bluuebunny/crossref_metadata_2025 huggingface dataset:
Sea surface barometry with an O2 differential absorption radar: retrieval algorithm development and simulation
Authors: Lin Bing , Mclinden Matthew Walker , Cai Xia , Heymsfield Gerald M. , Privé Nikki , Harrah Steven , Li Lihua
Published: July 2024

Sea surface air pressure observations are a significant gap in the current Earth observing systems. This study addresses retrieval algorithm development and the evaluation of the potential impact of instrumental and environmental uncertainties on sea level pressure retrievals for the measurements of O2 differential absorption radar systems operating at three spectrally evenly spaced close-frequency bands (65.5, 67.75, and 70.0 GHz). A simulated northern hemispheric summer case is used to simulate retrieval uncertainties. To avoid high attenuation and a low signal-to-noise ratio, radar measurements from weather conditions with a rain rate ≥1 mm/h are not used in the retrieval. This study finds that a retrieval algorithm combining all three channels, i.e., the 3-channel approach, can effectively mitigate major atmospheric and sea surface influences on sea surface air pressure retrieval. The major uncertainty of sea surface pressure retrieval is due to the standard deviation in radar power returns. Analysis and simulation demonstrate the potential of global sea surface pressure observations with errors of about 1∼2 mb, which is urgently needed for the improvement of numerical weather prediction models. Future work will emphasize instrument development and field experiments. It is anticipated that an O2 differential absorption radar system will be available for meteorological applications in a few years.
Transporter annotations are holding up progress in metabolic modeling
Authors: Casey John , Bennion Brian , D’haeseleer Patrik , Kimbrel Jeffrey , Marschmann Gianna , Navid Ali
Published: July 2024

Mechanistic, constraint-based models of microbial isolates or communities are a staple in the metabolic analysis toolbox, but predictions about microbe-microbe and microbe-environment interactions are only as good as the accuracy of transporter annotations. A number of hurdles stand in the way of comprehensive functional assignments for membrane transporters. These include general or non-specific substrate assignments, ambiguity in the localization, directionality and reversibility of a transporter, and the many-to-many mapping of substrates, transporters and genes. In this perspective, we summarize progress in both experimental and computational approaches used to determine the function of transporters and consider paths forward that integrate both. Investment in accurate, high-throughput functional characterization is needed to train the next-generation of predictive tools toward genome-scale metabolic network reconstructions that better predict phenotypes and interactions. More reliable predictions in this domain will benefit fields ranging from personalized medicine to metabolic engineering to microbial ecology.
First isolation, identification, and pathogenicity evaluation of an EV-G6 strain in China
Authors: Zhu Pei , Li Zhan-Hong , Li Zhuo-Ran , Zhang Zhen-Xing , Song Jian-Ling
Published: July 2024

Enterovirus G (EV-G) belongs to the Picornaviridae family and infects porcine populations worldwide. A total of 20 EV-G genotypes (EV-G1 to EV-G20) have been identified. In this study, we isolated and characterized an EV-G strain, named EV-G/YN29/2022, from the feces of diarrheic pigs. This was the first EV-G6 strain isolated in China. Comparison of the whole genome nucleotide and corresponding amino acid sequences showed that the isolate was more closely related to those of the EV-G6 genotype than other genotypes, with the complete genome sequence similarity ranging from 83.7% (Iba46442) to 84.4% (PEV-B-KOR), and corresponding amino acid homology ranged from 96% (Iba46442) to 96.8% (PEV-B-KOR). Similarly, the VP1 gene and corresponding amino acid sequences of EV-G/YN29/2022 were highly similar to those of the EV-G6 genotype (>82.9% and >94.3%, respectively). Thus, the isolated strain was classified as EV-G6 genotype. This was the first EV-G6 strain isolated in China. Pathogenicity analyses revealed that EV-G/YN29/2022 infection caused mild diarrhea, typical skin lesions, and weight reduction. The strain was mainly distributed to the intestinal tissue but was also found in the brain, mesenteric lymph nodes, spleen, and liver. Our results can be used as a reference to further elucidate the epidemiology, evolution, and pathogenicity of EV-G.
Domains and Methods of Medical Device Technology Evaluation: A Systematic Review
Authors: Toscas Fotini Santos , Blas Daiana Laurenci Orth , Teixeira Leidy Anne Alves , Santos Marisa da Silva , Dias Eduardo Mario
Published: July 2024

Objectives

Identify, through a systematic review, the main domains and methods to support health technology assessment of Medical Devices (MD) from the perspective of technological incorporation into healthcare systems.

Methods

Performed structured searches in MEDLINE, Embase, BVS, Cochrane Library, and Web of Science for full studies published between 2017 and May 2023. Selection, extraction, and quality assessment were performed by two blinded reviewers, and discrepancies were resolved by a third reviewer.

Results

A total of 5,790 studies were retrieved, of which 41 were included. We grouped the identified criteria into eight domains for the evaluations.

Conclusion

Overall, studies discuss the need to establish specific methods for conducting HTA in MD. Due to the wide diversity of MD types, a single methodological guideline may not encompass all the specificities and intrinsic characteristics of the plurality of MD. Studies suggest using clustering criteria through technological characterization as a strategy to make the process as standardized as possible.
Comparison of Reinforcement Learning Algorithms for Edge Computing Applications Deployed by Serverless Technologies
Authors: Femminella Mauro , Reali Gianluca
Published: July 2024

Edge computing is one of the technological areas currently considered among the most promising for the implementation of many types of applications. In particular, IoT-type applications can benefit from reduced latency and better data protection. However, the price typically to be paid in order to benefit from the offered opportunities includes the need to use a reduced amount of resources compared to the traditional cloud environment. Indeed, it may happen that only one computing node can be used. In these situations, it is essential to introduce computing and memory resource management techniques that allow resources to be optimized while still guaranteeing acceptable performance, in terms of latency and probability of rejection. For this reason, the use of serverless technologies, managed by reinforcement learning algorithms, is an active area of research. In this paper, we explore and compare the performance of some machine learning algorithms for managing horizontal function autoscaling in a serverless edge computing system. In particular, we make use of open serverless technologies, deployed in a Kubernetes cluster, to experimentally fine-tune the performance of the algorithms. The results obtained allow both the understanding of some basic mechanisms typical of edge computing systems and related technologies that determine system performance and the guiding of configuration choices for systems in operation.
Energy Consumption Outlier Detection with AI Models in Modern Cities: A Case Study from North-Eastern Mexico
Authors: Solís-Villarreal José-Alberto , Soto-Mendoza Valeria , Navarro-Acosta Jesús Alejandro , Ruiz-y-Ruiz Efraín
Published: July 2024

The development of smart cities will require the construction of smart buildings. Smart buildings will demand the incorporation of elements for efficient monitoring and control of electrical consumption. The development of efficient AI algorithms is needed to generate more accurate electricity consumption predictions; therefore; anomaly detection in electricity consumption predictions has become an important research topic. This work focuses on the study of the detection of anomalies in domestic electrical consumption in Mexico. A predictive machine learning model of future electricity consumption was generated to evaluate various anomaly-detection techniques. Their effectiveness in identifying outliers was determined, and their performance was documented. A 30-day forecast of electrical consumption and an anomaly-detection model have been developed using isolation forest. Isolation forest successfully captured up to 75% of the anomalies. Finally, the Shapley values have been used to generate an explanation of the results of a model capable of detecting anomalous data for the Mexican context.
Flow-Based Assessment of the Impact of an All-Electric Aircraft on European Air Traffic
Authors: Yildiz Bekir , Förster Peter , Feuerle Thomas , Hecker Peter
Published: July 2024

The consequences of new airspace entrants, such as novel aircraft concepts with innovative propulsion systems, on air traffic management operations need to be carefully identified. This paper aims to assess the impact of future aircraft with different performance envelopes on the European air traffic network from a flow-based perspective. The underlying approach assumes that all certification-related questions concerning airworthiness have been resolved and do not take into account any economic factors related to airline operations. For example, for an innovative propulsion system, a short range all-electric aircraft is considered in this study. Aircraft trajectory calculations are based on the dataset of base of aircraft data (BADA), which are developed and maintained by EUROCONTROL. The new design concept is integrated into BADA as well, resulting in a new set of coefficients for the all-electric aircraft. In addition to the adjusted parameters which affect airborne performances, ground-related aspects are also taken into account. This includes assumptions on operational procedures, charging capacities and adaptions in infrastructure. Investigations are carried out at the trajectory level as well as at the airport and the entire network.
SE-CBAM-YOLOv7: An Improved Lightweight Attention Mechanism-Based YOLOv7 for Real-Time Detection of Small Aircraft Targets in Microsatellite Remote Sensing Imaging
Authors: Kang Zhenping , Liao Yurong , Du Shuhan , Li Haonan , Li Zhaoming
Published: July 2024

Addressing real-time aircraft target detection in microsatellite-based visible light remote sensing video imaging requires considering the limitations of imaging payload resolution, complex ground backgrounds, and the relative positional changes between the platform and aircraft. These factors lead to multi-scale variations in aircraft targets, making high-precision real-time detection of small targets in complex backgrounds a significant challenge for detection algorithms. Hence, this paper introduces a real-time aircraft target detection algorithm for remote sensing imaging using an improved lightweight attention mechanism that relies on the You Only Look Once version 7 (YOLOv7) framework (SE-CBAM-YOLOv7). The proposed algorithm replaces the standard convolution (Conv) with a lightweight convolutional squeeze-and-excitation convolution (SEConv) to reduce the computational parameters and accelerate the detection process of small aircraft targets, thus enhancing real-time onboard processing capabilities. In addition, the SEConv-based spatial pyramid pooling and connected spatial pyramid convolution (SPPCSPC) module extracts image features. It improves detection accuracy while the feature fusion section integrates the convolutional block attention module (CBAM) hybrid attention network, forming the convolutional block attention module Concat (CBAMCAT) module. Furthermore, it optimizes small aircraft target features in channel and spatial dimensions, improving the model’s feature fusion capabilities. Experiments on public remote sensing datasets reveal that the proposed SE-CBAM-YOLOv7 improves detection accuracy by 0.5% and the mAP value by 1.7% compared to YOLOv7, significantly enhancing the detection capability for small-sized aircraft targets in satellite remote sensing imaging.
RmMYB44 Confers Resistance to Chilling, Drought, and Salt Stress in Both Rosa multiflora and Tobacco
Authors: Zhang Wuhua , Zhang Naiyu , Qin Qi , Zhang Xiaoying , Zhang Jinzhu , Yang Tao , Zhang Yifei , Dong Jie , Che Daidi
Published: July 2024

Roses, a popular ornamental crop, often face various abiotic stresses during growth and development, such as cold, drought, and salinity. Rosa multiflora is a commonly used rootstock and exhibits strong resistance to both biotic and abiotic stresses, making it an ideal material for studying mechanisms for resistance. Among the largest plant families, MYB transcription factors play a crucial role in plant abiotic stresses. Our previous research has indicated that RmMYB44 could be involved in the low-temperature response of R. multiflora. This study further investigated RmMYB44, revealing that its expression levels were upregulated in response to chilling, drought, and salt stress. The results suggested its potential role as a key transcription factor in plant resistance to abiotic stresses. Additionally, RmMYB44 encoded a nuclear-localized protein without the self-activating function. The overexpression of RmMYB44 in tobacco plants enhanced the resistance to cold, drought, and salt stresses, as evidenced by the improved growth compared to wild-type (WT) plants under conditions of 4 °C, 30% water-holding capacity, and 200 mM of NaCl, respectively. Moreover, in overexpression tobacco plants, the levels of hydrogen peroxide and malondialdehyde (MDA) were significantly reduced; and the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT); as well as the proline content and the expression levels of NtPOD, NtCAT, and NtCBF; were significantly elevated under abiotic stresses. We assumed that the resistance to abiotic stress in plants conferred by RmMYB44 was associated with the regulation of cell membrane integrity. This study aimed to elucidate the role of the RmMYB44 gene in the resistance mechanism of R. multiflora against abiotic stress, thereby providing a candidate gene for the molecular breeding of abiotic stress resistance in roses and related species.
Therapeutic Application of Extracellular Vesicles Derived from Mesenchymal Stem Cells in Domestic Animals
Authors: Lanci Aliai , Iacono Eleonora , Merlo Barbara
Published: July 2024

Recently, the therapeutic potential of extracellular vesicles (EVs) derived from mesenchymal stem cells (MSCs) has been extensively studied in both human and veterinary medicine. EVs are nano-sized particles containing biological components commonly found in other biological materials. For that reason, EV isolation and characterization are critical to draw precise conclusions during their investigation. Research on EVs within veterinary medicine is still considered in its early phases, yet numerous papers were published in recent years. The conventional adult tissues for deriving MSCs include adipose tissue and bone marrow. Nonetheless, alternative sources such as synovial fluid, endometrium, gingiva, and milk have also been intermittently used. Fetal adnexa are amniotic membrane/fluid, umbilical cord and Wharton’s jelly. Cells derived from fetal adnexa exhibit an intermediate state between embryonic and adult cells, demonstrating higher proliferative and differentiative potential and longer telomeres compared to cells from adult tissues. Summarized here are the principal and recent preclinical and clinical studies performed in domestic animals such as horse, cattle, dog and cat. To minimize the use of antibiotics and address the serious issue of antibiotic resistance as a public health concern, they will undoubtedly also be utilized in the future to treat infections in domestic animals. A number of concerns, including large-scale production with standardization of EV separation and characterization techniques, must be resolved for clinical application.
The Interaction between Canine Semen Bacteria and Semen Quality Parameters
Authors: Sorkytė Šarūnė , Šiugždinienė Rita , Virgailis Marius , Vaičiulienė Gintarė , Wysokińska Anna , Wójcik Ewa , Matusevičius Paulius , Rekešiūtė Audronė , Sutkevičienė Neringa
Published: July 2024

Assessing canine semen quality helps to detect infertility in males, but identifying factors that influence canine semen quality is a complicated task. The objective of this study was the assessment of the potential influence of bacteria found in canine semen samples on the characteristics of dogs’ semen. In this study, semen samples were collected manually from 30 dogs and subjected to a comprehensive examination. The results of sperm motility, concentration, viability, and morphology were statistically analysed in relation to the number of bacteria in the semen (CFUs/mL) and the seminal microbiota. Samples with an increased bacterial count per millilitre were associated with lower-quality sperm motility (p < 0.05). The most frequently isolated bacterial genera from the analysed semen samples were Staphylococcus spp. (26.0%), Corynebacterium spp. (17.8%), and Streptococcus spp. (16.4%). The presence of β-haemolytic Escherichia coli bacteria was linked to suboptimal semen samples, characterised by significantly reduced semen viability and a lower proportion of morphologically normal spermatozoa (p < 0.05). Corynebacterium spp. was associated with reduced bacterial load and superior semen quality (p < 0.01). These findings highlight the importance of bacterial cell counts and microbiota diversity in relation to various factors influencing canine semen quality, providing a more comprehensive understanding of canine reproductive well-being.
Allogeneic HLA Humoral Immunogenicity and the Prediction of Donor-Specific HLA Antibody Development
Authors: Jucaud Vadim
Published: July 2024

The development of de novo donor-specific HLA antibodies (dnDSAs) following solid organ transplantation is considered a major risk factor for poor long-term allograft outcomes. The prediction of dnDSA development is a boon to transplant recipients, yet the assessment of allo-HLA immunogenicity remains imprecise. Despite the recent technological advances, a comprehensive evaluation of allo-HLA immunogenicity, which includes both B and T cell allorecognition, is still warranted. Recent studies have proposed using mismatched HLA epitopes (antibody and T cell) as a prognostic biomarker for humoral alloimmunity. However, the identification of immunogenic HLA mismatches has not progressed despite significant improvements in the identification of permissible mismatches. Certainly, the prediction of dnDSA development may benefit permissible HLA mismatched organ transplantations, personalized immunosuppression, and clinical trial design. However, characteristics that go beyond the listing of mismatched HLA antibody epitopes and T cell epitopes, such as the generation of HLA T cell epitope repertoires, recipient’s HLA class II phenotype, and immunosuppressive regiments, are required for the precise assessment of allo-HLA immunogenicity.
Activity of Synthetic Peptide KP and Its Derivatives against Biofilm-Producing Escherichia coli Strains Resistant to Cephalosporins
Authors: Artesani Lorenza , Ciociola Tecla , Vismarra Alice , Bacci Cristina , Conti Stefania , Giovati Laura
Published: July 2024

Bacterial resistance to β-lactam antibiotics, particularly new generation cephalosporins, is a major public health concern. In Escherichia coli, resistance to these antibiotics is mainly mediated by extended-spectrum β-lactamases (ESBL), which complicates a range of health-threatening infections. These infections may also be biofilm-related, making them more difficult to treat because of the higher tolerance to conventional antibiotics and the host immune response. In this study, we tested as potential new drug candidates against biofilm-forming ESBL-producing E. coli four antimicrobial peptides previously shown to have antifungal properties. The peptides proved to be active in vitro at micromolar concentrations against both sensitive and ESBL-producing E. coli strains, effectively killing planktonic cells and inhibiting biofilm formation. Quantitative fluorescence intensity analysis of three-dimensional reconstructed confocal laser scanning microscopy (CLSM) images of mature biofilm treated with the most active peptide showed significant eradication and a reduction in viable bacteria, while scanning electron microscopy (SEM) revealed gross morphological alterations in treated bacteria. The screening of the investigated peptides for antibacterial and antibiofilm activity led to the selection of a leading candidate to be further studied for developing new antimicrobial drugs as an alternative treatment against microbial infections, primarily associated with biofilms.
General Characteristics and Current State of Antibiotic Resistance in Pediatric Urinary Tract Infection—A Single Center Experience
Authors: Isac Raluca , Doros Gabriela , Stolojanu Cristiana-Alexandra , Steflea Ruxandra Maria , Stroescu Ramona Florina , Olariu Ioana-Cristina , Micsescu-Olah Andrada-Mara , Gafencu Mihai
Published: July 2024

Urinary tract infection (UTI) represents one of the most common bacterial infections in children, mainly caused by Gram-negative bacteria. Empirical antibiotic treatment is based on international and national guidelines for treating UTIs in children and is individualized with local antibiotic resistance patterns. The aim of this study is to bring a clear view of present-day particularities of UTIs in children. Methods: We analyzed 210 positive urine cultures identified in 141 pediatric patients admitted to the hospital over a 6-month period. Results: The majority of patients were females (57%) with a median age of 5 years (IQR 12), while male patients revealed a median age of 2 (IQR 7). Most patients originated from urban areas (53%). Only 18 patients (12.76%) were identified with underlying Congenital Anomalies of the Kidney and Urinary Tract (CAKUT). Escherichia Coli was the most frequent pathogen. Increased antibiotic resistance was found in commonly-used antibiotics Ampicillin and Trimethoprim/Sulfamethoxazole, and in the case of patients with CAKUT. Suitable antibiotics for treating a Gram-negative UTI are aminoglycosides, Meropenem, third-generation Cephalosporins, and Nitrofurantoin. Vancomycin upholds efficacy in treating a Gram-positive pediatric UTI. Conclusion: Periodical analysis needs to be performed in order to constantly update clinicians on uropathogenic antibiotic resistance and optimal empirical treatment options.
Peri-Implant Microbial Signature Shifts in Titanium, Zirconia and Ceria-Stabilized Zirconia Reinforced with Alumina Sites Subjected to Experimental Peri-Implantitis: A Preclinical Study in Dogs
Authors: López-Píriz Roberto , Sevillano David , Fernández Domínguez Manuel , Alou Luis , González Natalia , Goyos-Ball Lidia , Cabal Belén , Moya José Serafín , Gómez-Lus María Luisa , Torrecillas Ramón
Published: July 2024

This study evaluates the dynamic shift in the microbiota at the peri-implant site of titanium (Ti) and zirconia (Zr) implants subjected to experimental peri-implantitis (PI) and, for the first time, of implants made of ceria-stabilized alumina-reinforced zirconia (Ce-TZP/Al), a revolutionary zirconia that is set to play a key role in modern implant dentistry. One- and two-piece (TP) implants, including Ce-TZP/AL TP/G3 glass, were placed bilaterally (six implants/side) in five beagle dogs to mimic a natural vs. ligature-induced PI following a split-mouth design. The experiment spanned 30 weeks from tooth extraction. Both PI models promoted plaque deposition at peri-implant sites. Comparatively, the PI induced by ligatures favored the deposition of anaerobes (p = 0.047 vs. natural). Regardless of the model, the plaque deposition pattern was entirely dependent on the implanted material. Ligated Ti and Zr implant sites accumulated up to 2.14 log CFU/mL unit anaerobic load (p ≤ 0.033 vs. non-ligated implant sites), predominantly comprising obligate anaerobes. Naturally occurring PI induced the deposition of co-occurring networks of obligate anaerobes and less oxygen-dependent bacteria. PI induction favored the enrichment of Ti and Zr sites with bacterial taxa belonging to the orange and red complexes (up to 28% increase naturally and up to 71% in the ligated hemiarch). Anaerobic deposition was significantly lower in ligated Ce-TZP/Al implant sites (p ≤ 0.014 vs. TI and Zr) and independent of the induction model (0.63–1 log units of increase). Facultative bacteria prevailed at Ce-TZP/AL sites. The abundance was lower in the Ce-TZP/AL TP implant. Unlike Ti and Zr sites, taxa from the orange and red complexes were negligible. Biofilms configured at the Ti and Zr sites after ligation-induced PI resemble those found in severe IP. We hypothesize that, although surface properties (surface energy and surface roughness) and physicochemical properties of the substrate play an important role in bacterial adhesion and subsequent plaque formation, Ce-TZP/Al modulates several biological activities that preserve the integrity of the gingival seal by limiting PI progression. In conclusion, biofilm progression differs in peri-implant sites according to the specific properties of the material. Ce-TZP/A, unlike titanium or zirconia, prevents dysbiosis in sites subjected to experimental PI and preserves the microbial signature of emergent obligate anaerobes related to PI development.
Magnesium: A Defense Line to Mitigate Inflammation and Oxidative Stress in Adipose Tissue
Authors: Cazzola Roberta , Della Porta Matteo , Piuri Gabriele , Maier Jeanette A.
Published: July 2024

Magnesium (Mg) is involved in essential cellular and physiological processes. Globally, inadequate consumption of Mg is widespread among populations, especially those who consume processed foods, and its homeostasis is impaired in obese individuals and type 2 diabetes patients. Since Mg deficiency triggers oxidative stress and chronic inflammation, common features of several frequent chronic non-communicable diseases, interest in this mineral is growing in clinical medicine as well as in biomedicine. To date, very little is known about the role of Mg deficiency in adipose tissue. In obesity, the increase in fat tissue leads to changes in the release of cytokines, causing low-grade inflammation and macrophage infiltration. Hypomagnesemia in obesity can potentiate the excessive production of reactive oxygen species, mitochondrial dysfunction, and decreased ATP production. Importantly, Mg plays a role in regulating intracellular calcium concentration and is involved in carbohydrate metabolism and insulin receptor activity. This narrative review aims to consolidate existing knowledge, identify research gaps, and raise awareness of the critical role of Mg in supporting adipose tissue metabolism and preventing oxidative stress.
Neuroprotective Benefits of Rosmarinus officinalis and Its Bioactives against Alzheimer’s and Parkinson’s Diseases
Authors: Kosmopoulou Danai , Lafara Maria-Parthena , Adamantidi Theodora , Ofrydopoulou Anna , Grabrucker Andreas M. , Tsoupras Alexandros
Published: July 2024

Neurodegenerative disorders (NDs) are conditions marked by progressively escalating inflammation that leads to the degeneration of neuronal structure and function. There is an increasing interest in natural compounds, especially those from pharmaceutical plants, with neuroprotective properties as part of potential therapeutic interventions. Thus, the rich bioactive content of the perennial herb rosemary (Rosmarinus officinalis) is thoroughly reviewed in this article, with an emphasis on its pleiotropic pharmacological properties, including its antioxidant, anti-inflammatory, and neuroprotective health-promoting effects. In addition, a comprehensive analysis of the existing scientific literature on the potential use of rosemary and its bioactive constituents in treating neurodegenerative disorders was also conducted. Rosemary and its bioactives’ chemical properties and neuroprotective mechanisms are discussed, focusing on their ability to mitigate oxidative stress, reduce inflammation, and modulate neurotransmitter activity. The role of rosemary in enhancing cognitive function, attenuating neuronal apoptosis, and promoting neurogenesis is outlined. Key bioactive components, such as rosmarinic acid and carnosic acid, are also highlighted for their neuroprotective act. The promising outcomes of the conducted pre-clinical studies or clinical trials confirm the efficacy of rosemary in preventing or alleviating Alzheimer’s and Parkinson’s diseases both in vitro (in cells) and in vivo (in animal models of NDs). From this perspective, the applications of rosemary’s bio-functional compounds and extracts in the food, cosmetics, and pharmaceutical sectors are also presented; in the latter, we discuss their use against neurodegenerative disorders, either alone or as adjuvant therapies. This paper critically evaluates these studies’ methodological approaches and outcomes, providing insights into the current state of the clinical research and identifying potential avenues for future investigation. All findings presented herein contribute to the growing body of literature and support the exploration of natural compounds as promising candidates for novel applications and neuroprotective interventions, paving the way for more applied scientific research.
Geotechnical Stability Analysis of the Tiga Dam, Nigeria on the Assessment of Downstream Soil Properties, Erosion Risk, and Seasonal Expansion
Authors: Umar Ibrahim Haruna , Abubakar Adamu , Salisu Ibrahim Mu’azzam , Lin Hang , Hassan Jubril Izge
Published: July 2024

The Tiga Dam, a primary hydraulic structure in northern Nigeria, is subjected to intense hydrological stress during the rainy season, posing potential risks to its structural integrity. This study investigates the geotechnical properties and stability of the Tiga Dam in Kano State, Nigeria. Twelve soil samples from the downstream area were analyzed for specific gravity, grain size distribution, Atterberg limits, compaction parameters, permeability, and shear strength. The dam’s stability was assessed using Plaxis 2D under various reservoir conditions. Soil erodibility was evaluated using the Revised Universal Soil Loss Equation (RUSLE), and a linear regression model with noise was developed to predict soil expansion rates. The results showed heterogeneous soil properties, with specific gravity ranging from 2.11 to 2.63 and permeability from 3.40 × 10−9 to 1.49 × 10−7 m/s. Stability analysis revealed factors of safety of 1.322, 1.006, 1.002, and 1.147 for high reservoir, rapid drawdown, slow drawdown, and low reservoir conditions, respectively. The RUSLE K factor ranged from 0.055 to 0.145, indicating low to moderate soil erodibility. The expansion rate model demonstrated high accuracy (R2 = 0.989) in predicting seasonal and long-term soil expansion trends, with peak rates increasing from 16.94 mm/month in 2010–2013 to 19.45 mm/month in 2017–2020. This comprehensive analysis provides crucial insights into the Tiga Dam’s geotechnical behavior, highlighting potential vulnerabilities and the need for targeted management strategies to ensure long-term stability and safety.
Cold Nitrogen Plasma: A Groundbreaking Eco-Friendly Technique for the Surface Modification of Activated Carbon Aimed at Elevating Its Carbon Dioxide Adsorption Capacity
Authors: Siemak Joanna , Ulejczyk Bogdan , Mikołajczak Grzegorz , Pęksiński Jakub , Sreńscek-Nazzal Joanna , Młotek Michał , Krawczyk Krzysztof , Michalkiewicz Beata
Published: July 2024

The commercially available activated carbon was modified using barrier and spark discharge low-temperature nitrogen plasma treatment. The samples were investigated using nitrogen sorption at a temperature of −196 °C, XRD, SEM, and FTIR methods, and elemental analysis. The nitrogen content on the surface was increased, but other properties, such as specific surface area, total pore volume, pseudocrystallite height, and pseudocrystallite width, remained unchanged. The activated carbons after nitrogen plasma treatment indicated higher CO2 adsorption than the pristine ones. Since the investigated materials only differed in their nitrogen content, it has been unequivocally demonstrated that the increased presence of nitrogen is responsible for the enhanced adsorption of CO2. The low-temperature nitrogen plasma treatment of activated carbon is a promising method for enhancing CO2 capture.
Impact of Dual-Depth Head-Up Displays on Vehicle Driver Performance
Authors: Chen Chien-Yu , Chou Tzu-An , Chuang Chih-Hao , Hsu Ching-Cheng , Chen Yi-Sheng , Huang Shi-Hwa
Published: July 2024

In recent years, the display information of head-up displays for vehicles has gradually developed from single-depth to multi-depth. To reduce the workload of driving and the number of eye adjustments, researchers use the visual perception of human eyes to realize the image information integrated with the real world. In this study, HoloLens2 is used to demonstrate head-up displays of different depths. An electroencephalogram, an electro-ophthalmogram, and a NASA-TLX questionnaire were used to evaluate the fatigue of drivers during long-term driving. The results showed that a dual-depth head-up display could effectively reduce the driver’s workload.
Retreatability of Bioceramic-Filled Teeth: Comparative Analysis of Single-Cone and Carrier-Based Obturation Using a Reciprocating Technique
Authors: Spinelli Andrea , Zamparini Fausto , Lenzi Jacopo , Carboni Davide , Gandolfi Maria Giovanna , Prati Carlo
Published: July 2024

Objectives: To evaluate the retreatment efficacy of premixed bioceramic sealer using a reciprocating system, comparing single-cone and carrier-based obturation techniques. Materials and Methods: Twenty-three monoradicular teeth with oval canals were divided into two groups: NeoSealer Flo with single cone (SC) and NeoSealer Flo with Guttafusion (GF). Retreatment was performed using Reciproc Blue (RB) with a crown-down technique. X-ray and CBCT images were taken to measure the remnant areas and volumes. Results: Apical patency was achieved in all the samples. The remnants were mostly distributed in the middle third in the GF group, while an equal distribution in both the middle and apical thirds was observed in the SC group. The GF group had a lower remnant area and volume after RB 50.05, respectively (0.18 ± 0.33 mm2 vs. 0.39 ± 0.80 mm2 and 0.36 ± 0.59 mm3 vs. 0.51 ± 1.16 mm3). The use of RB 50.05 led to an additional reduction in the remnant areas in the SC (14.89%) and GF (69.49%) groups, while in terms of the volume, the reductions were 20.63% and 36.36%. Conclusions: Reciprocating instruments are effective in removing remnants from root canals filled with both single-cone and carrier-based techniques. The blooming effect in CBCT imaging suggests further in vivo studies for validation.
Incidence of Metaphorical Virtual Classrooms and Interactive Learning Objects in the Interaction of Online Students: An Ecuadorian Case Study
Authors: Herrera-Granda Erick P. , Loor-Bautista Jonathan G. , Mina-Ortega Jorge I.
Published: July 2024

This study explored the incidence of metaphorical virtual classrooms and interactive learning objects in the interaction of students in online mode. The main objective was to analyze how these digital tools, driven by a set of strategies to promote their use, affect the interaction of students in the virtual classroom system and their derived effects. To this end, the latest version of Moodle was implemented in conjunction with gamification plugins and interactive tools in the higher education institution used as a case study. The methodology consisted of data collection through ordinal instruments applied to the teachers and student performance metrics gathered using a plugin developed to extract accurate metrics of each student’s usage and performance through direct queries to the Moodle database and its processing through a neural network. This facilitated the collection of standardized data on the actual metrics of each virtual classroom at the end of the teaching of each subject from both the previous LMS and the newly implemented one. This data was then analyzed using advanced statistical techniques, including Mahalanobis distances, confirmatory factor analysis, and the Wilcoxon signed-rank test. These methods provided a compelling comparison between the old and new systems, revealing significant improvements in the metrics and factors evaluated. The results showed a significant improvement in teachers’ perceptions of the usability of the virtual classroom system and an increase in students’ academic performance, interaction, progress, and time spent learning in virtual contexts. These results provide solid empirical evidence of the added value of these educational tools as effective strategies for improving student interaction, performance, and motivation in online education.
Main Trend Topics on Industry 4.0 in the Manufacturing Sector: A Bibliometric Review
Authors: Reyes Domínguez Dayron , Infante Abreu Marta Beatriz , Parv Aurica Luminita
Published: July 2024

The main objective of this research is to identify current trends in Industry 4.0 within the manufacturing sector through bibliometrics. A dataset of 1069 documents from 2020 to 2024 obtained from the Web of Science is processed. Using the R-Bibliometrix package, research trends, leading authors, and institutional contributions are identified. The accelerated growth rate of 30.77% in publications confirms research interest. Thematic exploration reveals the convergence of Industry 4.0 with sustainability, AI, the Internet of Things, smart manufacturing, and digitalization as dominant themes. The transition towards smarter and more efficient systems is evident, with an emphasis on integrating sustainability into Industry 4.0 practices. Challenges persist in management adjustment, technological integration, and strategy for digital transformation. The study identifies sustainability and machine learning as critical enabling factors for Industry 4.0, while security and collaboration have emerged as key focus areas in recent years. A wide geographic distribution of research contributions with substantial international cooperation is observed, highlighting India, Italy, and China. Major journals like Sustainability and Journal of Manufacturing Systems emerge as influential platforms for disseminating research on the topic. The analysis of citation networks, co-occurrence, and thematic evolution underscores the multidimensional impact of Industry 4.0 technologies on manufacturing.
Controllability of Pre-Chamber Induced Homogeneous Charge Compression Ignition and Performance Comparison with Pre-Chamber Spark Ignition and Homogeneous Charge Compression Ignition
Authors: Krajnović Josip , Ugrinić Sara , Dilber Viktor , Kozarac Darko
Published: July 2024

This paper presents an experimental and numerical evaluation of the pre-chamber induced HCCI combustion concept (PC-HCCI) in terms of engine performance, emissions, and controllability. In this concept, a spark-initiated combustion in the pre-chamber is utilized to trigger the kinetically controlled combustion of an ultra-lean mixture in the main combustion chamber. The experimental measurements were performed on a single-cylinder engine with a custom-made active pre-chamber. A high compression ratio of 17.5 was used, which limits the maximum achievable engine load due to high knocking tendency but enables both standard PCSI combustion (flame propagation) at very high dilution levels and HCCI combustion at reasonable intake temperatures. The analysis of combustion characteristics and the resulting performance is performed at indicated mean effective pressures (IMEPs) of 3.5 and 3.0 bars, and three different intake temperatures of 80 °C, 90 °C, and 100 °C. The variation in engine load was achieved by adjusting the excess air ratio in the main chamber. On each combination of intake temperature and engine load, a spark sweep and an injected PC fuel mass sweep were performed to obtain the highest indicated efficiency while satisfying the restrictions in terms of combustion stability and knock intensity. It was shown that, unlike in a conventional HCCI engine, the combustion phasing can be directly and reliably controlled by adjusting either spark timing or the reactivity of the pre-chamber mixture, ensuring adequate combustion stability and eliminating potential misfires. A similar indicated efficiency as with conventional HCCI combustion was obtained, while the NOx emissions, although slightly elevated, are still insignificant. Compared to PCSI combustion at the same engine load, a 4-percentage-point increase in indicated efficiency and two times lower NOx emissions were achieved. Compared to the most efficient PCSI operating point, it was 1 percentage point lower, indicating that efficiency was achieved, but the specific NOx emissions are reduced by approximately 70%. Most importantly, very similar performance was obtained with significant variations in intake temperature, proving the reliability and adaptability of this combustion concept.
Effects of Materials and Riblets on Erosion Mitigation Induced by Multiple Collapses of Cavitation Bubbles
Authors: Kadivar Ebrahim , Rezaee Sasan , Löschner Udo , el Moctar Ould
Published: July 2024

The current research investigates the effects of materials and riblets on cavitation-induced erosion morphology, depth, and cross-sectional area through experimental approaches. To achieve these aims, the erosion of pure aluminum (1xxxAl or Al) and alpha brass (CuZn37 or CZ108), in the presence and absence of bio-inspired sawtooth riblets, was examined after exposure to multiple collapses of single cavitation bubbles with a wall distance of 1.8 (dimensionless). The results indicate that the erosion morphology resembles a rounded cone with a circular cross-section. Brass provides 21.6% more erosion resistance compared to that of Al in terms of material properties. Furthermore, the erosion for both Al (depth by 3.8% and width by 18.3%) and brass (depth by 7.9% and width by 27.4%) decreases in the presence of riblets compared to the results for flat surfaces. The greater erosion resistance of brass compared to Al is attributed to the superior mechanical stability of brass, making it a potentially suitable alloy for use in propellers and hulls in the shipping industry. In summary, the results reveal that riblet-equipped materials with high mechanical durability are promising erosion-resistant materials for the shipping industry. However, the potential for chemical reactions in a cathodic environment should be addressed to provide a comprehensive perspective in regards to reducing corrosion intensity.
An Effective Biochar Application for Reducing Nitrogen Emissions from Buffalo Digestate Storage Tank
Authors: Scotto di Perta Ester , Giudicianni Paola , Mautone Antonio , Grottola Corinna Maria , Cervelli Elena , Ragucci Raffaele , Pindozzi Stefania
Published: July 2024

Open manure storage contributes to the release of ammonia (NH3) into the atmosphere. Tank floating covers represent an effective technique to reduce NH3 emissions and biochar has been gain attention as a floating cover and as manure additive. Nevertheless, the mechanisms involved in the process still need to be elucidated since they are influenced by the biochar specific properties, application methods and dose. This work aims to study: (i) the biochar adsorption performances in an NH3 aqueous solution under conditions relevant to manure storage and (ii) the effect of different biochar application methods and dosage on NH3 emissions from buffalo digestate storage. The results show that a 43% reduction in NH3 emissions can be achieved by using biochar as a floating cover of 2 cm rather than as an additive. Moreover, the results show that the biochar produced at 550 °C acts as an adsorbent material for both NH4+ and NH3, by being adsorbed on the biochar surface in the form of NH4+ after H+ abstraction from the acid groups. A minimum cover height of 2 cm is required to give compactness and provide an additional resistance to the gas transfer, which is even more relevant than the adsorption in reducing NH3 emissions.
Study on a Landslide Segmentation Algorithm Based on Improved High-Resolution Networks
Authors: Sun Hui , Yang Shuguang , Wang Rui , Yang Kaixin
Published: July 2024

Landslides are a kind of geological hazard with great destructive potential. When a landslide event occurs, a reliable landslide segmentation method is important for assessing the extent of the disaster and preventing secondary disasters. Although deep learning methods have been applied to improve the efficiency of landslide segmentation, there are still some problems that need to be solved, such as the poor segmentation due to the similarity between old landslide areas and the background features and missed detections of small-scale landslides. To tackle these challenges, a proposed high-resolution semantic segmentation algorithm for landslide scenes enhances the accuracy of landslide segmentation and addresses the challenge of missed detections in small-scale landslides. The network is based on the high-resolution network (HR-Net), which effectively integrates the efficient channel attention mechanism (efficient channel attention, ECA) into the network to enhance the representation quality of the feature maps. Moreover, the primary backbone of the high-resolution network is further enhanced to extract more profound semantic information. To improve the network’s ability to perceive small-scale landslides, atrous spatial pyramid pooling (ASPP) with ECA modules is introduced. Furthermore, to address the issues arising from inadequate training and reduced accuracy due to the unequal distribution of positive and negative samples, the network employs a combined loss function. This combined loss function effectively supervises the training of the network. Finally, the paper enhances the Loess Plateau landslide dataset using a fractional-order-based image enhancement approach and conducts experimental comparisons on this enriched dataset to evaluate the enhanced network’s performance. The experimental findings show that the proposed methodology achieves higher accuracy in segmentation performance compared to other networks.
Light-YOLO: A Study of a Lightweight YOLOv8n-Based Method for Underwater Fishing Net Detection
Authors: Chen Nuo , Zhu Jin , Zheng Linhan
Published: July 2024

Detecting small dark targets underwater, such as fishing nets, is critical to the operation of underwater robots. Existing techniques often require more computational resources and operate under harsh underwater imaging conditions when handling such tasks. This study aims to develop a model with low computational resource consumption and high efficiency to improve the detection accuracy of fishing nets for safe and efficient underwater operations. The Light-YOLO model proposed in this paper introduces an attention mechanism based on sparse connectivity and deformable convolution optimized for complex underwater lighting and visual conditions. This novel attention mechanism enhances the detection performance by focusing on the key visual features of fishing nets, while the introduced CoTAttention and SEAM modules further improve the model’s recognition accuracy of fishing nets through deeper feature interactions. The results demonstrate that the proposed Light-YOLO model achieves a precision of 89.3%, a recall of 80.7%, and an mAP@0.5 of 86.7%. Compared to other models, our model has the highest precision for its computational size and is the lightest while maintaining similar accuracy, providing an effective solution for fishing net detection and identification.