bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization and Biological Application Assessment of Silver Nanoparticles Extracted from Telescopium telescopius (Linnaeus, 1758), the telescope snail - The Green Synthesis Revolution
Authors: P.R Vignesh , Rani V. Pushpa , Prabhu D. Antony , Ravindran Florence Suganya 
Published: September 2024

Abstract

Nanobiotechnology is a rapidly growing field with numerous applications in the medical field. The discipline combines biological research with various fields of nanotechnology. Nanodevices, nanoparticles, and nanoscale phenomena within nanotechnology are enhanced through nanobiology. Typically, nanoparticles are synthesized using either a top-down or bottom-up approach. However, these chemical methods can be dangerous as they involve handling toxic chemicals and producing toxic by-products. Therefore, researchers have conducted several studies to extract and synthesise nanoparticles from living sources, known as the "Green synthesis of Nanoparticles." Silver nanoparticles are particularly prioritised because they are harmless to the human body but detrimental to microbes even in minimal concentrations. Much effort has been devoted to extracting them from plant sources and microbes. Animal extracts are also potential reducing agents for extracting silver nanoparticles without the use of any toxic substances. It has been discovered that extracts from various animals used in nanoparticle manufacturing contain biomolecules that act as reducing and capping agents. In line with this perspective, the present study focuses on using the telescope snail, Telescopium telescopium (Linnaeus, 1758), as an animal source for producing silver nanoparticles. The extracted TtSN-particles (Telescopium telescopium Silver Nanoparticles) were subjected to various characterisation methods, including Ultra Violet- Visible Spectroscopy (UV Spectroscopy), Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray (EDX) and Dynamic Light Scattering Technique (DLS) analyses. The absorption of TtSN-particles was found at 360 nm. The sizes of the TtSN particles visualised in SEM were 98.44 nm, 81.88 nm, and 88.65 nm. The EDX pattern showed a predominance of silver in the colloidal solution of the synthesized TtSN-particles. In DLS, the intensity distribution was observed in diameters of 46.4 nm, 90.4 nm, and 182.8 nm, respectively. Additionally, the sharp peak of the XRD confirmed the crystallinity of the nanoparticles. Further bio-assays were conducted to study the anti-thrombolytic activity of the TtSN-particles. The results showed that the TtSN-particles significantly reduced the formation of blood clots in the veins compared to the control groups. These nanoparticles also exhibited antimicrobial activity against both gram-positive (Streptococcus mutans) and gram-negative bacteria (Escherichia coli). They possessed high antioxidant and anti-inflammatory activities, as confirmed by performing a DPPH assay and Heat hemolysis assay, respectively.
Model-independent Gamma-Ray Bursts Constraints on Cosmological Models Using Machine Learning
Authors: Liang Nan , zhang Bin , Wang Huifeng , Nong Xiaodong , Wang Guangzhen , Wu Puxun 
Published: September 2024

Abstract

In this paper, we calibrate the luminosity relation of gamma-ray bursts (GRBs) with the machine learning (ML) algorithms from the Pantheon+ sample of type Ia supernovae in a cosmology-independent way. By using K-Nearest Neighbors (KNN) and Random Forest (RF) selected with the best performance in the ML algorithms, we calibrate the Amati relation (Ep-Eiso) relation with the A219 sample to construct the Hubble diagram of GRBs. Via the Markov Chain Monte Carlo numerical method with GRBs at high redshift and latest observational Hubble data, we find the results of constraints on cosmological models by using KNN and RF algorithms are consistent with those obtained from GRBs calibrated by using the Gaussian Process.
HGREncoder: Enhancing Real-Time Hand Gesture Recognition with Transformer Encoder - A Comparative Study
Authors: Santillan Luis Gabriel Macias , Zea Jonathan A. , López Lorena Isabel Barona , Caraguay Ángel Leonardo Valdivieso , Benalcázar Marco E. 
Published: September 2024

Abstract

In the field of Hand Gesture Recognition (HGR), Electromyography (EMG) is used to detect the electrical impulses that muscles emit when a movement is generated. Currently, there are several HGR models that use EMG to predict hand gestures. However, most of these models have limited performance in real-time applications, with the highest recognition rate achieved being 65.78\% \textpm15.15\%, without post-processing steps. Other non-generalizable models, i.e., those trained with a small number of users, achieved a window-based classification accuracy of 93.84\%, but not in time-real applications. Therefore, this study addresses these issues by employing transformers to create a generalizable model and enhance recognition accuracy in real-time applications. The architecture of our model is composed of a Convolutional Neural Network (CNN), a positional encoding layer and the transformer encoder. To obtain a generalizable model, the EMG-EPN-612 dataset was used. This dataset contains records of 612 individuals. Several experiments were conducted with different architectures, and our best results were compared with other previous research that used CNN, LSTM and transformers. The findings of this research reached a classification accuracy of 95.25 \textpm4.9\% and a recognition accuracy of 89.7\% \textpm8.77\%. This recognition accuracy is a significant contribution because it encompasses the entire sequence without post-processing steps.
Risk evaluation for human factors of flight dispatcher based on the hesitant fuzzy TOPSIS-DEMATEL-ISM approach: A case study in Sichuan Airlines
Authors: Zeng Jing-Han , Huang Jing-Yang , Zhong Qing-Wei , Zhu Dai-Wu , Dai Yi 
Published: September 2024

Abstract

To effectively mitigate unsafe events and accident symptoms stemming from flight dispatchers’ human factors, this paper proposes a novel risk evaluation model to objectively and accurately identify and evaluate potential human risks associated with flight dispatchers. First, the HFACS (Human Factors Analysis and Classification System, HFACS) model is employed to construct a human risk assessment indicator system for flight dispatchers. Second, the hesitant fuzzy set is introduced to represent the uncertainty inherent during experts’ evaluation, and the improved TOPSIS (Technique for Order Preference by Similarity to Ideal Solution, TOPSIS) method is applied within a hesitant fuzzy environment to obtain rankings of human factors. Third, the hesitant fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory, DEMATEL)-ISM (Interpretive Structural Modeling, ISM) method is constructed to analyze the correlation among human factors, leading to the establishment of a multi-level hierarchical structure model. Finally, a case study of risk assessment for human factors of flight dispatchers in Sichuan Airlines is conducted to demonstrate the effectiveness of the proposed method. The results revealed the human factors that exhibit higher risks and the key factors influencing flight dispatchers’ human risk in Sichuan Airlines; then, a multi-level hierarchical structure model comprises five layers is developed to investigate the internal correlation among human factors, enabling the formulation of targeted improvement suggestions for higher-risk indicators and key influencing factors.
Structure and mobility of the lipid system in water-ionic liquid mixtures: magnetic resonance measurements and molecular dynamics simulations
Authors: Sashina A. N. , Khakimzyanova A. R. , Khakimov A. M. , Filippov A. V. , Khaliullina A. V. 
Published: September 2024

Abstract

Ionic liquids (ILs) are salts which persist in liquid state near room temperature. They are characterized by high thermal and chemical resistance, good solubility, and high ionic conductivity. ILs can be used as permeability enhancers for transdermal delivery of drugs. The study of the interaction of ILs with lipids is important for understanding their potential toxicity to cells and the environment. In this work, we discuss features of the molecular structure and mobility of the aqueous system consisting of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and ethylammonium nitrate ionic liquid (EAN) mixtures studied by NMR and computer simulation MD methods.
The 31P NMR line shape analysis revealed two lipid states in the systems: in D2O it is a lamellar liquid crystalline state associated with the formed vesicle-like structures of DMPC, while in EAN it is isotopic. The ratio of these states correlates with the ratio of solvents in the system. Based on the self-diffusion coefficients obtained by NMR, sizes of the diffusing particles were estimated.
The method of MD showed that DMPC molecules assemble into micelles in the presence of water. In the mixtures of EAN and water the configuration of DMPC molecules changed. When DMPC interacts only with EAN, the micelle disintegrates. It is thus inferred that the presence of IL in the environment significantly affects the structure of the lipid system. The comparative analysis of the SDCs revealed a correlation between values obtained by MD and NMR methods.
How to Combine Multiple Tools for the Genetic Diagnosis Work-up of B-Cell Acute Lymphoblastic Leukemia
Authors: Hidalgo-Gómez Gloria , Tazón-Vega Bárbara , Palacio Carlos , Saumell Silvia , Martínez-Morgado Noemi , Navarro Víctor , Murillo Laura , Velasco Pablo , Murciano Thais , de Heredia Cristina Díaz , Bosch Francesc , Armengol Gemma , Ortega Margarita 
Published: September 2024

Abstract

This study investigated the importance of comprehensive genetic diagnosis in pediatric B-cell acute lymphoblastic leukemia (B-ALL). We analyzed 175 B-ALL employing karyotyping, FISH, MLPA, targeted next-generation sequencing (t-NGS), and Optical Genome Mapping (OGM). This approach achieved an 83% classification rate, identifying 17 distinct genetic subtypes. Specifically, within B-other subtype, seven different subgroups were identified (ZNF384, IGH, DUX4, NUTM1 rearrangements, PAX5 alterations, PAX5 P80R, and IKZF1 N159Y). Secondary genetic alterations were observed, with copy number alterations (CNA) present in 60% of cases and mutations detected in 70.6%. While these alterations exhibited specific associations with certain genetic subtypes, CNAs did not appear to significantly impact the prognosis within these genetic groups. HeH, ETV6::RUNX1, ZNF384r, and PAX5 P80R exhibited excellent outcomes, contrasting with the poor prognoses observed in KMT2Ar, hypodiploidy, and CRLF2r (5-year overall OS were 50%, 50%, and 52%, respectively). These findings underscore the value of integrated genetic diagnostics for accurate subtyping, risk stratification, and guiding personalized treatment in pediatric B-ALL. Therefore, optimizing diagnostic workflows for routine clinical practice is crucial. Our study confirms the utility of conventional techniques (karyotyping and FISH), combined with t-NGS and OGM, for comprehensive genetic diagnosis.
Health implications of heavy metal contamination in urban vegetables: Assessing the risks in Kinshasa and Lubumbashi
Authors: Mputu Lievins Malolo , Ndelo Patrick Matondo , Tuakuila Joel , Ndelo-di-Phanzu Josaphat , Nuapia Yannick Belo 
Published: September 2024

Abstract

The contamination of edible vegetables with heavy metals is a significant global environmental and public health issue. These inorganic pollutants persist in the environment, accumulate in human tissues, and pose serious health risks. This study aimed to assess the levels of heavy metals such as aluminium (Al), arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), lead (Pb), manganese (Mn), selenium (Se), and zinc (Zn) in leaves of Brassica oleracea, Hibiscus sabdariffa L., Amaranthus sp., and Ipomoea batatas leaves. The samples were collected from urban markets in Kinshasa and Lubumbashi, two major cities in the Democratic Republic of Congo. The microwave digestion system was used to extract metals from the samples, and the concentrations of heavy metals were measured using advanced spectroscopic techniques. The detected concentration ranges (in mg/kg dry weight) were as follows: Pb (0.23–1.76), Cd (0.31–1.73), As (1.16–7.19), Fe (22.69–94.22), Zn (17.75-375.01), Al (18.78–93.62), Cr (0.15–0.77), Cu (1.88–16.17), Mn (7.03-153.89), and Se (0.51–3.17). The health risk assessments revealed significant non-carcinogenic and carcinogenic risks to local populations, particularly from Pb and As exposure. These findings highlight the urgent need for regulatory measures to reduce heavy metal exposure from consuming vegetables in urban areas, aligning with global health and sustainability goals.
Systematic Evaluation of AI-Generated Python Code: A Comparative Study across Progressive Programming Tasks
Authors: Qianyi Yang 
Published: September 2024

Abstract

Background: AI-based code assistants are on the rise in software development as powerful technologies offering streamlining of code generation and better-quality code. However, their effectiveness is very variable, and understanding their pros and cons becomes very important in regard to using them optimally.
Introduction: This study evaluates the capabilities of four prominent AI-based code assistants: GitHub Copilot, Microsoft Copilot, Tabnine, and ChatGPT. This study addresses whether the quality of produced code is functional, efficient, and maintainable and whether it has areas for improvement.
Methodology: The AI-generated code was compared in terms of correctness, McCabe complexity (cyclomatic complexity), efficiency, and code size. The correctness percentage was the portion of code without errors, McCabe complexity was used for measuring structural complexity, execution performance represented efficiency, and the size of the code was just by lines of code. All AI tools were benchmarked against a standard set of 100 prompts to ensure like-for-like assessment.
Results: GitHub Copilot had the highest correctness at 42%, and ChatGPT generated the most complex code—which was measured with a McCabe complexity score of 2.92. Efficiencywise, ChatGPT also topped with the highest number of codes that meet the "good" criteria. On average, Tabnine produced the shortest code, whereas GitHub Copilot and ChatGPT were among the most verbose. The analysis revealed that although AI-based assistants can generate high-quality code, they usually produce code far different from solutions written by developers themselves, and it is difficult for them to cope with dependencies between classes.
Conclusion: AI-based code assistants have substantial potential for improvingcode generation and software development efficiency. However, challenges remain, particularly in handling complex dependencies and producing ready-to-use code. The study suggests that leveraging the strengths of different assistants and focusing on enhancing their ability to manage complex coding scenarios could lead to significant advancements. Ongoing research and development are essential to address these limitations and fully harness the potential of AI-based code assistants in software development.
miRNA-541-5p regulates myocardial ischemia-reperfusion injury by targeting ferroptosis
Authors: Zhao ZhiYu , Li BoXia , Cheng DianWei , Leng YuFang 
Published: September 2024

Abstract

Background
Ferroptosis is recognized as a significant mechanism underlying myocardial ischemia‒reperfusion (I/R) injury. An increasing number of studies suggest that targeting iron death could be a new therapeutic approach. Currently, because of the mechanism of iron death, the mechanism of I/R injury via microRNA-targeted treatment has not been fully confirmed.
Methods
To establish a myocardial I/R model in SD rats. Deferoxamine was administered (100 mg/kg). The successful establishment of the rat I/R model was determined by histopathological analysis. Oxidative stress indices and iron death factors in rat serum or myocardial tissue were detected by ELISA, immunofluorescence and RT‒PCR. Differential target genes were subsequently screened via the sequencing of myocardial tissue miRNAs. In addition, rat H9C2 cardiomyocytes were cultured, and a target gene adenovirus vector was constructed. Changes in the cell survival rate, oxidative stress indices and iron death factors were detected by CCK8, Western blot, ELISA, immunofluorescence and RT‒PCR, respectively.
Results
In this study, to confirm the occurrence of iron death in the myocardial tissue of a rat model of myocardial I/R injury, the target gene miRNA-541-5p was screened via miRNA sequencing, and the level of miRNA-541-5p was greater in the myocardium of the I/R injury model group than in those of the control and DFO groups. Finally, further verification through cell experiments revealed that the overexpression of miRNA-541-5p can significantly inhibit the viability of cardiomyocytes and promote the accumulation of the oxidation product ROS, causing iron overload in cardiomyocytes and exacerbating cardiomyocyte damage, whereas reducing miRNA-541-5p expression can reverse this pathological condition.
Conclusion
In summary, miRNA-541-5p may be a biomarker of myocardial I/R damage diseases and can regulate oxidative stress and iron death by inhibiting the expression of miRNA-541-5p, thereby reducing the mechanisms of I/R injury.
Novel Rh catalytic systems based on microporous metal-organic framework MIL-53(Al) for “green” ethylene hydroformylation
Authors: Isaeva Vera I. , Tarasov Andrei L. , Tkachenko Olga P. , Savilov Sergei V. , Davshan Nikolai A. , Chernyshev Vladimir V. , Kustov Leonid M. 
Published: September 2024

Abstract

Novel hybrid nanomaterials were synthesized using microporous metal-organic framework MIL-53(Al) as a support for rhodium nanoparticles (Rh NPs). In order to elucidate the factors that govern the dispersion and location of Rh, MIL-53(Al) samples were synthesized using two alternative strategies: conventional solvothermal procedure and microwave (MW) activation of the reaction mass. It was established that the use of different preparation conditions for the synthesis of the MIL-53(Al) carrier results in the spatial manipulation of the structural characteristics of the Rh@MIL-53(Al) nanohybrids. The structural study revealed also a pronounced confinement effect of the MIL-53(Al) porous matrix for the Rh nanoparticles. The novel Rh@MIL-53(Al) nanohybrids show high efficiency in “green” ethylene hydroformylation into propionic aldehyde (propanal) using syngas produced by CO2 hydrogenation. Carbon dioxide hydrogenation (atmospheric pressure, 500oC) was performed over cobalt nanoparticles deposited on the MIL-53(Al) nanomaterial obtained in MW fields. Exceptionally high thermal stability of the MIL-53(Al) matrix under conditions of the two-stage catalytic process was found. This work results demonstrate the new potential of the nanostructured catalysts based on the MIL-53(Al) carrier in the carbon dioxide conversion into value-added products.
Analysis of the Guatemalan Earthquake Catalog
Authors: González-Negreros Ramiro Alfonso , Gáspar-Escribano Jorge .M 
Published: September 2024

Abstract

In this paper, we study the geographic and temporal distribution of earthquakes in Guatemala. We utilized the earthquake catalog of the national seismic network of Guatemala, complemented by two additional sources. First, we describe the development of the detection network and the seismic catalog. Second, we analyze the errors in the catalog and determine the quality of the focal locations examining their distribution in time and space while separating events into shallow and deep earthquakes. Finally, we calculate seismic parameters such as annual rates of earthquakes, magnitude of completeness, and the b-value of the frequency-magnitude distribution. The results indicate a strong variability in time and space of errors and seismic parameters that are linked to changes in the detection network. In conclusion, by highlighting the evolution of this catalog and its features, this paper underscores the importance of considering these spatial and temporal variations in future analysis of seismicity and seismic hazard in Guatemala. This topic can be of interest to other countries with similar characteristics in tectonics and detection networks.
On the accuracy of data assimilation algorithms for dense flow fields reconstructions
Authors: Sciacchitano A. , Leclaire Benjamin , Schröder Andreas 
Published: September 2024

Abstract

Within the framework of the European Union’s Horizon 2020 project HOMER (Holistic Optical Metrology for Aero-Elastic Research), data assimilation (DA) algorithms for dense flow fields reconstructions are comparatively assessed. The assessment is performed using a synthetic database that reproduces the turbulent flow in the wake of a cylinder in wall proximity. Both the cases of flat rigid wall and flexible panel undergoing periodic oscillations were considered. The participants were provided with datasets containing the particles locations and their trajectories identification numbers, at increasing tracers’ concentrations from 0.04 to 1.4 particles/mm3 (equivalent image density values between 0.005 and 0.16 particles per pixel, ppp). The requested outputs were the three components of the velocity, the nine components of the velocity gradient tensor and the static pressure, defined in the flow field on a Cartesian grid, as well as the static pressure on the wall surface, and its position in the deformable wall case. The results were analysed in terms of errors of the output quantities with respect to the ground truth values and their distributions. Additionally, the performances of the different DA algorithms were compared with that of a standard linear interpolation approach. The velocity errors were found in the range between 3% and 11% of the bulk velocity; furthermore, the use of the DA algorithms enabled an increase of the measurement spatial resolution by a factor between 3 and 4. The errors of the velocity gradients were of the order of 10-15% of the peak vorticity magnitude. Accurate pressure reconstruction was achieved in the flow field, whereas the evaluation of the surface pressure revealed more challenging. As expected, lower errors were obtained for increasing seeding concentration. The difference of accuracy among the results of the different data assimilation algorithms were noticeable especially for the pressure field and the compliance with governing equations of fluid motion, and in particular mass conservation. The analysis of the flexible panel test case showed that the panel’s position could be reconstructed with micrometric accuracy, rather independently of the data assimilation algorithm and the seeding concentration. The accurate evaluation of the static pressure field and of the surface pressure proved to be a challenge, with typical errors between 3% and 20% of the free-stream dynamic pressure.