bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring the Chemistry of High-Si/Al Metakaolin Geopolymers: From Synthesis to Structure
Authors: Prakash Jose
Published: September 2024

This experimental study investigates the impact of different silica-to-alumina (Si/Al) ratios on geopolymers synthesized from metakaolin. Various ratios of Si/Al (1:1, 1.5:1, 2:1, 3:1, 4:1, and 5:1) were employed, nano-silica was the source material to alter the Si ratio. Microstructure and strength were analysed using SEM, XRD, NMR, and compressive strength testing. FTIR examined the dissolution rate of aluminium (Al) and silicon (Si) molecules during geopolymerization as well as the formation of N-A-S-H gel. The binding energy of individual silicon atoms and the overall energy produced during geopolymerization were calculated using modelling and moulding techniques. The results showed that a Si/Al ratio of 2:1 led to the highest dissolution of Si and Al, promoting the formation of Si-O-T bonds and resulting in geopolymers with superior compressive strength. The mechanical performance at different Si/Al ratios was attributed to the production of N-A-S-H gel, rather than zeolitic nuclei or silicate derivatives. These findings provide a foundation for geopolymerization of mine tailings, which often possess high Si/Al ratios.
Machine learning and experiments revealed key genes related to PANoptosis linked to drug prediction and immune landscape in spinal cord injury
Authors: Li BO , Li Tao , Cai Yibo , Cheng Junyao , Zhang Chuyue , Liu Jianheng , Song Keran , Wang Zheng , Ji Xinran
Published: September 2024

Spinal cord injury (SCI) is a severe central nervous system injury without effective therapies. PANoptosis is involved in the development of many diseases, including brain and spinal cord injuries. However, the biological functions and molecular mechanisms of PANoptosis-related genes in spinal cord injury remain unclear. Bioinformatics analysis of public data of SCI, the differentially expressed genes (DEGs) identified by GSE151371 were hybridized with PANoptosis-related genes (PRGs) to obtain  differentially expressed PANoptosis-related genes (DE-PRGs). Through three machine learning algorithms, we obtained the hub genes. Then, we constructed functional analysis, drug prediction, regulatory network construction, and immune infiltrating cell analysis. Finally, the expression of the hub gene was verified in GSE93561, GSE45376 and qRT-PCR analysis. Through the above analysis, 14 DE-PRGs were obtained by intersecting 3582 DEGs with 46 PRGS. Five key hub genes, CASP4, GSDMB, NAIP, NLRC4, and NLRP3, were obtained by 3 machine learning algorithms. All five hub genes were enriched in phagocytosis mediated by FC GAMMA R. The 11 immune cells were significantly different between SCI group and HC group, such as mast cell and gamma delta T cell. The transcription factor (TF)-hub gene network contained 10-nodes (4 hub genes and 6 TFs) and 8-edges. The miRNA-hub gene network consisting of 5-nodes (3 hub genes and 2 miRNAs) and 3-edges was constructed. Morever, the CASP4 predicted 1 small molecule drug and NLRP3 predicted 9 small molecule drugs. Finally, the expression of 5 hub genes were significantly different in GSE45376 and GSE93561 (SCI vs HC) and mice SCI model (Sham vs SCI). Collectively, we identified 5 hub genes (CASP4, GSDMB, NAIP, NLRC4, and NLRP3) associated with PANoptosis, providing potential directions for treating spinal cord injury.
Intramuscular innervation of the frontalis muscle using sihler’s staining
Authors: Han Ju Eun , Kim Taeyeon , Lee Shin Hyo , Shin Kang-Jae
Published: September 2024

The facial nerve is the seventh cranial nerve, and its temporal branch (TBFN) innervates the frontalis muscle. Peripheral nerve disorders involving the facial nerve can lead to facial palsy, for which a common noninvasive treatment approach is to inject a chemodenervation agent such as botulinum toxin (BoNT). The purpose of this study was to provide anatomical suggestions for BoNT injection sites in the frontalis muscle based on the intramuscular innervation pattern of the TBFN as identified objectively using Sihler’s staining. Nineteen hemifaces containing the TBFN and the frontalis muscle were harvested from 15 embalmed cadavers according to facial landmarks. The frontalis muscle was divided into 16 areas to identify the prevalence rates of distal nerve endings and the arborization pattern of the TBFN after applying modified Sihler’s staining. Distal nerve endings of the TBFN were most commonly found in area B2 (17 of 19 specimens, 89.5%), followed by in area B3 (n = 15, 78.9%). The largest arborization patterns were observed in areas C4 and D4, which are the inferolateral ends of the frontalis muscle. We propose four BoNT injection sites based on the intramuscular innervation pattern of the TBFN in the frontalis muscle as identified using Sihler’s staining.
Insights into the Electrochemical Hydrogenation Reaction Mechanisms of Aromatic Compounds Mixtures over Bimetallic PtRu Catalyst
Authors: Sumner Joy , Jiang Ying , Catizane Cesar
Published: September 2024

Efficient and selective electrochemical hydrogenation (ECH) of organic compounds is crucial for global sustainability; offering both chemical feedstock circularity and routes to generate synthetic fuels, reducing fossil fuel reliance. This study focuses on ECH of benzoic acid (BA), phenol (P), and guaiacol (G), commonly appearing as mixtures in potential oils for upgrade. The impact of various conditions on the hydrogenation process was elucidated using a carbon-supported PtRu catalyst; assessing initial concentrations/mixtures, temperatures, and current densities. Phenol ECH exhibited the most favourable outcome, achieving an 83.17% conversion rate and 60% Faradaic Efficiency (FE). When mixtures (BA + P, BA + G, P + G, and BA + P + G) were evaluated, revealing that BA + P yielded the highest conversion rate (64.19%) and FE (74%). This outcome suggests a potential synergistic effect between benzoic acid and phenol. Additionally, regardless of experimental parameters, BA selectivity for cyclohexane carboxylic acid (CCA) remained consistently at 100%. Density functional theory (DFT) calculations provided insight into molecular/catalyst interactions, highlighting the stability of parallel positioning the BA molecule on the cathode surface compared to perpendicular placement (-1.12 eV vs. 0.58 eV), this offers a plausible explanation for the observed high selectivity towards CCA. These findings provide a foundation for future developments in ECH of real pyrolysis oil.
Evaluating the Dynamic Response and Phase Angle Behavior of SBS-Modified Asphalt Mixtures for Enhanced Pavement Performance
Authors: Khan Inamullah , Bilal Muhammad , Khaliq Wasim , Khan Nasir , Khahro Shabir Hussain , Memon Zubair Ahmed , Malik Muhammad Abdul
Published: September 2024

Bitumen exhibits viscoelastic properties, showcasing both viscous and elastic behaviors, which are characterized by the phase angle (Ø) and dynamic modulus (|E*|). Issues like early fatigue fractures, rutting, and permanent deformations in bituminous asphalt pavements arise due to moisture susceptibility, high-temperature deformation, low-temperature cracking, and overloading. These distresses result in potholes, alligator cracks, and specific deformations that lead to early pavement failure, increasing rehabilitation and maintenance costs. To address these issues, this study examines the dynamic response (|E*|) and phase angle (Ø) behavior of Styrene Butadiene Styrene (SBS) modified and unmodified asphalt mixtures. SBS was incorporated in various proportions, ranging from 2–7% by the weight of bitumen. The asphalt mixture performance tester (AMPT) was utilized to measure the |E*| at temperatures of 4.4, 21.1, 37.8, and 54.4°C, and frequencies of 0.1, 0.5, 1, 5, 10, and 25 Hz. The study found significant correlations between dynamic modulus, temperature, loading frequency, and SBS content. Additionally, Multi Expression Programming (MEPX) and regression modeling were employed to estimate the |E*| of SBS-modified HMA. Results indicated that increasing SBS content up to 7% decreased penetration and ductility values by up to 46% and 56%, respectively, while raising the softening point by 63% due to increased stiffness. The blend with 6% SBS by weight of bitumen exhibited superior performance compared to other mixtures. Phase angle initially increased with rising temperature, peaking at 37.8°C at lower frequencies, and continued to increase at higher frequencies. Isothermal and isochronal plots showed that the 0% SBS mix had a higher phase angle due to increased bitumen content. Overall, the HMA mix with 6% SBS provided the best outcomes.
Exploring the relationship between TNF-β in mediating Mannose in Primary biliary cholangitis by Two-Step Mendelian randomization analysis and machine learning
Authors: Xu Zihao , Liu Yifan , Xu Jun , Cheng Liangbin
Published: September 2024

Observational studies have suggested an association between mannose and the prognosis of Primary biliary cholangitis (PBC). The interactions between immune cell-mediated inflammatory factors and PBC may contribute to the pathogenesis of PBC and present therapeutic potential. However, the causal relationship between mannose and PBC, along with the mechanisms mediated by inflammatory factors, remains to be elucidated.Using publicly available GWAS gene data, we employed a two-sample Mendelian randomization (MR) method to investigate the causal association between Mannose and PBC. Additionally, through two-step Mendelian randomization, we investigated the mediating role of TNF-β in the causal association between Mannose and PBC. Furthermore, we utilized the GEO database to obtain single-cell RNA-seq and Bulk RNA-seq data of PBC and controls using machine learning methods to validate our findings.We found that with Mannose as the exposure factor and PBC as the outcome, the OR was 0.1977 (95% CI: 0.0502~0.7776,p=0.020). With TNF-β as the exposure factor and PBC as the outcome, the OR was 0.4661 (95% CI: 0.3160~0.6875,p<0.001). With Mannose as the exposure factor and TNF-β as the outcome, the OR was 1.4993 (95% CI: 1.0438~2.1537,p=0.028). These findings were further validated using single-cell and bulk RNA-seq machine learning approaches, confirming the mediating role of TNF-β in the association between Mannose and PBC.Our analysis indicates a causal association between Mannose and PBC where TNF-β plays a mediating role.
Investigation of the Reproductive Behavior of Tarim Pigeons
Authors: Zhu Lin , Kamal Mahmoud , Sun Mengyue , Li Yao , Fu Rui , El-Hack Mohamed E. Abd , Wang Zewu , Yang Kailun , Li Fengming , Cheng Yanfen
Published: September 2024

This study aims to investigate pigeon behavior across various stages of the breeding period and document their behavioral frequencies to contribute to the theoretical foundation for pigeon breeding and management. The experiment involved ten pairs of pigeons in the incubation period, nine pairs of parent pigeons within the first ten days of the nurturing period, and nine pairs of parent pigeons with chicks above ten days. The direct observation method records behaviors from 8:22 to 22:00 daily. Our results revealed that the female pigeon was primarily responsible for incubation during the incubation period, followed by male pigeons. The average incubation duration for female pigeons was 7.94 hours, primarily concentrated between 8:22 − 13:00 and 20:00–22:00. The average incubation duration for male pigeons was 4.05 hours, mainly occurring between 13:00–20:00. Pigeon feed intake and frequency during the nursing period exceeded that of the incubation period, and both increased with offspring age. During the breeding period, feeding behavior peaked at 8:22 − 10:00, 13:00–14:00, and 19:00–21:00; drinking behavior peaked at 13:00–14:00 and 20:00–21:00, with feeding behavior being most frequent at 13:00–14:00; mating behavior predominantly occurred between 17:00–22:00. Artificial feeding affects the behavioral rhythms of pigeons, particularly in feeding and nursing behaviors.
Hovering and standing guards: nest defense strategies in a polymorphic stingless bee (Tetragonisca angustula)
Authors: Santos Luana Guimarães , Vieira Bruno , Pedrosa Jéferson , Nascimento Fábio do
Published: September 2024

The stingless bee, Tetragonisca angustula, has a sophisticated nest defense strategy carried out by guards that are larger compared to other workers. Guards display two different strategies: flying near the colony entrance (hovering guards) or positioning themselves at the entrance tube (standing guards). To better understand the roles played by each guard behavioral phenotype in nest defense, we investigated whether their behaviors were distinctly displayed when faced with different threats. We used two types of bait (flying and walking) to simulate threats to the colony and compared the behaviors displayed by the guards in relation to the species used as bait and the guard function. We also investigated if the species and the type of bait influenced the number of guards before and after the presentation. We found a significant interaction between the behaviors displayed by the guards and the bait species. Hovering guards were more influenced by flying baits, and standing guards by walking baits. The presence of Lestrimellita limao caused a high proportion of recruitment and aggressive behavioral responses from guards, confirming specialization against this potential enemy. Our results show that the two behavioral phenotypes are capable of recognition and act with complementary behaviors depending on the threat.
Design and mechanical properties analysis of drill pipe’s joint thread with unequal taper under complex loads
Authors: Liu Hangming , Song Yongpeng , Hu Shunhua , He Yuxian , Wan Jifang , Yi Xianzhong , Hou Song
Published: September 2024

The design of drill pipe joint thread with unequal taper is proposed to investigate the fracture failure of the API NC38 used in the drill pipe joint of the SU36-8-4H2 well. The effect of changes in thread taper on the stress distribution and mechanical properties of drill pipe joints is analyzed and compared with the API standard thread to determine the optimal thread structure with unequal taper. The results reveal highly concentrated stress at the last engaged thread root of API NC38 single-shoulder thread (SUT) may cause early yield failure of the joint threads. Adjusting the unequal taper of the pin thread mitigates uneven stress distribution in NC38 single and double-shoulder threads and enhances connection strength, particularly for SUT-II and DUT-I. However, altering the box thread's unequal taper modifies the stress concentration slightly in NC38 single and double-shoulder threads. This offers limited tensile and compressive strength improvement. The maximum Mises stress value of SUT-II is reduced by 56.69% compared to SUT. The maximum Mises stress value of DUT-I is reduced by 34.87% compared to NC38 double-shoulder joint thread (DUT). This design approach can guide the optimization of other API standard threads and enhance joint strength for non-API and specialized taper threads.
Machine Learning-Based Real-Time Feedback Assessment System for Student Performance Prediction in Tertiary Institution
Authors: Ebem Deborah Uzoamaka , Ikegwu Anayo Chukwu , Ezugwu Chinenye Juliet , Ikpo Chibueze Valentine , Ogbunude Festus Okechukwu
Published: September 2024

The need for effective and digitized formative feedback mechanisms in classroom management of core courses in tertiary institutions in the developing world such as Nigeria, Kenya, and Ghana is paramount. A fair trivial environment is needed for students to learn and interact with their tutor effectively. This paper presents a framework for feedback assessment in real-time for student performance prediction using a machine learning approach in the university to maximize students’ satisfaction through an internalized and effective learning environment by monitoring students’ level of engagement during lecture sessions. The analysis from the existing system shows that the large amount of data generated from students’ responses makes it possible to predict student performance per course. This was done using machine learning (K-Nearest Neighbor) to predict the likelihood of student performance and engagement overtime on the dataset generated from attendance, personal and assessment history. The system was developed using Django (Python Framework). The empirical result from the classifier shows that KNN presented an accuracy of 78%. The implication of the study would further assist the developing country’s university system, increase the performance rate of student engagement and lecturer’s teaching styles, as well as aid in the educational decision-making process.
An Experimental Investigation of Optimum Process Parameters for Friction Stir Welding of Copper Plate
Authors: Tefera Mulugeta Belay , Fetene Besufekad Negash , Debebe Seyfu Tiruneh , Sinha Devendra Kumar
Published: September 2024

In this study, the friction stir welding technique was utilized to create qualified weld joints from a 5mm thick copper plate on a vertical milling machine. The experiments involved a steel backing plate and tool profiles with different pin shapes, including flat cylindrical, cylindrical threaded pin, and square pins, each with 3 shoulder pin ratios. Process parameters were determined using Taguchi’s L9 orthogonal array. The experiments considered tool geometry or pin profile, tool rotational speed (9100 RPM, 1280 RPM, 1700 RPM), and weld speed (16 mm/min, 29 mm/min, 44 mm/min). Tensile strength analysis indicated that welding speed had the most significant impact, contributing 76.90%. Hardness analysis showed that the tool profile had the highest influence, contributing 84.67%. The highest tensile strength achieved was 345.03 MPa with a cylindrical threaded tool profile, 1700 RPM tool rotation, and 16 mm/min weld speed. The maximum hardness obtained was 94 RHE with a square tool profile, 910 RPM tool rotation, and 44 mm/min weld speed. The study revealed that welding speed significantly affected the ultimate tensile strength of FSW joints in the copper plate, while the tool profile was crucial in achieving optimal hardness in the Heat Affected Zone (HAZ), Thermo-Mechanically Affected Zone (TMAZ), and Stir Zone (SZ).
Title: Prediction of Functional Disability in Older Chinese Adults Using a Random Survival Forest Model
Authors: Shan Yifan , Jiang Shuai , Yu Dahai , Fan Wei , Gao Jinghong , Lu Wei , Duan Yanran , Zhang Yafeng , Wang Sufan , Fu Hang , Wang Chengzeng
Published: September 2024

Background
As life expectancy increases, so does the risk of age-related diseases and functional disability, which significantly raises the risk of all-cause mortality in older adults. Individuals with disabilities may die up to 20 years earlier than those who are non-disabled.
Objectives
To develop a prediction model for functional disability using random survival forest analysis (RSF).
Methods
Data were drawn from 2,364 older adults without functional disability from the China Health and Retirement Longitudinal Study (CHARLS), conducted from 2011 to 2020. Functional disability was the primary outcome. Univariable and multivariable Cox regression analyses were used to identify significant factors, which were then screened using variable importance (VIMP) and minimal depth to construct the RSF model. The model's performance was evaluated using calibration curves and the area under the receiver operating characteristic (AUC) curve. Multimorbidity trajectories were also identified as potential risk factors through group-based multi-trajectory modeling.
Results
Four multimorbidity trajectories were identified: no multimorbidity, newly-developing, moderate-developing, and severe-developing. The RSF model outperformed the Cox regression model in predicting functional disability, with key factors including age, education, walking time, grip strength, CES-D score, and multimorbidity trajectories. Significant factors identified were CES-D score, grip strength, multimorbidity trajectory, age, and the use of antihypertensive medications.
Conclusions
The RSF model, based on CHARLS data, effectively predicts functional disability in older adults, with depressive symptoms, handgrip strength, multimorbidity trajectories, age, and antihypertensive medication use emerging as key predictors.
ERAD deficiency disrupts mitochondrial bioenergetics by altering MAM Ca2+ in human hepatic cells
Authors: Hu Yabing , Bai Yongfeng , Jiang Beier , Wang Mingming , Zhang Feng
Published: September 2024

Mitochondria and the endoplasmic reticulum (ER) physically and functionally interact, regulating each other’s function, but the molecular mechanisms remain not fully understood. In this study, we revealed that ER-associated degradation (ERAD), an ER protein quality control mechanism, governs ER Ca2+ entry into mitochondria by mitochondria-associated ER membrane (MAM) in hepatic cells. Inhibition of ERAD by pharmaceuticals or genetic ablation of the key ERAD protein SEL1L resulted in altered mitochondrial morphology, reduced mitochondrial energy production, and increased Ca2+ transfer from ER to mitochondria. Additionally, SEL1L absence caused an increase in the number of MAM. In ERAD-deficient hepatic cells, a reduction in the number of MAM or knockdown of the inositol 1,4,5-trisphosphate receptor (IP3R), which is responsible for ER Ca2+ release, partially restored mitochondrial Ca2+ signaling and bioenergetics. Together, these results suggest that ERAD plays a crucial role in regulating mitochondrial bioenergetics, suggesting the potential to improve cellular and organismal mitochondrial function by increasing cellular ERAD activity.
New Virtual Contrast Enhancement Boost Technique Can Reduce the Dose of Intravenous Contrast Medium Used in Angiotomography of the Abdominal Aorta
Authors: Noschang Julia , Tachibana Adriano , Viviani Larissa Barsotti da Silva , Silva Murilo Marques Almeida , Mendes Cynthia Almeida , Rocha Marcelo Assis , Ishikawa Walther Yoshiharu , Wolosker Nelson , Szarf Gilberto
Published: September 2024

Purpose: This study aims to evaluate the image quality of computed tomography (CT) angiograms obtained using a virtual contrast augmentation technique, adding an iodine map to the contrast-enhanced images, obtained through a digital subtraction technique, reducing the dose of intravenous iodinated contrast medium compared to the conventional institutional standard technique.
Methods: This prospective investigation enrolled patients previously diagnosed with abdominal aortic aneurysms, who underwent two successive computed tomography angiographies (CTAs) of the aorta. One CTA was performed employing the virtual contrast enhancement boost technique with a 40% decrease in the intravenous contrast medium dose, while the other adhered to the conventional protocol without any reduction in contrast medium volume. After imaging, both qualitative and quantitative assessments were conducted to evaluate the opacification level of the aorta and its branching vessels.
Results: The study analyzed 28 examinations from 14 subjects (two per participant). Qualitative analysis revealed that image quality was deemed adequate for diagnostic purposes, with nearly all arterial segments in both protocols rated as good or excellent. Although no statistically significant differences were detected, the average attenuation across all arterial segments in the angiograms exhibited a trend towards higher values in the virtual contrast enhancement boost technique, compared to the conventional protocol. Similarly, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) demonstrated comparable levels between the two methodologies.
Conclusion: The application of virtual contrast enhancement in the acquisition of CT angiograms of the aorta maintains comparable image quality, while reducing the dosage of intravenous contrast medium in 40%. This approach suggests a potential for optimizing contrast use in vascular imaging, aligning with goals related to patient safety and radiological efficiency.
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

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

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

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

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

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

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

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

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

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

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

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

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.
Using Computational Systematic Social Observation to Identify Environmental Correlates of Fear of Crime
Authors: Solymosi Reka , Parkinson Simon , Pődör Andrea , Khan Saad , Khan Muhammad
Published: September 2024

There is great importance in understanding whether people perceive an environment as safe or unsafe. Perceptions are influenced by the built environment, and through better understanding, design interventions can be made to improve the feeling of safety. There is a rich body of research on this topic, yet it requires a lot of manual effort. In this work, we present an approach named Computational Systematic Social Observation (CSSO) to automate the collection and analysis process. The approach uses Google Street View and the Google Vision API to extract characteristics (herein referred to as features) of the built environment that is used to automate the process of understanding whether people will feel fear or safety. In testing this approach, we extracted 1.3M images for the 100 locations and identified 297 features of the built environment. A measure of dependency demonstrated that some are more strongly associated with areas where people express a feeling of safety or fear. Further, through empirical testing, it is observed that these features can be used for classification. The results demonstrate the potential of the technique and were compared with human coders. The presented methodology and experimental research provide a foundation for systematic computational observation to identify environmental correlates of fear of crime.