bluuebunny/crossref_metadata_2025 huggingface dataset:
The Lognormal Distribution Is Characterized by Its Integer Moments
Authors: Novi Inverardi Pier Luigi , Tagliani Aldo
Published: December 2024

The lognormal moment sequence is considered. Using the fractional moments technique, it is first proved that the lognormal has the largest differential entropy among the infinite positively supported probability densities with the same lognormal-moments. Then, relying on previous theoretical results on entropy convergence obtained by the authors concerning the indeterminate Stieltjes moment problem, the lognormal distribution is accurately reconstructed by the maximum entropy technique using only its integer moment sequence, although it is not uniquely determined by moments.
Surrounding Rock Squeezing Classification in Underground Engineering Using a Hybrid Paradigm of Generative Artificial Intelligence and Deep Ensemble Learning
Authors: Cheng Shouye , Yin Xin , Gao Feng , Pan Yucong
Published: December 2024

Surrounding rock squeezing is a common geological disaster in underground excavation projects (e.g., TBM tunneling and deep mining), which has adverse effects on construction safety, schedule, and property. To predict the squeezing of the surrounding rock accurately and quickly, this study proposes a hybrid machine learning paradigm that integrates generative artificial intelligence and deep ensemble learning. Specifically, conditional tabular generative adversarial network is devised to solve the problems of data shortage and class imbalance for data augmentation at the data level, and the deep random forest is built based on the augmented data for subsequent squeezing classification. A total of 139 historical squeezing cases are collected worldwide to validate the efficacy of the proposed modeling paradigm. The results reveal that this paradigm achieves a prediction accuracy of 92.86% and a macro F1-score of 0.9292. In particular, the individual F1-scores on strong squeezing and extremely strong squeezing are more than 0.9, with excellent prediction reliability for high-intensity squeezing. Finally, a comparative analysis with traditional machine learning techniques is conducted and the superiority of this paradigm is further verified. This study provides a valuable reference for surrounding rock squeezing classification under a limited data environment.
Physics-Informed Generative Adversarial Network Solution to Buckley–Leverett Equation
Authors: Ma Xianlin , Li Chengde , Zhan Jie , Zhuang Yupeng
Published: December 2024

Efficient and economical hydrocarbon extraction relies on a clear understanding of fluid flow dynamics in subsurface reservoirs, where multiphase flow in porous media poses complex modeling challenges. Traditional numerical methods for solving the governing partial differential equations (PDEs) provide effective solutions but struggle with the high computational demands required for accurately capturing fine-scale flow dynamics. In response, this study introduces a physics-informed generative adversarial network (GAN) framework for addressing the Buckley–Leverett (B-L) equation with non-convex flux functions. The proposed framework consists of two novel configurations: a Physics-Informed Generator GAN (PIG-GAN) and Dual-Informed GAN (DI-GAN), both of which are rigorously tested in forward and inverse problem settings for the B-L equation. We assess model performance under noisy data conditions to evaluate robustness. Our results demonstrate that these GAN-based models effectively capture the B-L shock front, enhancing predictive accuracy while embedding fluid flow equations to ensure model interpretability. This approach offers a significant advancement in modeling complex subsurface environments, providing an efficient alternative to traditional methods in fluid dynamics applications.
Influences of Reciprocal Altruistic Preferences and Reference Low-Carbon-Level Effect on Carbon Emission Transfer Strategies of Supply Chains
Authors: Zhao Biying , Li Dongyue , Sun Licheng , Wang Wentao
Published: December 2024

Consumers’ low-carbon preferences will affect the decision-making behavior of supply chain members; an understanding of the influence mechanism of reciprocal altruistic preferences and reference low-carbon-level effect on carbon emission transfers in a supply chain is of great significance for optimizing transfer and reducing emissions and enhancing the overall emission reduction effect of the supply chain. By constructing a manufacturer-led differential game model, we analyzed the carbon emission transfer strategy of a supply chain under the influence of the reference low-carbon level effect and reciprocal altruistic preferences in scenarios with and without such preferences. The results showed that the reference low-carbon-level effect had a positive influence on the manufacturer’s transfers but not on the supplier’s acceptance of them. Moreover, reciprocal altruistic preferences increased both the transfer and acceptance of emissions while improving the low-carbon level of products. Under the influence of reciprocal preferences, the difference in the degree of altruism will also affect the carbon emission transfer and acceptance behavior of the manufacturer and supplier. When the supplier’s reciprocal altruism coefficient and the consumer’s memory parameter remain within a certain range, the transfers positively affect cooperation in the supply chain.
High-Dimensional U-Statistics Type Hypothesis Testing via Jackknife Pseudo-Values with Multiplier Bootstrap
Authors: Zhang Mingjuan , Jin Libin
Published: December 2024

High-dimensional parameter testing is commonly used in bioinformatics to analyze complex relationships in gene expression and brain connectivity studies, involving parameters like means, covariances, and correlations. In this paper, we present a novel approach for testing U-statistics-type parameters by leveraging jackknife pseudo-values. Inspired by Tukey’s conjecture, we establish the asymptotic independence of these pseudo-values, allowing us to reformulate U-statistics-type parameter testing as a sample mean testing problem. This reformulation enables the use of established sample mean testing frameworks, simplifying the testing procedure. We apply a multiplier bootstrap method to obtain critical values and provide a rigorous theoretical analysis to validate the approach. Simulation studies demonstrate the robustness of our method across a variety of scenarios. Additionally, we apply our approach to investigate differences in the dependency structures of a subset of genes within the Wnt signaling pathway, which is associated with lung cancer.
The Effect of Training Experience on Cardiac Morphology in Resistance Exercise Practitioners: A Study on Left Ventricular Systolic and Diastolic Parameters and Left Atrium Mechanical Functions
Authors: Kurtoğlu Ahmet , Kurtoğlu Ertuğrul , Çar Bekir , Eken Özgür , Muracki Jarosław , Setiawan Edi , Alotaibi Madawi H. , Elkholi Safaa M.
Published: December 2024

Background and Objectives: Resistance exercises (REs) are a type of physical activity that individuals from many age groups have been doing recreationally, both as amateurs and professionally, in their daily lives in recent years. It is crucial to understand the effects of such sports on cardiac morphology in order to maximize the benefit of training and to tailor the training content accordingly. The aim of this study was to investigate the relationship between training experience (TE) and left ventricular (LV) systolic and diastolic parameters and left atrial (LA) mechanical function in healthy subjects who regularly performed RE for different durations. Materials and Methods: Forty-five healthy adults [age = 28.91 ± 10.30 years, height = 178.37 ± 5.49 cm, weight = 83.15 ± 13.91 kg, body mass index = 26.03 ± 3.42 kg/m2, TE = 7.28 ± 6.49 years] who performed RE between 1 year and 20 years were included in our study. The transthoracic echocardiograms (ECHOs) of the participants were evaluated by the cross-sectional research method, which is often used to understand the current situation in a given time period. Correlations between TE and LV systolic and diastolic parameters and LA mechanical function were analyzed. Results: As a result, interventricular septal thickness (IVS; r = 0.33, p = 0.028), the aortic diameter systole (ADs; r = 0.56, p < 0.001), and aortic diameter diastole (ADd; r = 0.58, p < 0.001) were positively correlated with TE, indicating associations with increased left ventricular (LV) hypertrophy and reduced ventricular compliance, while the aortic strain (AS; r = −0.44, p = 0.002), aortic distensibility (AD; r = −0.62, p < 0.001), and diastolic flow parameters including E (r = −0.41, p = 0.005), E/A (r = −0.38, p = 0.011), and E/Em (r = −0.31, p = 0.041) were negatively correlated with TE, reflecting impairments in diastolic function. Conclusions: This study showed that diastolic parameters were adversely affected in chronic RE. Therefore, we think that these individuals may have decreased relaxation and filling functions of the heart, which may also reduce adequate oxygen and nutrient delivery to the tissues. In this context, cohort studies are needed to analyze in detail the reasons for the decrease in diastolic parameters in these individuals.
SurfILE: An Open-Source Python Package for Surface Topography Analysis
Authors: Giura Andrea , Zucco Massimo , Ribotta Luigi
Published: December 2024

Surface metrology deals with inspecting surfaces and profiles by using contact or non-contact profilometers. In this field, the characterization of the dimensional, morphological, and texture parameters of samples as well as the assessment of metrological characteristics of measuring instruments are key issues. Manufacturers of instruments provide commercial software tools to analyze topography data. There are also freely available tools, including open-source options, that provide a variety of algorithms and methods. The rapid growth of investigations aimed at better understanding the effects of the microscale phenomena requires the improved traceable calibration of samples, the development of new methodologies and measuring techniques, and the specification of new mathematical models and processing techniques. In this work, we present SurfILE, the launch of an open-source Python project that provides various procedures and algorithms for topography analysis. The open-source software presented in this article is intended to be modular, expandable, and customizable.
Genomic Insights into Vibrio parahaemolyticus from Southern Korea: Pathogenicity, Antimicrobial Resistance, and Phylogenetic Distinctions
Authors: Zin Hyunwoo , Lim Jaewon , Shin Younhee , Kim Byeori , Yoon Minchul , Ha Kwangsoo , Cho Sunghyun
Published: December 2024

Vibrio parahaemolyticus, a significant cause of gastroenteritis and a growing public health concern, has become increasingly prevalent owing to the rise in ocean temperatures driven by climate change. This study aimed to characterize the genetic diversity, pathogenic potential, and antimicrobial resistance (AMR) profiles of V. parahaemolyticus strains isolated from the southern coastal region of Korea. Using whole genome sequencing (WGS) and advanced bioinformatics tools, we identified novel sequence types through multilocus sequence typing and serotyped isolates using the VPsero database. Pathogenic genes, such as tdh and trh, were detected in only a few isolates, suggesting the involvement of alternative virulence mechanisms in the pathogenicity of these strains. An in silico analysis revealed widespread AMR, particularly against beta-lactams, chloramphenicol, and tetracycline antibiotics, underscoring the public health threats posed by these strains. A phylogenetic analysis revealed no significant clustering by geographic origin, year, or strain source, although most clinical and environmental strains were not closely related at lower phylogenetic branches. These findings highlight the importance of continued genomic surveillance and strict regulations regarding antibiotic use in marine environments. Moreover, this study suggests that integrating WGS data with epidemiological models could enhance the prediction of the emerging virulent strains and support effective outbreak management strategies.
Wild-Mouse-Derived Gut Microbiome Transplantation in Laboratory Mice Partly Alleviates House-Dust-Mite-Induced Allergic Airway Inflammation
Authors: Islam Md Zohorul , Jozipovic Danica , Lopez Pablo Atienza , Krych Lukasz , Correia Banny Silva Barbosa , Bertram Hanne Christine , Hansen Axel Kornerup , Hansen Camilla Hartmann Friis
Published: December 2024

Laboratory mice are instrumental for preclinical research but there are serious concerns that the use of a clean standardized environment for specific-pathogen-free (SPF) mice results in poor bench-to-bedside translation due to their immature immune system. The aim of the present study was to test the importance of the gut microbiota in wild vs. SPF mice for evaluating host immune responses in a house-dust-mite-induced allergic airway inflammation model without the influence of pathogens. The wild mouse microbiome reduced histopathological changes and TNF-α in the lungs and serum when transplanted to microbiota-depleted mice compared to mice transplanted with the microbiome from SPF mice. Moreover, the colonic gene expression of Gata3 was significantly lower in the wild microbiome-associated mice, whereas Muc1 was more highly expressed in both the ileum and colon. Intestinal microbiome and metabolomic analyses revealed distinct profiles associated with the wild-derived microbiome. The wild-mouse microbiome thus partly reduced sensitivity to house-dust-mite-induced allergic airway inflammation compared to the SPF mouse microbiome, and preclinical studies using this model should consider using both ‘dirty’ rewilded and SPF mice for testing new therapeutic compounds due to the significant effects of their respective microbiomes and derived metabolites on host immune responses.
Low Reproductivity of Giant Pandas May Be Associated with Increased Vaginal Escherichia-Shigella
Authors: Wu Wei , Xue Fei , Huang Chong , Zhou Yanshan , Lan Guanwei , Bi Wenlei , Liu Jiabin , Yu Xiang , Li Zusheng , Zhang Long , Feng Feifei , Gu Jiang , Ma Rui , Qi Dunwu
Published: December 2024

The poor reproductive capacity of giant pandas significantly hinders the development of captive populations, with 80.88% of adult individuals being unable to successfully become pregnant and deliver offspring. The disturbance of vaginal microbiota has been proven to potentially lead to miscarriage, abortion, and stillbirth in mammals. To elucidate the potential relationship between the vaginal microbiota and the reproductive capacity of giant pandas, we performed high-throughput sequencing of vaginal microbiota at the time of fertilization and conducted comparative analyses based on different pregnancy outcomes. We found that the microbial diversity in the delivery (D) group exceeded that in the non-delivery (ND) group and the vaginal microbial community structure was statistically different between the two groups. The vaginal microbiota in the delivery pandas consisted of unclassified Pseudomonadaceae which was gradually replaced by the Escherichia-Shigella type of vaginal microbiota in the ND group. A function predictions analysis showed that infectious disease, glycan biosynthesis, and metabolism were significantly enriched in the ND group. Additionally, an analysis of the microbial community phenotypic categories indicated that the ND group exhibited a significantly higher abundance of Gram-negative bacteria, facultative anaerobes, potential pathogens, and stress-tolerant species compared to the D group, predominantly driven by the elevated abundance of Escherichia-Shigella. Escherichia-Shigella can be used within LDA and ROC analyses to diagnostically distinguish the vaginal microflora associated with bad pregnancy outcomes during estrus. Our results will help to identify potential pathogens causing reproductive tract diseases, reduce the number of reproductive tract disease infections in pandas, and increase the birth rate of giant pandas in conservation breeding programs.
Locust Pathogen Aspergillus oryzae XJ1 Is Different from Aspergillus oryzae and Aspergillus flavus Based on Genomics Comparisons
Authors: You Yinwei , Xu Xiao , Liu Hui , Zhang Long
Published: December 2024

Fungi play an increasingly important role in the biological control of insect pests. Aspergillus oryzae XJ1 is highly virulent to locust adults and nymphs, which are a destructive economic pest worldwide. Because of its host association with locusts, which is unique in Aspergillus, in this study, we examined the genetic relationships of A. oryzae XJ1 within Aspergillus. We sequenced the genome of A. oryzae XJ1 and compared it with the genomes of other Aspergillus species. The complete genome of A. oryzae XJ1 is 37.9 Mb, comprising 11,720 putative genes, assembled into eight chromosomes. The genome size is similar to that of other A. oryzae strains. Phylogenomic analysis indicated that A. oryzae XJ1 was most closely related to A. flavus NRRL3357, not A. oryzae RIB40. Core/pan-genome analysis of A. oryzae XJ1 and other Aspergillus species revealed that A. oryzae XJ1 had 704 strain-specific genes, whereas A. flavus NRRL3357, A. oryzae KDG 21, and A. parasiticus NRRL 2999 had 646, 955, and 779 unique genes, respectively. The A. oryzae XJ1 genome showed structural differences compared with the genomes of A. oryzae RIB40 and A. flavus NRRL3357 in genomic synteny analysis. These results indicate that A. oryzae XJ1 is genetically distinct at the genome level from other Aspergillus species, including A. oryzae and A. flavus, and may be as a distinct species. This will provide new insight into the classification of Aspergillus based on genomics.
The Association of Blood Eosinophils and Neutrophils Expressing Eosinophilic Surface Markers with the Severity and Outcome of COVID-19
Authors: Wang Jun , Li Xin , Ren Jiaqi , Rao Yafei , Qiao Yixian , Sun Lina , Liang Ying , Chang Chun , Zhou Qingtao , Sun Yongchang
Published: December 2024

(1) Background: The implication of type 2 (T2) inflammatory response in COVID-19 remains controversial. This study aimed to evaluate the association of eosinophils, neutrophils expressing eosinophilic surface markers and T2 cytokines with the severity and outcome of COVID-19. (2) Methods: Patients who were admitted to hospital due to COVID-19 from 18 December 2022 to 31 January 2023 were enrolled. Peripheral blood WBC and differentials, T2 cellular markers (subsets of eosinophils and neutrophils expressing eosinophilic surface markers) and cytokines at admission were measured and compared between subjects with different disease severities and outcomes. (3) Results: Ten mild-to-moderate and 22 severe-to-very severe cases were enrolled for analysis. Of these patients, seven died of severe-to-very severe disease. The severe-to-very severe patients showed a higher number of neutrophils, but lower numbers of eosinophils, lymphocytes cells and neutrophils expressing eosinophilic surface markers. Similarly, deceased cases were also characterized by increased neutrophils, but decreased eosinophils and neutrophils expressing eosinophilic surface markers. The levels of T2 cytokines failed to demonstrate a significant correlation with the severity or outcome of COVID-19. (4) Conclusions: Eosinophils and neutrophils expressing eosinophilic surface markers were associated with milder disease and better outcomes of COVID-19, suggesting that a T2 inflammatory response may confer a potential protective effect against the disease.
Gastrointestinal Shedding of Rubulaviruses from Egyptian Rousette Bats: Temporal Dynamics and Spillover Implications
Authors: Muvengi Tauya S. , Mortlock Marinda , Kain Morgan P. , Markotter Wanda
Published: December 2024

Bats are recognized as reservoirs for diverse paramyxoviruses, some of which are closely related to known human pathogens or directly implicated in zoonotic transmission. The emergence of the zoonotic Sosuga virus (SOSV) from Egyptian rousette bats (ERBs), which caused an acute febrile illness in a reported human case in Africa, has increased the focus on the zoonotic potential of the Rubulavirinae subfamily. Previous studies identified human parainfluenza virus 2 (HPIV2)- and mumps (MuV)-related viruses in ERBs from South Africa, with HPIV2-related viruses restricted to gastrointestinal samples, an underexplored target for rubulavirus biosurveillance, suggesting that sample-type bias may have led to their oversight. To address this, we performed a longitudinal analysis of population-level fecal samples from an ERB maternity roost for rubulavirus RNA, employing a broadly reactive hemi-nested RT-PCR assay targeting the polymerase gene. We detected HPIV2- and MuV-related viruses in addition to numerous pararubulaviruses, highlighting significant viral diversity. Temporal analysis of three major clades revealed peaks in rubulavirus shedding that correlated with seasonal environmental changes and host reproductive cycles, although shedding patterns varied between clades. These findings identify specific periods of increased risk for the spillover of bat-associated rubulaviruses to humans, providing critical information for developing targeted mitigation strategies to minimize zoonotic transmission risk within the local community.
Forensic Aspects of Designer LSD Analogs Identification by GC–MS (EI) and UV Spectroscopy
Authors: Tusiewicz Kaja , Wachełko Olga , Zawadzki Marcin , Szpot Paweł
Published: December 2024

Lysergic acid diethylamide (LSD) analogs, often referred to as new psychoactive substances, are synthesized to mimic controlled substances while evading drug regulations. This study emphasizes the challenges of identifying these compounds, particularly their isomeric forms. Gas chromatography–mass spectrometry (GC–MS) and UV spectroscopy were employed to analyze 13 LSD analogs. The effects of different solvents on the detection of these analogs were analyzed, demonstrating that solvents like diethyl ether, tert-butyl methyl ether, dichloromethane and acetone provided the best sensitivity and stability. Methanol, on the other hand, causes alcoholysis of many LSD analogs, which may lead to false results. Additionally, effective chromatographic separation of isomers was established, including LSD, MiPLA, LAMPA, 1P-LSD and 1P-MiPLA, as well as 1cP-LSD and 1cP-MiPLA, which is crucial for accurate identification. The elution order of the determined compounds with the use of developed chromatographic method was as follows: LSD, MiPLA, LAMPA, AL-LAD, LSZ, 2-Br-LSD, ALD-52, 1P-LSD, 1P-MiPLA, 1B-LSD, 1V-LSD, 1cP-LSD and 1cP-MiPLA. Differences in ion ratios observed in mass spectrometry (MS) were also analyzed to distinguish between closely related compounds. Several key ions for LSD analogs were able to be identified, including 221, 208, 207, 196, 194, 192, 181, 167, 154, 152 and 128 m/z. In analogs with an N-diethyl group (or variants like N-methyl-propyl in LAMPA or N-methyl-isopropyl in MiPLA), mass spectra showed fragments 100, 72 and 58 m/z. For LSZ, the cyclic group at R1 produces ions 98 and 70 m/z. Analogs with an N6 allyl group (e.g., AL-LAD) show a characteristic ion 247 m/z. This method allows for the correct differentiation of structural isomers based on their unique ion fragmentation patterns and relative intensities. UV spectroscopy was used as a supplementary tool for screening, though it has limitations in analyzing complex mixtures. This work contributes to the forensic identification of designer LSD analogs, ensuring reliable detection for legal and toxicological investigations.
Characterization of Walnut Oil and Evaluation of Its Neuroprotective Effects in an In Vitro Model of Parkinson’s Disease
Authors: Filaferro Monica , Avallone Rossella , Rustichelli Cecilia , Vitale Giovanni
Published: December 2024

Parkinson’s disease (PD) is a common neurodegenerative disorder marked by the degeneration of dopaminergic neurons and the buildup of α-synuclein aggregates. The current treatments focus on symptom relief, with no drugs available to halt disease progression. This has prompted interest in plant-based extracts as alternative therapies. This study examines the neuroprotective and antioxidant effects of walnut oil (WO), extracted from Juglans regia L., in an in vitro PD model using the neurotoxin rotenone (ROT). WO, rich in polyunsaturated fatty acids (PUFAs), including linoleic acid (LA) and α-linolenic acid (ALA), together with minor bioactive components, is known for its neuroprotective properties. Using human HMC3 microglial and SH-SY5Y neuroblastoma cells, we tested WO’s effects on ROT-induced toxicity. The experiments were performed at different time points. The results showed that the co-administration of WO with ROT significantly improved cell viability and reduced reactive oxygen species (ROS) levels. Additionally, conditioned media from WO-treated HMC3 cells enhanced SH-SY5Y cell survival, indicating positive microglia–neuron interactions. Cell viability appeared to be concentration- and time-dependent. These findings highlight WO’s potential, mainly due to its PUFA content, as a promising candidate for preventing neurodegenerative diseases like PD; they underscore the potential of WO content in food for the prevention of neurodegenerative diseases such as PD.
Novel Hierarchical Disordered Li- and Al-KIL-2 Catalysts for the Pyrolysis of Biomass Model Compounds and Wool Waste: A Comparison with ZSM-5
Authors: Kalateh Roozbeh , Aysu Tevfik , Ojeda Manuel , Sanna Aimaro
Published: December 2024

In this study, we investigated the pyrolysis of cellulose, lignin, phenylalanine and textile wool waste using microscale thermogravimetric analysis (TGA) and a gram-scale fixed bed reactor. The pyrolysis was conducted at 500 °C and 1 bar N2, using Al- and Li-doped mesoporous KIL-2 and ZSM-5 catalysts for comparison. Our results show that amorphous Al-KIL-2 catalyst was the most efficient in producing aromatics from cellulose and lignin. This efficiency is attributed to Al-KIL-2 large mesoporosity, wide pore size distribution, and mild acid sites. Additionally, Al-KIL-2 promoted esterification and denitrogenation reactions, indicating its potential application in the pyrolysis of biomass and protein-rich feedstocks. Conversely, the Li-KIL-2 catalyst demonstrated activity primarily in the depolymerisation of cellulose to sugars and promoted ketonisation and alcohol formation. In summary, our findings indicate that Al-KIL-2 is a promising catalyst for efficient aromatic production from biomass.
Effect of Gold Nanoparticles on Luminescence Enhancement in Antibodies for TORCH Detection
Authors: Chen Cuimei , Ding Ping
Published: December 2024

Purposes: To explore the optimization method and application of Au-NP-enhanced luminol––H2O2 luminescence system in TORCH (TOX, RV, CMV, HSVI, and HSVII) detection. Method: 4.5 × 10−5 mmol/L gold nano solution was prepared with chloroauric acid as the reducing agent and trisodium citrate as the stabilizer. After curing for 3 days, Au NPs participate in the luminal–H2O2 luminescence system to detect TORCH antibodies and establish the cut off value. SPSS 18.0 software was used to analyze the TORCH antibodies detected by the nano-gold-enhanced luminol luminescence method and TORCH kit. Additionally, its detection performance is studied. Results: The results of a paired t-test for the absorbance values of samples with and without gold nanoparticles showed that there were statistically significant differences (p < 0.001) between the two methods in the detection of TOX, RV, CMV, HSVI, and HSVII. The luminescence values with the addition of gold nanoparticles were significantly higher than those without gold nanoparticles. Using the Au NP–luminol–H2O2 chemiluminescence method, 127 serum samples were tested for TORCH antibodies. The sensitivities were 84.6%, 83.3%, 90.9%, 85.7%, and 84.6%, while the specificities were 94.7%, 96.5%, 96.6%, 97.3%, and 95.6%, respectively. The sensitivity and specificity of the chemiluminescence method enhanced by gold nanoparticles are significantly improved compared to the chemiluminescence method without enhancers. Conclusions: Au NPs participate in the luminal–H2O2 luminescent system. The absorbance, sensitivity, and specificity of TORCH antibodies show that Au NPs can enhance the luminol–H2O2 luminescent system. Au NP–luminol–H2O2 luminescence system has broad application prospects in the detection of eugenics.
Hollow Biomass Adsorbent Derived from Platanus Officinalis Grafted with Polydopamine-Mediated Polyethyleneimine for the Removal of Eriochrome Black T from Water
Authors: Jiang Zefeng , Song Tongyang , Huang Bowen , Qi Chengqiang , Peng Zifu , Wang Tong , Li Yuliang , Ye Linjing
Published: December 2024

Platanus officinalis fibers (PFs) taking advantage of high-availability, eco-friendly and low-cost characteristics have attracted significant focus in the field of biomaterial application. Polyethyleneimine grafted with polydopamine on magnetic Platanus officinalis fibers (PEI-PDA@M-PFs) were prepared through a two-step process of mussel inspiration and the Michael addition reaction, which can work as an effective multifunctional biomass adsorbent for anionic dye with outstanding separation capacity and efficiency. The as-prepared PEI-PDA@M-PFs possess desirable hydrophilicity, magnetism and positive charge, along with abundant amino functional groups on the surface, facilitating efficient adsorption and the removal of Eriochrome Black T (EBT) dyes from water. In addition to the formation mechanism, the adsorption properties, including adsorption isotherms, kinetics, and the reusability of the absorbent, were studied intensively. The as-prepared PEI-PDA@M-PFs achieved a theoretical maximum adsorption capacity of 166.11 mg/g under optimal conditions (pH 7.0), with 10 mg of the adsorbent introduced into the EBT solution. The pseudo-second-order kinetic and Langmuir models were well matched with experimental data. Moreover, thermodynamic data ΔH > 0 revealed homogeneous chemical adsorption with a heat-absorption reaction. The adsorbent remained at high stability and recyclability even after five cycles of EBT adsorption processes. These above findings provide new insights into the adsorption processes and the development of biologic material for sustainable applications.
Innovative and Interactive Technologies in Creative Product Design Education: A Review
Authors: Nazlidou Ioanna , Efkolidis Nikolaos , Kakoulis Konstantinos , Kyratsis Panagiotis
Published: December 2024

When discussing the Education 4.0 concept and the role of technology-based learning systems along with creativity, it is interesting to explore how these are reflected as educational innovations in the case of design education. This study aims to provide an overview of interactive technologies used in product design education and examine their integration into the learning process. A literature search was conducted, analyzing scientific papers to review relevant articles. The findings highlight several categories of technologies utilized in design education, including virtual and augmented reality, robotics, interactive embedded systems, immersive technologies, and computational intelligence systems. These technologies are primarily integrated as supportive tools throughout different stages of the design process within learning environments. This study suggests that integrating such technologies alongside pedagogical methods positively impacts education, offering numerous opportunities for further research and innovation. In conclusion, this review contributes to ongoing research in technological advancements and innovations in design education, offering insights into the diverse applications of interactive technologies in enhancing learning environments.
A Graphene-Based Bioactive Product with a Non-Immunological Impact on Mononuclear Cell Populations from Healthy Volunteers
Authors: Lavín-López María del Prado , Torres-Torresano Mónica , García-Cuesta Eva María , Soler-Palacios Blanca , Griera Mercedes , Martínez-Rovira Martín , Martínez-Rovira José Antonio , Rodríguez-Puyol Diego , de Frutos Sergio
Published: December 2024

We previously described GMC, a graphene-based nanomaterial obtained from carbon nanofibers (CNFs), to be biologically compatible and functional for therapeutic purposes. GMC can reduce triglycerides’ content in vitro and in vivo and has other potential bio-functional effects on systemic cells and the potential utility to be used in living systems. Here, immunoreactivity was evaluated by adding GMC in suspension at the biologically functional concentrations, ranging from 10 to 60 µg/mL, for one or several days, to cultured lymphocytes (T, B, NK), either in basal or under stimulating conditions, and monocytes that were derived under culture conditions to pro-inflammatory (GM-MØ) or anti-inflammatory (M-MØ) macrophages. All stirpes were obtained from human peripheral mononuclear cells (PBMCs) from anonymized healthy donors. The viability (necrosis, apoptosis) and immunological activity of each progeny was analyzed using either flow cytometry and/or other analytical determinations. A concentration of 10 to 60 µg/mL GMC did not affect lymphocytes’ viability, either in basal or active conditions, during one or more days of treatment. The viability and expression of the inflammatory interleukin IL-1β in the monocyte cell line THP-1 were not affected. Treatments with 10 or 20 µg/mL GMC on GM-MØ or M-MØ during or after their differentiation process promoted phagocytosis, but their viability and the release of the inflammatory marker activin A by GM-MØ were not affected. A concentration of 60 µg/mL GMC slightly increased macrophages’ death and activity in some culture conditions. The present work demonstrates that GMC is safe or has minimal immunological activity when used in suspension at low concentrations for pre-clinical or clinical settings. Its biocompatibility will depend on the dose, formulation or way of administration and opens up the possibility to consider GMC or other CNF-based biomaterials for innovative therapeutic strategies.
Immediate Effects of Distinct Intensities of Transcutaneous Spinal Direct Current Stimulation on Chronic Pain: A Randomized Controlled Trial
Authors: Ferreira Kariny Realino do Rosário , Macedo Maria de Cássia Souza , Alves Ana Luiza Guimarães , Esquírio Arthur Ferreira , Botim Bianca Rossi , Jacob Gabrielly Souza , dos Santos Mayra Evelise Cunha , Gama Gabriela Lopes , Barbosa Michelle Cristina Sales Almeida , Barbosa Alexandre Wesley Carvalho
Published: December 2024

This study aimed to assess the immediate effects of transcutaneous spinal direct current stimulation (tsDCS) on pain outcomes, measured using the visual analog scale (VAS) and pressure pain thresholds in a cohort of 55 participants experiencing chronic pain using a controlled, randomized trial with 55 participants allocated into 2 groups: 2 mA and 0.5 mA of tsDCS for 20 min. Anodal stimulation was applied on the 12th thoracic vertebra, with the cathode positioned on the 7th cervical vertebra. Pain outcomes were assessed before and post intervention using the VAS and pressure algometry. Between- and within-group differences, along with chi-square tests, were used to determine the differences and responsiveness. Significance was established at p < 0.05. Findings showed significant temporal effects for both VAS (p < 0.001) and pressure algometry (p = 0.04). However, no between-group differences were noted for the time × group factor for VAS (p = 0.46) and pressure algometry (p = 0.78). No significant between-group differences were observed for the responsiveness analysis. The results indicate that a single 20-min session of 2 and 0.5 mA tsDCS improves pain scores for both intensities equally. However, there were no statistically significant between-group differences in pain perception or pressure pain threshold.
Self-Adaptive Moving Least Squares Measurement Based on Digital Image Correlation
Authors: Zhu Hengsi , Guo Yurong , Tan Xiao
Published: December 2024

Digital image correlation (DIC) is a non-contact measurement technique used to evaluate surface deformation of objects. Typically, pointwise moving least squares (PMLS) fitting is applied to process the noisy data from DIC to obtain an accurate strain field. In this study, a self-adaptive pointwise moving least squares (SPMLS) method was developed to optimize the process of window size selection, thereby attaining superior accuracy in measurements. The premise of this method is that the noise in the displacement field follows white Gaussian noise. Under this assumption, it analyses the random errors and systematic errors of the PMLS method under different calculation window sizes. The optimal size of the calculation window is determined by minimizing the errors. Subsequently, the strain field is computed based on the optimized calculation window. The results were compared with a typical PMLS method. Whether calculating low-gradient strain fields or high-gradient strain fields, the computational accuracy of SPMLS is close to the optimal accuracy of PMLS. This study effectively addresses the inherent challenge of manually selecting window size in the PMLS method.
Assessment of the Utilization of Sodium–Glucose Cotransporter-2 Inhibitors in Patients Without Diabetes
Authors: Koinuma Takuma , Yoshida Manato , Akazawa Manabu
Published: December 2024

Background: Sodium–glucose cotransporter-2 inhibitors (SGLT2Is) have demonstrated effects beyond glucose-lowering, leading to their approval for treating chronic heart failure (HF) in Japan. This study examines prescription trends for SGLT2Is in patients with diabetes versus those without diabetes, focusing on their backgrounds and HF treatment status of patients without diabetes who received SGLT2I after an HF diagnosis. Methods: Using data from DeSC Healthcare Inc., we analyzed patients aged 65 and above who received their first SGLT2I prescription between October 2014 and February 2023. Patients were classified into SGLT2I-treated diabetic and non-diabetic groups. We analyzed the annual prescription trends and compared the characteristics of both groups who started SGLT2I between 2022 and 2023. Additionally, we assessed the timing of SGLT2I initiation and the use of concomitant HF treatment in patients without diabetes after HF diagnosis. Results: The proportion of patients without diabetes receiving their first SGLT2I prescription has increased since 2021. Patients without diabetes receiving SGLT2Is were older, likely owing to aging-related diseases. In patients without a confirmed diabetes diagnosis, SGLT2I was most frequently initiated at the time of HF diagnosis. Mineralocorticoid receptor antagonists (MRAs) are the most common concomitant HF medications. The increase in SGLT2I prescriptions for patients without diabetes receiving SGLT2I since 2021, particularly in older individuals, suggests that SGLT2I is being initiated either at the time of HF diagnosis or in a stepwise manner. Conclusion: In Japan, MRA is commonly used as a concomitant medication in patients without diabetes receiving SGLT2I.
Object Recognition in Foggy and Hazy Conditions Using Dark Channel Prior-Based Fringe-Adjusted Joint Transform Correlator
Authors: Mohapatra Jyoti Bikash , Nishchal Naveen K. , Monikantan Jyothish
Published: December 2024

Extreme weather conditions like fog and haze present substantial challenges to object recognition systems. Reduced visibility and contrast degradation significantly affect the auto-correlation process, often leading to failure in object recognition. To address this critical issue and to make object recognition accurate and invincible, we propose a hybrid digital–optical correlator specifically designed to perform under adverse weather conditions. This approach integrates the dark channel prior (DCP) with the fringe-adjusted joint transform correlator (FJTC), promising significant potential to enhance the robustness of the object recognition process under challenging environmental conditions. The proposed scheme presents a unique and alternative approach for object recognition under bad weather conditions. The incoming input scenes are processed with the DCP, enabling the FJTC to perform optical correlation on the refined images. The effectiveness of the proposed method is evaluated using several performance metrics like the structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), correlation peak intensity (CPI), processing time, and recognition accuracy. To validate the performance of the proposed study, numerical simulation along with hybrid digital–optical demonstrations have been conducted.
Substituent Effects on the Photophysical Properties of a Series of 8(meso)-Pyridyl-BODIPYs: A Computational Analysis of the Experimental Data
Authors: Bobadova-Parvanova Petia , Goliber Dylan , Hernandez Elijuah , LaMaster Daniel , Vicente Maria da Graça H.
Published: December 2024

Recently, a series of 8(meso)-pyridyl-BODIPYs (2-pyridyl, 3-pyridyl, and 4-pyridyl) and their 2,6-substituted derivatives were synthesized and their structure and photophysical properties were studied both experimentally and computationally. One of the main observed trends was that the 2-pyridyl-BODIPYs were consistently less fluorescent than their 3-pyridyl and 4-pyridyl analogs, regardless of the 2,6-substituents. Herein, we extend our previous computational studies and model not only the ground but also the excited states of the entire series of previously synthesized meso-pyridyl-BODIPYs with the aim of explaining the observed differences in the emission quantum yields. To better understand the trends and the effect of 2- and 2,6-substitution on the photophysical and electron-density-related properties, we also model the ground and excited states of BODIPYs that were not synthesized experimentally, however represent a logical part of the series. We calculate a variety of molecular properties and propose that the experimentally observed low quantum yields for all 2-pyridyl-BODIPYs could be due to the very flat potential energy surfaces with respect to the rotation of the 2-pyridyl ring in the excited states, and the stability of a non-planar and significantly less fluorescent meso-2-pyridyl-BODIPY structure.
Experimental and Numerical Simulation of Flow Modes in Flow Focusing/Blurring Nozzle
Authors: Fu Juan , Ye Zhenhuan , Zhao Jin
Published: December 2024

The flow mode of the flow focusing/blurring nozzle was studied through experimental and numerical simulation methods. The experimental results indicate that the flow mode of the nozzle can be classified into flow focusing, transition, and flow blurring based on the location of the liquid jet breakup. Numerical simulation studies have found that the transformation of flow mode is mainly related to viscous shear force, gas pressure on the jet surface, and liquid inertia force. The increase in the gas flow rate changes the flow mode by affecting the viscous shear force. The increase in the liquid flow rate changes the flow mode by affecting the liquid inertial force. When the liquid flow rate is high, the increase in the liquid flow rate affects the flow mode by affecting the gas pressure on the jet surface. The study also found that excessive gas flow rates can hinder the flow of liquid inside the nozzle, while excessive liquid flow rates can hinder the breakup of liquid inside the nozzle. Therefore, the normal operation of the flow focusing/blurring nozzle requires ensuring that the gas and liquid flow rates are within the normal range.
A Review of Intelligentization System and Architecture for Ultra-Precision Machining Process
Authors: Pan Minghua , Zhang Guoqing , Zhang Wenqi , Zhang Jiabao , Xu Zejiang , Du Jianjun
Published: December 2024

The intelligence of ultra-precision machining processes has become a research focus in the field of precision and ultra-precision manufacturing. Scholars have conducted some fragmented studies on the intelligence of ultra-precision machining processes; however, a systematic review and summary of the intelligent systems and architectures for such processes are still lacking. Therefore, this paper is devoted to reviewing the intelligent systems and architectures for ultra-precision machining processes, focusing on three aspects: machining environment monitoring, cutting process analysis, and intelligent machining system frameworks. The paper first provides an overview of environmental intelligence monitoring from the perspective of the machining environment and then discusses and summarizes monitoring processes, such as tool errors, tool wear, tool setting, and surface measurement, from the perspective of machining process analysis. The intelligent machining system framework is then analyzed and summarized from the perspective of process control. Finally, the paper outlines the overall framework of the intelligent system for ultra-precision machining processes and analyzes its components. This paper provides guidance for the development of intelligent systems in ultra-precision machining processes.
Research on Oscillation Suppression Control Method for Contact Scanning Motion
Authors: Wang Bin , Shu Panfeng , Wang Haibin
Published: December 2024

Contact scanning sensors play a crucial role in certain detection equipment, enabling the precise identification and detection of structural degradation to effectively mitigate risks. However, these sensors face a challenge: during high-speed scanning, vibrations can occur due to surface unevenness and friction. These vibrations not only compromise the scanning accuracy but also expedite sensor wear and tear. To address this issue, this study introduces a control strategy. By precisely regulating the actuator’s output, we aim to adjust the sensor’s motion, minimizing vibrations and enhancing the detection system’s stability and accuracy. Simulation results demonstrate that this strategy significantly improves scanning quality and reduces vibrations, validating its effectiveness. These findings pave the way for future research and technological applications.
HAIPO: Hybrid AI Algorithm-Based Post-Fabrication Optimization for Modern 3D NAND Flash Memory
Authors: Kim Myungsuk
Published: December 2024

To successfully meet the various requirements of modern storage systems, NAND flash memory should be highly optimized by precisely tuning a huge number of internal operating parameters. Although 3D NAND flash memory succeeds in increasing the capacity of storage systems, its complex architecture and unique error behavior make such optimization a more difficult and time-consuming process during NAND manufacturing. In this paper, we introduce HAIPO, a novel methodology for post-fabrication optimization of NAND flash memory, which is an essential step in the manufacturing process of modern 3D NAND flash memory to simultaneously meet various requirements on reliability, performance, yield, etc. HAIPO is based on simple machine-learning approaches that consist of (i) a lightweight deep-learning (DL) model to generate initial device parameters and (ii) an evolutionary algorithm (EA) to explore device parameters automatically. To more effectively explore device parameters, we introduce three key guidelines for each generation in the EA: (1) domain-specific rules, (2) recent optimization results, and (3) online Bayesian simulation, respectively, to enable quick optimization for a huge number of device parameters within the limited product turnaround time (TAT). In addition, we integrate two optimization modules with HAIPO to improve optimization efficiency even in environments with severe process variation. We demonstrate the feasibility and effectiveness of HAIPO using real 320 3D TLC/QLC NAND flash chips, showing significant performance and reliability improvements by up to 8.8% and 12% on average, respectively, within a quite limited optimization TAT.