumers can manipulate their readings to launch cyberattacks for electricity theft, allowing them to illegally reduce their bills. While this challenge has been addressed for supervised learning CAT settings, it remains insufficiently addressed in unsupervised learning settings. Moreover, due to the distortion introduced in the power consumption readings due to using the CAT approach, the accurate prediction of future consumption for energy management is a challenge. In this paper, we propose a two-stage approach to predict future readings and detect electricity theft in the smart grid while optimizing data collection using the CAT approach. For the first stage, we developed a predictor that is trained exclusively on benign CAT power consumption readings, and the output of the predictor is the actual readings. To enhance the prediction accuracy, we propose a cluster-based predictor that groups consumers into clusters with similar consumption patterns, and a dedicated predictor is trained for each cluster. For the second stage, we trained an autoencoder and a one-class support vector machine (SVM) on the benign reconstruction errors of the predictor to classify instances of electricity theft. We conducted comprehensive experiments to assess the effectiveness of our proposed approach. The experimental results indicate that the prediction error is very small and the accuracy of detection of the electricity theft attacks is high.
New Outcomes Observed from Replacing Cement with BJPA under Different Curing Temperatures and the True Effects of Each Experimental Factor on Compressive Strength
Authors: Kuo Wen-Ten , Zhuang Zheng-Yun
Published: October 2024

In the lab experiments, the compressive strength (CS) of cement mortar, three pre-setting water/binder (W/B) ratios, five substitution rates of burned joss paper ash (SR-BJPA), and three curing temperatures (T) were tested for the 45 samples. The results were recorded at 3, 7, 28, 56, 90, and 120 days after curing (#days) for each sample. The correlations between CS and each experimental factor (W/B ratio, SR-BJPA, T, and #days) and the effects of each factor or pair of factors on CS were determined using four univariate and six bivariate regression models. All the models were significant (i.e., the factors and the pairs of factors can be used to predict CS); however, each model had a different ability to fit the data and explain the data variance, making some models not that suitable. The effects on CS of substituting cement with different BJPA proportions and curing the mortar at different temperatures were mainly identified. A knowledge base for predicting the CS was established before any sample is to be made in future practise. Finally, using an SR-BJPA of 5% and raising the curing temperature to 50 °C (or 75 °C, if additional heating energy consumption needs not be considered) while keeping the W/B ratio at 0.4 is recommended to obtain an optimal CS for the full-aged sample (i.e., at #days = 120) in future practise, subject to the aim to consume the BJPA wastes by using it to replace Portland cement, in order to reduce the vast volume of carbon emitted along with the production of the cement material.
Comparative Study of Computational Methods for Classifying Red Blood Cell Elasticity
Authors: Bachratý Hynek , Novotný Peter , Smiešková Monika , Bachratá Katarína , Molčan Samuel
Published: October 2024

The elasticity of red blood cells (RBCs) is crucial for their ability to fulfill their role in the blood. Decreased RBC deformability is associated with various pathological conditions. This study explores the application of machine learning to predict the elasticity of RBCs using both image data and detailed physical measurements derived from simulations. We simulated RBC behavior in a microfluidic channel. The simulation results provided the basis for generating data on which we applied machine learning techniques. We analyzed the surface-area-to-volume ratio of RBCs as an indicator of elasticity, employing statistical methods to differentiate between healthy and diseased RBCs. The Kolmogorov–Smirnov test confirmed significant differences between healthy and diseased RBCs, though distinctions among different types of diseased RBCs were less clear. We used decision tree models, including random forests and gradient boosting, to classify RBC elasticity based on predictors derived from simulation data. The comparison of the results with our previous work on deep neural networks shows improved classification accuracy in some scenarios. The study highlights the potential of machine learning to automate and enhance the analysis of RBC elasticity, with implications for clinical diagnostics.
The Impact of Sport-Specific Practice on Health-Related Physical Fitness Components in Young Water Polo and Volleyball Athletes
Authors: Sgrò Francesco , Barca Michele , Mollame Federico , Orofino Francesca , Quinto Antonella , Stodden David
Published: October 2024

Physical fitness (PF) has been identified as a critical health marker in youth and is significantly influenced by environmental factors, such as the specificity of training involved in different sports. This study investigated PF differences among young athletes who participated in water polo and volleyball to understand how different training programs and environments impact physical development. A sample of 98 youth athletes, including 46 water polo players (46% female; mean age: 13.07 ± 2.27 years) and 52 volleyball players (100% female; mean age: 13.80 ± 1.86 years) was assessed using Handgrip (HG), Standing Long Jump (SLJ), and Progressive Aerobic Cardiovascular Endurance Run (PACER) tests. Results were normalized against European percentile reference values and analyzed using the Mann–Whitney U test. The PACER test revealed a significant difference (U = 639, p < 0.001, r = −0.466), with water polo athletes exhibiting superior cardiorespiratory fitness compared to volleyball players. The HG test also showed significant differences (U = 1571, p = 0.007, r = 0.314), indicating greater grip strength in volleyball players. No significant difference was observed in the SLJ test. These findings underscore the importance of sport-specific training in youth athletes, but also the importance of well-rounded physical development training for all youth sports. Results suggest that practicing different sports that involve different training and environments is significantly associated with certain aspects of PF components. This awareness can guide grassroots coaches and trainers towards effective and balanced training strategies to promote performance and long-term health.
A Comprehensive Hybrid Deep Learning Approach for Accurate Status Predicting of Hydropower Units
Authors: Ma Liyong , Chen Siqi , Wei Dali , Zhang Yanshuo , Guo Yinuo
Published: October 2024

Hydropower units are integral to sustainable energy production, and their operational reliability hinges on accurate status prediction. This paper introduces an innovative hybrid deep learning model that synergistically integrates a Temporal Convolutional Network (TCN), a Residual Short-Term LSTM (REST-LSTM) network, a Gated Recurrent Unit (GRU) network, and the tuna swarm optimization (TSO) algorithm. The model was meticulously designed to capture and utilize temporal features inherent in time series data, thereby enhancing predictive performance. Specifically, the TCN effectively extracts critical temporal features, while the REST-LSTM, with its residual connections, improves the retention of short-term memory in sequence data. The parallel incorporation of GRU further refines temporal dynamics, ensuring comprehensive feature capture. The TSO algorithm was employed to optimize the model’s parameters, leading to superior performance. The model’s efficacy was empirically validated using three datasets—unit flow rate, guide vane opening, and maximum guide vane water temperature—sourced from the Huadian Electric Power Research Institute. The experimental results demonstrate that the proposed model significantly reduces both the maximum and average prediction errors, while also offering substantial improvements in forecasting accuracy compared with the existing methodologies. This research presents a robust framework for hydropower unit operation prediction, advancing the application of deep learning in the hydropower sector.
Distillers’ Grains Peptides Scavenge Free Radicals and Influence Volatile Compounds of Chi-Aroma Baijiu
Authors: Zhang Renjie , Hu Xi , Luo You , Zheng Siqin , Wu Zhenqiang
Published: October 2024

The production of Chi-aroma Baijiu generates free radicals, which may pose potential health risks. This study aimed to scavenge free radicals in Chi-aroma Baijiu and assess the impact on the composition of volatile compounds (VOCs) by using distillers’ grains-derived homologous peptides. Five peptides—Pro-Ala (PA), Pro-Val (PV), Gly-Leu (GL), Asp-Phe (DF), and Pro-Leu (PL)—were isolated from the distillers’ grain filtrate. These peptides are present in trace amounts in Chi-aroma Baijiu. By supplementing five peptides to Chi-aroma Baijiu, they could completely scavenge hydroxyl radicals. The rate of scavenging alkoxy radicals ranged from 10.84% to 35.66%. Furthermore, these peptides had an impact on ethyl nonanoate, diethyl acetal, and octanal, which were recognized as characteristic compounds. Ultraviolet spectroscopy simulation revealed that the highest absorption peaks of certain peptides shift when they interact with various esters. Those peptides interact with ethyl acetate and ethyl lactate via hydrogen bonding and Van der Waals forces, demonstrating their influence on VOCs. These findings offer new insights into free radical scavenging, flavor compound regulation, and the valorization of Baijiu by-products in Chi-aroma Baijiu production.
A Large Bridge Traffic Operation Status Impact Assessment Model Based on AHP–Delphi–SVD Method
Authors: Guo Jianxing , Zhang Yunrui , Yuan Guanhu , Li Yanbo , Wang Longfei , Dong Zhi
Published: October 2024

As an important component of road traffic facilities, bridges play a crucial role in daily traffic operations, and changes in their status can have an impact on traffic operation. The existing research mainly focuses on monitoring the status of bridges themselves or analyzing the operation status of road traffic, and rarely considers the changes in traffic operation status caused by changes in bridge status. Therefore, in order to evaluate the impact relationship between the two, this article designs an algorithm that combines the Analytic Hierarchy Process (AHP), the Delphi method, and Singular Value Decomposition (SVD) based on the traditional evaluation of bridges and road traffic operation status, and establishes a bridge traffic operation status impact assessment model. Then, simulation analysis and actual data verification will be conducted based on the specific situation of Ma’anshi Bridge on the Chongqing Wuhan Expressway. The experimental results show that the evaluation model established in this paper conforms to the characteristics of traffic operation, can reflect the impact of bridge state changes on traffic operation status well, effectively promote the automation level of bridge traffic impact management, and has high reliability and accuracy.
True Triaxial Crack Stress Thresholds and Deformation Characteristics of Cement Stone Subjected to Sulfuric Acid Corrosion
Authors: Chen Zhi , Xia Yi
Published: October 2024

This article presents the results of deformation characteristics and crack stress thresholds of cement stone under different acid treatment times. A series of true triaxial tests were conducted on cement stones under four sulfuric acid treatment times (0, 7, 14, and 28 days). The microstructures of cement stone under different acid treatment times were examined. In the range of 0 to 14 days, the damaging effect of sulfuric acid dominated, and the structural integrity was damaged by sulfuric acid. In the range of 14 to 28 days, the strengthening effect of calcium sulfate precipitate dominated, and the structural integrity was enhanced by calcium sulfate precipitate. The cement stone exhibited anisotropic deformation characteristics under true triaxial stress states. With an increase in acid treatment time, the deformation modulus of cement stone first decreased and then slightly increased. The crack stress thresholds first increased and then decreased with an increasing intermediate principal stress coefficient. With an increase in acid treatment time, the crack stress thresholds first decreased and then slightly increased. Substantially, the ratio of crack stress thresholds was analyzed. The proportion of the unstable crack growth stage and crack growth stage increased with minimum principal stress. Additionally, the proportion of the unstable crack growth stage and thecrack growth stage first increased and then decreased with increasing acid treatment time. However, the proportion of the stable crack growth stage had the opposite variation law to that of the unstable crack growth stage and crack growth stage.