bluuebunny/crossref_metadata_2025 huggingface dataset:
Textile Characteristics, Medullation, and Colorimetry of Wool Fiber Dyed with Dactylopius coccus Using Atmospheric Pressure Plasma Jet (APPJ)
Authors: Quispe-Quispe Arturo , Lozano Franklin , Machaca-Machaca Virgilio , Quispe-Marcatoma Justiniano
Published: January 2025

The industrial and artisanal textile industries necessitate the adoption of sustainable dyeing practices. Although the natural dye derived from Dactylopius coccus presents a viable option, its traditional application requires metallic mordants that pose environmental and health risks. This study investigates the utilization of atmospheric-pressure plasma jet (APPJ) technology for dyeing wool with Dactylopius coccus dye, with the objective of optimizing the process and minimizing its environmental impact. The APPJ technique was employed for wool dyed with Dactylopius coccus dye, and the textile properties, medullation, and colorimetry were evaluated using an optical fiber diameter analyzer (OFDA) and a spectrometer with an integrating sphere. The results demonstrated that the APPJ enhanced the color intensity and uniformity, facilitating improved dye penetration into the fibers. Plasma treatment darkened the fiber, generated reddish and yellowish tones, and increased the color saturation and intensity. The wool samples treated with plasma exhibited an increase in DMF and SF but a decrease in IC and greater size variability. The APPJ reduces total medullation in wool dyed with cochineal dye. In conclusion, the APPJ was demonstrated to be a promising method for dyeing wool with Dactylopius coccus dye, offering an effective and sustainable alternative to traditional methods, with enhanced color vibrancy and uniformity and reduced resource utilization.
The Adducts Lipid Peroxidation Products with 2′-DeoxyNucleosides: A Theoretical Approach of Ionisation Potential
Authors: Karwowski Boleslaw T.
Published: January 2025

The human body contains ~1014 cells—each of which is separated by a lipid bilayer, along with its organeller. Unsaturated fatty acids are located on the external layer and, as a result, are particularly exposed to harmful factors, including xenobiotics and ionising radiation. During this activity, lipid peroxidation products are generated, e.g., 4-hydroxy-2-nonenal (HNA), 4-oxo-2(E)-nonenal (ONE), and malondialdehyde (MDA). The mentioned aldehydes can react with cytosolic 2′-deoxynucleosides via Michael addition. In this paper, the following adducts have been taken into theoretical consideration: ε-dCyt, H-ε-dAde, ε-dCyt, H-ε-dAde, H-ε-dGua, R/S-OH-PdGua, N2,3-ε-dGua, M1-dGua, N1-ε-dGua, and HNE-dGua. The presence of the above molecules can alter a cell’s antioxidant pool. With this in mind, the adiabatic ionisation potential (AIP) and vertical ionisation potential (VIP), as well as the spin and charge distributions, are discussed. For this purpose, DFT studies were performed at the M06-2x/6-31++G** level of theory in the aqueous phase (both non-equilibrated (NE) and equilibrated (EQ) solvent–solute interaction modes), together with a Hirshfeld charge and spin distribution analysis. The obtained results indicate that the AIPs of all the investigated molecules fell within a range of 5.72 and 5.98 eV, which is consistent with the reference value of 7,8-dihydro-8-oxo-2′-deoxyguanosine (OXOdGua), 5.78 eV. N2,3-ε-dGua and M1-dGua were the only exceptions, whose VIP and AIP were noted as higher. The electronic properties analysis of 2′-deoxynucleoside adducts with lipid peroxidation products reveals their potential influence on the cells’ antioxidant pool, whereby they can affect the communication process between proteins, lipids, and nucleotides.
The Influence of Air Flow Rates and Voltage on the Plasma Emission Spectra and the Concentrations of Nitrogen Oxides Produced by Gliding Arc Discharge Plasma
Authors: Marcinauskas Liutauras , Uscila Rolandas , Aikas Mindaugas
Published: January 2025

In this work, gliding arc discharge (GAD) was used to produce air plasma and investigate the influence of the discharge parameters on the composition of the air plasma, vibrational temperatures, and the production of NOx. It was demonstrated that the main particles obtained in the GAD air plasma were N2*, N2+, N+, NOγ, and O. It was observed that the reduction in the discharge frequency increased the intensity of the excited nitrogen molecules lines and reduced the nitric oxide (NO) and nitrogen dioxide (NO2) gas concentrations. The increase in the output voltage prolonged the duration of arc discharge and enhanced the intensities of the emission lines of the N2+, O, and NOγ species and the concentrations of NO and NO2 gasses. It was shown that the increase in the air flow rate from 6.7 L/min to 15.6 L/min decreased the concentration of the produced NO gas by 24%. Additionally, the line intensities of all main species in air plasma were enhanced. Studies have shown that the NO and NO2 gas concentrations (selectivity of NO and NO2) can be controlled by varying the air flow, output voltage, and discharge frequency. The highest NOx concentration of 2380 ppm was produced at 250 V, when the direct air flow was 11.2 L/min.
Self-Compacting Concrete with Artificial Lightweight Aggregates from Sugarcane Ash and Calcined Scheelite Mining Waste
Authors: Sousa Jemima Tabita F. de , Anjos Marcos Alyssandro S. dos , Neto José Anselmo da S. , Farias Evilane C. de , Branco Fernando G. , Maia Pederneiras Cinthia
Published: January 2025

Self-compacting concrete (SCC) is a relevant technology and an alternative to conventional concrete in complex structures due to its exceptional workability. The rheological parameters demonstrated by SCC provide high fluidity and cohesion, resulting in high mould-filling capability and segregation resistance, as well as optimising concreting processes and reducing costs. In view of this, self-compacting lightweight concrete (SCLC) has emerged as a possible alternative as it combines the benefits of SCC and lightweight aggregate concrete (LWAC). In the production of LWC, the most widely used lightweight aggregate in the world, and also in Brazil, is still expanded clay; however, Brazilian production is restricted to the southeast region. In this context, previous studies have verified the feasibility of producing lightweight aggregates from the sintering of industrial waste and regional raw materials (Rio Grande do Norte/Brazil), such as sugarcane bagasse ash (SBA), scheelite mining residue (SMR), and local clay. Therefore, this study evaluates the influence of three lightweight aggregates, analysing their performance in comparison with SCLC produced with commercial lightweight aggregate (expanded clay). The concretes studied were subjected to characterisation tests in a fresh state; fluidity, apparent viscosity, visual stability, and passing ability were assessed through slump flow tests, flow time (T500), visual stability index, and J-ring, respectively, as well as measurement of the fresh specific mass. In the hardened state, tests were carried out to determine the compressive strength at 7 and 28 days, the dry specific mass, the chloride ion diffusion coefficient, and the thermal conductivity. The new concretes had density values ranging from 1.94 to 2.03 g/cm3 and compressive strength values at 28 days between 26.11 and 36.72 MPa. The results obtained show that it is feasible to produce SCLC with unconventional lightweight aggregates based on sugarcane bagasse waste and scheelite mining waste.
A Compact Multi-Identity Fully Homomorphic Encryption Scheme Without Fresh Ciphertexts
Authors: Wang Ziwei , Huang Ruwei , Wei Xiyi
Published: January 2025

The lattice-based multi-identity fully homomorphic encryption scheme combines the quantum security of lattice cryptography with the advantage of identity-based encryption. However, existing schemes face challenges such as large key sizes, inefficient ciphertext expansion processes, and reliance on outdated trapdoor designs, limiting their compactness and practicality. In this study, we propose a novel Compact Multi-Identity Fully Homomorphic Encryption Scheme (WZ-MIBFHE) that eliminates the need for fresh ciphertexts during expansion. First, we construct a compact identity-based encryption scheme by combining the YJW23 trapdoor and ABB10 under the standard model, proving its IND-sID-CPA security. The scheme is then adapted to ensure correctness and security when integrated with the decomposition method for ciphertext expansion. This adaptation also utilizes approximation errors to reduce overall noise. Finally, we expand the modified IBE scheme’s ciphertext using the decomposition method to construct the WZ-MIBFHE scheme. Compared to existing methods, WZ-MIBFHE reduces the lattice dimension to nlogq+logbq, improves public and private key sizes, and significantly lowers ciphertext expansion rates by removing the need for fresh ciphertexts. These improvements enhance both the compactness and efficiency of the scheme, making it a promising solution for multi-identity homomorphic encryption.
Trajectory Tracking for 3-Wheeled Independent Drive and Steering Mobile Robot Based on Dynamic Model Predictive Control
Authors: Xu Chaobin , Zhou Xingyu , Chen Rupeng , Li Bazhou , He Wenhao , Li Yang , Ye Fangping
Published: January 2025

Compared to four-wheel independent drive and steering (4WID4WIS) mobile robots, three-wheel independent drive and steering (3WID3WIS) mobile robots are more cost-effective due to their lower cost, lighter weight, and better handling performance, even though their acceleration performance is reduced. This paper proposes a dynamic model predictive control (DMPC) controller for trajectory tracking of 3WID3WIS mobile robots to simplify the computational complexity and improve the accuracy of traditional model predictive control (MPC). The A* algorithm with a non-point mass model is used for path planning, enabling the robot to navigate quickly in narrow and constrained environments. Firstly, the kinematic model of the 3WID3WIS mobile robot is established. Then, based on this model, a DMPC trajectory tracking controller with dynamic effects is developed. By replacing MPC with DMPC, the computational complexity of MPC is reduced. During each control period, the prediction horizon is dynamically adjusted based on changes in trajectory curvature, establishing a functional relationship between trajectory curvature and prediction horizon. Subsequently, a comparative study between the proposed controller and the traditional MPC controller is conducted. Finally, the new controller is applied to address the trajectory tracking problem of the 3WID3WIS mobile robot. The experimental results show that DMPC improves the lateral trajectory tracking accuracy by 62.94% and the heading angle tracking accuracy by 34.81% compared to MPC.
Composite Study of Relationships Between the Characteristics of Atlantic Cold Tongue: Onset, Duration, and Maximum Extent
Authors: Koné Dianikoura Ibrahim , Diawara Adama , Kouassi Benjamin Komenan , Yoroba Fidele , Kouadio Kouakou , Yapo Assi Louis Martial , Tiemoko Touré Dro , Diarrassouba Mamadou , Silué Foungnigué , Diedhioune Arona
Published: January 2025

This study analyzes the relationships between the onset, the duration, and the maximum extent of the Atlantic Cold Tongue (ACT) using ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) over the period 1979–2019. After calculating the start and end dates of the ACT each year, this study investigates potential relationships between early or late onset that may be linked to the maximum duration and extent of the ACT, which is known to influence weather patterns and precipitation in surrounding regions and the West African Monsoon System. Results show that 68% of years with a short ACT duration are associated with a late-onset ACT, while 70% of years with a long ACT duration are associated with early ACT onset years. In addition, 63% of years with a short duration of ACT have a cold tongue with a low maximum extent, while 83% of years with a long duration of ACT have a cold tongue with a greater maximum extent. Finally, 78% of early ACT onset years are associated with the coldest SST tongue in the eastern equatorial Atlantic Ocean. A comparison of the last 20 years (1999–2019) with the previous 20 years (1979–1998) shows a cooling trend in SST, with ACT occurring and ending earlier in recent years than in the past. However, as the changes in the end date are greater than those in the onset date, the duration of the ACT has been 5–12 days shorter in the last 20 years than in the previous 20 years. Knowledge of these ACT characteristics and their interrelations and drivers is crucial for understanding the West African Monsoon System and for improving climate models and seasonal forecasts.
A Comparison of Machine Learning-Based Approaches in Estimating Surface PM2.5 Concentrations Focusing on Artificial Neural Networks and High Pollution Events
Authors: Wei Shijin , Shores Kyle , Xu Yangyang
Published: January 2025

Surface PM2.5 concentrations have significant implications for human health, necessitating accurate estimations. This study compares various machine learning models, including linear models, tree-based algorithms, and artificial neural networks (ANNs) for estimating PM2.5 concentrations using the MERRA-2 dataset from 2012 to 2023. Mutual information and Spearman cross-feature correlation scores are used during feature selections. The performance of models is evaluated using metrics including normalized Nash–Sutcliffe efficiency (NNSE), root mean standard deviation ratio (RSR), and mean percentage error (MPE). Our results show that ANNs outperform linear and tree models, particularly in estimating daily PM2.5 concentrations of 35–1000 µg/m3. ANNs improve NNSE by 119% and 46%, RSR by 40% and 24%, and MPE by 44% and 30% from linear and tree models, respectively, indicating ANN’s superior estimation performance during high pollution days. The sensitivity analysis of features that interpret the models suggests that the total extinction AOD at 550 nm and surface CO concentrations are the most important features in the Western and Eastern U.S., respectively. The findings suggest that even the simplest NNs provide better air quality estimates, especially during high pollution events, which is beneficial for long-term exposure analysis. Future research should explore more sophisticated NN architectures with spatial and temporal variations in PM2.5 to improve the model performance.
Investigating the Disproportionate Impacts of Air Pollution on Vulnerable Populations in South Africa: A Systematic Review
Authors: Frazenburg Claudia , Sepadi Maasago Mercy , Chitakira Munyaradzi
Published: January 2025

Background: Knowledge of how different social groups in South Africa are affected by air quality is important for informing air quality regulations and determining the integrated social–environmental approach to adopt. This systematic review evaluates the impact of air pollution on these groups, investigates socio-economic factors that increase exposure, and assesses mitigation measures. Methods: The review followed the PRISMA guidelines and analyzed quantitative studies conducted in South Africa, which were published between 2014 and 2024. The studies’ sources included databases such as Google Scholar, PubMed, and Scopus. Data from 47 eligible studies were analyzed using descriptive statistics. Results: Results show that women, children, and low-income communities tend to bear the brunt of poor air quality. Children are the most affected by poor air quality, with significant respiratory issues. Pregnant women are vulnerable to adverse birth outcomes. The results indicate that of the 47 studies reviewed, 51% focused on the effects of air pollution on children, whilst fewer studies (26%) focused on women. This may point to a gap in research on the specific impacts of air pollution on women. Low-income communities face increased exposure due to proximity to pollutant sources and substandard housing. The results further indicated that of the health impacts experienced by vulnerable populations, general health issues (96%) and respiratory health issues (89%) are the most prominent health impacts. Conclusions: The study underscores the need for stricter air quality regulations, public education, and an integrated social–environmental approach to mitigate exposure in vulnerable populations.
Groundwater Storage Estimation in the Saskatchewan River Basin Using GRACE/GRACE-FO Gravimetric Data and Machine Learning
Authors: Hamdi Mohamed , El Alem Anas , Goita Kalifa
Published: January 2025

Climate change is having a significant impact on groundwater storage, affecting water resources in many parts of the world. To characterize this impact, remote sensing and machine learning are essential tools to analyze the data accurately and efficiently. This study aims to predicting the variations of groundwater storage (GWS) using GRACE/GRACE-FO and multi-source remote sensing data, combined with machine learning techniques. The approach was applied over the Canadian Prairies region. The study area was classified into three zones of different aquifer potentials (low, medium, and high) using a combination of remote sensing data and the Classification and Regression Trees (CART) approach. The prediction model was developed using a machine-learning approach based on multiple linear regression to estimate GWS variations as a function of various environmental parameters. The results showed that the developed model was able to predict GWS variations with satisfactory accuracy (up to 95% of the explained variance) and good robustness (96% success rate). They also provided a better understanding of the variations in groundwater storage in the Canadian Prairies. Therefore, this work provides a promising method for predicting GWS, which could eventually be applied to other similar environmental conditions.
Theoretical Basis for Classifying Hyperuniform States of Two-Component Systems
Authors: Frusawa Hiroshi
Published: January 2025

Hyperuniform states of matter exhibit unusual suppression of density fluctuations at large scales, contrasting sharply with typical disordered configurations. Various types of hyperuniformity emerge in multicomponent disordered systems, significantly enhancing their functional properties for advanced applications. This paper focuses on developing a theoretical framework for two-component hyperuniform systems. We provide a robust theoretical basis to identify novel conditions on structure factors for a variety of hyperuniform binary mixtures, classifying them into five distinct types with seven unique states. Our findings also offer valuable guidelines for designing multihyperuniform materials where each component preserves hyperuniformity, added to the overall hyperuniformity.
HBV cccDNA: The Molecular Reservoir of Hepatitis B Persistence and Challenges to Achieve Viral Eradication
Authors: Boonstra André , Sari Gulce
Published: January 2025

Hepatitis B virus (HBV) is a major global health issue, with an estimated 254 million people living with chronic HBV infection worldwide as of 2022. Chronic HBV infection is the leading cause of cirrhosis and liver cancer. Current treatment with nucleos(t)ide analogs is effective in the suppression of viral activity but generally requires lifelong treatment. They fail to eradicate the HBV viral reservoir, called covalently closed circular DNA (cccDNA), which replicates in the nucleus of liver cells. The cccDNA serves as the sole template for viral replication, as it generates the pregenomic RNA (pgRNA) necessary for producing new viral genomes. This stable form of viral DNA can reactivate the virus when treatment is stopped. HBV cccDNA is therefore one of the main challenges in curing chronic HBV infections. By targeting steps such as cccDNA formation, capsid assembly, or particle secretion, researchers continue to seek ways to interfere with HBV replication and to reduce its persistence, ultimately to eradicate HBV as a global health problem. This review provides an overview of what is currently known about cccDNA formation and biogenesis and the ongoing efforts to target and eradicate it to cure chronic HBV infections.
Sigma-1 Receptor Modulates CFA-Induced Inflammatory Pain via Sodium Channels in Small DRG Neurons
Authors: Song Yuanlong , Xu Zifen , Zhang Liangpin , Gao Linlin
Published: January 2025

The sigma-1 receptor (Sig-1R) has emerged as a significant target in the realm of pain management and has been the subject of extensive research. Nonetheless, its specific function in inflammatory pain within dorsal root ganglion (DRG) neurons remains inadequately elucidated. This study utilized whole-cell patch clamp techniques, single-cell real-time PCR, and immunohistochemistry to examine the influence of Sig-1R on inflammatory pain induced by complete Freund’s adjuvant (CFA) in a rat model. Our results revealed several key findings: (1) The expression of Sig-1R was found to be upregulated during the progression of inflammatory pain, with a notable translocation from the cytoplasm to the membrane; (2) Inhibition of peripheral Sig-1R using S1RA resulted in a reduction of CFA-induced allodynia; (3) Activation of Sig-1R through PRE-084 led to a decrease in the fast sodium current in isolated DRG neurons from CFA-treated rats, which was associated with a diminished action potential (AP) peak and maximum depolarizing rate (MDR), as well as an increased rheobase; (4) Furthermore, PRE-084 was observed to enhance the slow component of the sodium current, resulting in hyperpolarization of the threshold potential and an increase in AP firing frequency, alongside an elevation in the mRNA expression of the slow sodium channel Nav1.9 in CFA-treated rats. In conclusion, our findings suggest that the modulation of sodium channels by Sig-1R in DRG neurons plays a significant role in the mechanisms underlying inflammatory pain.
Reliability and Validity of the Articulation Motion Assessment System Using a Rotary Encoder
Authors: Ito Hiroki , Yamaguchi Hideaki , Inoue Mari , Nagano Hikaru , Kitai Ken , Morita Kiichiro , Kodama Takayuki
Published: January 2025

This study aimed to validate the effectiveness of the Articulation Motion Assessment System (AMAS), a joint kinematic evaluation system, for clinical applications. AMAS enables synchronised measurement using neurophysiological indicators, overcoming laboratory setting limitations. We compared AMAS-based ankle joint kinematic evaluations, particularly the sagittal and frontal plane angles, with two-dimensional (2D) motion analysis to determine the validity and reliability of AMAS. Both AMAS and 2D motion analysis reliably detected significant differences in angles within the sagittal and frontal planes. Correlation analysis revealed a significant moderate-to-strong correlation between the AMAS and the conventional method of 2D motion analysis, proving the measurement validity of the AMAS (ρ = 0.53–0.77 for sagittal plane angles; ρ = 0.46–0.72 for frontal plane angles). The average root mean squared error (RMSE) was significantly lower in AMAS (10.90 ± 2.93° for sagittal plane angles; 13.44 ± 1.09° for frontal plane angles) than in the inertial sensor-based three-dimensional (3D) motion analysis. Reliability analysis revealed high reliability of measurements (intraclass correlation coefficients (ICC) ≥ 0.76). However, the Bland–Altman analysis identified a slightly lower fixed bias, which was observed as a characteristic of each measurement system. The AMAS accurately detects ankle joint angles without being constrained by measurement environment limitations. Synchronised measurements using neurophysiological indicators potentially contribute to understanding ankle joint control mechanisms and developing rehabilitation strategies.
Correlation Between Systemic Inflammation, Gut Microbiome Dysbiosis and Postoperative Complications After the Modified Whipple Procedure
Authors: Breaza Gelu Mihai , Hut Florin Emil , Cretu Octavian , Abu-Awwad Simona-Alina , Abu-Awwad Ahmed , Sima Laurențiu Vasile , Dan Radu Gheorghe , Dan Cristina Ana-Maria , Closca Raluca Maria , Zara Flavia
Published: January 2025

(1) Background: The modified Whipple procedure, or pylorus-preserving pancreaticoduodenectomy, is a complex surgical intervention used to treat pancreatic head tumors. While preserving digestive function, it is associated with significant perioperative risks. This study explores the clinical, immunological, and microbiome-related factors influencing postoperative complications, focusing on the interplay between patient comorbidities, systemic inflammation, and gut dysbiosis. (2) Methods: A retrospective analysis was conducted on 123 patients undergoing the modified Whipple procedure for pancreatic head tumors. Patients were categorized into two groups based on the occurrence of significant postoperative complications (Group A: with complications; Group B: without complications). Data on demographics, comorbidities, inflammatory markers (CRP, IL-6, procalcitonin), and gut microbiome composition were collected. Microbial diversity was evaluated using the Shannon Index, and logistic regression was performed to identify independent predictors of complications. (3) Results: Patients in Group A had a significantly higher prevalence of diabetes mellitus (43.1% vs. 20.8%; p = 0.02) and cardiovascular disease (35.3% vs. 13.9%; p = 0.01). Elevated inflammatory markers (CRP ≥ 40 mg/L, IL-6 ≥ 30 pg/mL, procalcitonin ≥ 0.5 ng/mL) were strongly associated with higher complication rates. Microbiome analysis indicated dysbiosis in Group A, with reduced Lactobacillus and Bifidobacterium levels, increased Enterobacteriaceae abundance, and a lower Shannon Index (<2). Patients exhibiting both dysbiosis and elevated inflammation had the highest complication rate (60%). Multivariate analysis identified diabetes, elevated IL-6, and dysbiosis as independent predictors of adverse outcomes. (4) Conclusions: Postoperative complications after the modified Whipple procedure are influenced by systemic inflammation and gut dysbiosis. A systematic preoperative assessment of microbiome health and inflammatory markers enables accurate risk stratification and personalized interventions, potentially reducing the incidence of complications and improving overall surgical outcomes.
A Numerical Study on the Crashworthiness of Corrugated Conical Tubes with Small Semi-Apical Angles and Their Influence Mechanism
Authors: Song Yiheng , Lin Qinyu , Chen Jinxiang , Zhao Tidong
Published: January 2025

To develop a new type of biomimetic single-cell and multi-cell energy-absorbing box (tube) featuring conical tubes at the intersection of cell walls, it is necessary to address the issue of large bottom-space requirements in current conical energy-absorbing tubes with superior crashworthiness due to their large semi-apical angles. This study proposes adding corrugations to conical tubes with small semi-apical angles and modifying the bottom by replacing the last one or two inclined corrugations with vertical ones. Finite element simulation results show that, compared to conventional conical tubes, adding corrugations reduces the optimal semi-apical angle of conical tubes by 5°, with the optimal range being 5–10°. Furthermore, the modification method of replacing inclined corrugations with vertical ones effectively mitigates the challenges of increasing peak crushing force and large end-peak crushing force as the semi-apical angle increases. This structural optimization lays a foundation for the development of new biomimetic single-cell and multi-cell energy-absorbing boxes (tubes) incorporating conical tubes.
Multi-Strategy Improved Red-Tailed Hawk Algorithm for Real-Environment Unmanned Aerial Vehicle Path Planning
Authors: Wang Mingen , Yuan Panliang , Hu Pengfei , Yang Zhengrong , Ke Shuai , Huang Longliang , Zhang Pai
Published: January 2025

In recent years, unmanned aerial vehicle (UAV) technology has advanced significantly, enabling its widespread use in critical applications such as surveillance, search and rescue, and environmental monitoring. However, planning reliable, safe, and economical paths for UAVs in real-world environments remains a significant challenge. In this paper, we propose a multi-strategy improved red-tailed hawk (IRTH) algorithm for UAV path planning in real environments. First, we enhance the quality of the initial population in the algorithm by using a stochastic reverse learning strategy based on Bernoulli mapping. Then, the quality of the initial population is further improved through a dynamic position update optimization strategy based on stochastic mean fusion, which enhances the exploration capabilities of the algorithm and helps it explore promising solution spaces more effectively. Additionally, we proposed an optimization method for frontier position updates based on a trust domain, which better balances exploration and exploitation. To evaluate the effectiveness of the proposed algorithm, we compare it with 11 other algorithms using the IEEE CEC2017 test set and perform statistical analysis to assess differences. The experimental results demonstrate that the IRTH algorithm yields competitive performance. Finally, to validate its applicability in real-world scenarios, we apply the IRTH algorithm to the UAV path-planning problem in practical environments, achieving improved results and successfully performing path planning for UAVs.
Glucose Sensor Design Based on Monte Carlo Simulation
Authors: Xue Gang , Zhang Ruiping , Chen Yihao , Xu Wei , Zhang Changxing
Published: January 2025

Continuous glucose monitoring based on the minimally invasive implantation of glucose sensor is characterized by high accuracy and good stability. At present, glucose concentration monitoring based on fluorescent glucose capsule sensor is a new development trend. In this paper, we design a fluorescent glucose capsule sensor with a design optimization study. The motion trajectory of incident light in the fluorescent gel layer is simulated based on the Monte Carlo method, and the cloud maps of light intensity with the light intensity distribution at the light-receiving layer are plotted. Altering the density of fluorescent molecules, varying the thickness of tissue layers, and adjusting the angle of incidence deflection, the study investigates the influence of these parameter changes on the optimal position of reflected light at the bottom. Finally, the simulation results were utilized to design and fabricate a fluorescent glucose capsule sensor. Rabbit subcutaneous tissue glucose level tests and real-time glucose solution concentration monitoring experiments were performed. This work contributes to the real-time monitoring of glucose levels and opens up new avenues for research on fabricating glucose sensors.
Development and Validation of LAMP Assays for Distinguishing MPXV Clades with Fluorescent and Colorimetric Readouts
Authors: Atceken Nazente , Asghari Dilmani Sara , Abdullah Ahmed Choukri , Sarıkaya Mutlu , Yigci Defne , Korkmaz Gozde , Tasoglu Savas
Published: January 2025

Human monkeypox (Mpox) is a zoonotic disease caused by the Monkeypox virus (MPXV). As of 14 August 2024, the World Health Organization (WHO) has declared it a global health emergency. For Mpox, this was the second public health emergency of global significance in the past two years. MPXV belongs to the Poxviridae family and is phylogenetically and epidemically divided into two clades: the Congo Basin (Clade-I) and the West African (Clade-II) clades. Clade-I has been associated with more severe disease progression and higher mortality compared to Clade-II, and thus the differentiation between clades can play an important role in predicting disease prognosis. The LAMP technique has the advantages of not requiring thermal cycling and achieving higher amplification in a shorter time compared to qPCR. Different types of LAMP assays were developed in this study to benefit from these advantages. We report the development of LAMP-1 and LAMP-2 assays using the LAMP method to detect MPXV Clade-I and Clade-II, respectively. The LAMP-1 assay includes both fluorescence and visible colorimetric readout tests developed with sensitivities of 103 and 107 copies, respectively. For the LAMP-2 assay, a probe-based test utilizing the Novel R-Duplex DARQ probe was developed, offering fluorescence detection at a sensitivity of 103 copies. As a result, we successfully developed three highly specific molecular diagnostic tests that distinctly differentiate between MPXV clades, delivering essential tools for the precise diagnosis and effective control of Mpox.
Enhancing Biocide Safety of Milk Using Biosensors Based on Cholinesterase Inhibition
Authors: Mouawad Lynn , Istamboulie Georges , Catanante Gaëlle , Noguer Thierry
Published: January 2025

A sensitive and reliable electrochemical biosensor for the detection of benzalkonium chloride (BAC) and didecyldimethylammonium chloride (DDAC), the most commonly used disinfectant biocides in the agri-food industry, is described. Acetylcholinesterase from Drosophila melanogaster (DM AChE) and butyrylcholinesterase from horse serum (BChE) were immobilized by entrapment in a photocrosslinkable polymer on the surface of carbon screen-printed electrodes. Preliminary tests conducted in phosphate buffer showed limits of detection (LODs) of 0.26 µM for BAC using the BChE-based sensor and 0.04 µM for DDAC using the DM AChE sensor. These performances comply with the European regulation for dairy products, which sets a maximum allowable concentration of 0.28 µM for biocides. However, when tested directly in milk samples, a dramatic decrease in the sensitivity of both sensors towards BAC and DDAC biocides was reported. To overcome this problem, a simple liquid–liquid extraction was necessary prior to biosensor measurements, ensuring that the biosensors met European regulatory standards and provided an unbiased response.
The Relationships of Workplace Spirituality and Psychological Capital with Work Engagement Among Junior High School Teachers
Authors: Wu Shwu-Ming
Published: January 2025

Engaged teachers demonstrate high levels of motivation and commitment to their work, increasing the likelihood of job retention and enabling them to perform at their best, ultimately benefiting both schools and students. Teacher engagement may be fostered by enhancing workplace spirituality and psychological capital. This study aimed to examine the relationships between and effects of workplace spirituality and psychological capital on work engagement, while also comparing demographic differences affecting these variables. A sample of 123 teachers was recruited from various junior high schools in Taiwan. The measured variables were workplace spirituality (including meaningful work, inner life, and sense of community), psychological capital (covering efficacy, hope, optimism, and resilience), and work engagement (comprising vigor, dedication, and absorption). The results indicate that male teachers exhibited higher levels of hope and overall psychological capital, while older teachers displayed greater optimism and a stronger sense of community. Additionally, strong positive correlations were found among workplace spirituality, psychological capital, and work engagement. Particularly, workplace spirituality and psychological capital were identified as significant predictors of work engagement among junior high school teachers. The implication for school organizations is that enhancing workplace spirituality and psychological capital should be prioritized as strategies to promote work engagement among junior high school teachers.
Determinants for Drunk Driving Recidivism—An Application of the Integrated Prototype Willingness Model
Authors: Jou Rong-Chang , Hsu Han-Wen
Published: January 2025

The paper applies the prototype willingness model (PWM) and incorporates components of the theory of planned behavior (TPB), along with deterrence factors, to understand the behavioral intentions, willingness, and recidivism behaviors of individuals penalized for drunk driving. It explores psychological and social factors influencing repeat offenses, focusing on attitudes, subjective norms, prototypes, and deterrence. The PWM outlines two pathways—reasoned (based on intentions) and social reactive (based on willingness). The model helps predict risky behaviors like drunk driving. Thirteen hypotheses are proposed in this study to examine how various factors, such as attitudes, subjective norms, and deterrence, influence willingness, intentions, and behavior. Surveys were conducted among individuals attending road safety classes after being penalized for drunk driving. A total of 1156 individuals participated in the survey, with 855 valid responses collected. The results indicate that behavioral willingness had a stronger impact on recidivism than intention. On the other hand, subjective norms did not significantly affect the intent to reoffend, but attitudes, deterrence, and PBC did. The findings suggest that focusing on behavioral willingness, deterrence, and educational interventions could help reduce repeat drunk driving offenses. The paper offers insights for policymakers to improve prevention strategies, by focusing on the psychological motivators of repeat offenders.
Solubility Characteristics and Microstructure of Bitumen: A Review
Authors: Liu Han , Ding Haibo , Qiu Yanjun , Grothe Hinrich
Published: January 2025

This is a comprehensive review of the significance of solubility theories, internal stability, and external compatibility within petroleum science and pavement engineering. The historical development and future trends of solubility methods in bitumen are discussed, emphasizing the importance of separating bitumen components based on solubility to establish a link with chemistry. The paper also highlights the development of solubility theories and various characterization tests for bitumen, as well as the distribution of functional groups of solvents and their parameters. Additionally, it explores the generation of solubility profiles for different types and aging states of bitumen based on solubility data and statistical correlation, and the use of stability diagrams to assess the internal stability of bitumen in different states. The potential for continued research in this field is emphasized to bridge the gap between fundamental chemistry and practical application, leading to improved formulations and enhanced performance of bitumen in various applications, ultimately resulting in more durable and stable pavement structures.
Life Cycle Carbon Emission Analysis of Buildings with Different Exterior Wall Types Based on BIM Technology
Authors: Lyu Yuelong , Fomin Nikita Igorevich , Li Shuailong , Hu Wentao , Xiao Shuoting , Huang Yue , Liu Chong
Published: January 2025

Building energy conservation and emission reduction are crucial in addressing global climate change. High-performance insulated building envelopes can significantly reduce energy consumption over a building’s lifecycle. However, few studies have systematically analyzed carbon reduction potential through a life cycle assessment (LCA), incorporating case studies and regional differences. To address this, this study establishes an LCA carbon emission calculation model using Building Information Modeling (BIM) technology and the carbon emission coefficient method. We examined four residential buildings in China’s cold regions and hot summer–cold winter regions, utilizing prefabricated concrete sandwich insulation exterior walls (PCSB) and autoclaved aerated concrete block self-insulating exterior walls (AACB). Results indicate that emissions during the operational phase account for 75% of total lifecycle emissions, with heating, ventilation, and air conditioning systems contributing over 50%. Compared to AACB, PCSB reduces lifecycle carbon emissions by 18.54% and by 20.02% in hot summer–cold winter regions. The findings demonstrate that PCSB offers significant energy-saving and emission-reduction benefits during the construction and operation phases. However, it exhibits higher energy consumption during the materialization and demolition phases. This study provides a practical LCA carbon calculation framework that offers insights into reducing lifecycle carbon emissions, thereby guiding sustainable building design.
Optimizing Subsurface Geotechnical Data Integration for Sustainable Building Infrastructure
Authors: Ijaz Nauman , Ijaz Zain , Zhou Nianqing , Rehman Zia ur , Ijaz Hamdoon , Ijaz Aashan , Hamza Muhammad
Published: January 2025

Sustainable building construction encounters challenges stemming from escalating expenses and time delays associated with geotechnical assessments. Developing and optimizing geotechnical soil maps (SMs) using existing data across heterogeneous geotechnical formations offer strategic and dynamic solutions. This strategic approach facilitates economical and prompt site evaluations, and offers preliminary ground models, enhancing efficient and sustainable building foundation design. In this framework, this paper aimed to develop SMs for the first time in the rapidly growing district of Gujrat using the optimal interpolation technique (OIT). The subsurface conditions were evaluated using the standard penetration test (SPT) N-values and soil classification including seismic wave velocity to account for seismic effects. Among the different geostatistical and geospatial models, the inverse distance weighting (IDW) model based on an optimized spatial analyst approach yielded the minimum error and a higher association with the field data for the understudy region. Overall, the optimized IDW technique yielded root mean square error (RMSE), mean absolute error (MAE), and correlation coefficient (CC) ranges between 0.57 and 0.98. Furthermore, analytical depth-dependent models were developed using SPT-N values to assess the bearing capacity, demonstrating the association of R2 > 0.95. Moreover, the study area was divided into three geotechnical zones based on the average SPT-N values. Comprehensive validation of different strata evaluation based on the optimal IDW for the SPT-N and soil type-based SMs revealed that the RMSE and MAE ranged between 0.36–1.65 and 0.30–0.59, while the CC ranged between 0.93 and 0.98 at multiple depths. The allowable bearing capacity (ABC) for spread footings was determined by evaluating the shear, settlement, and seismic factors. The study offers insights into regional variations in geotechnical formations along with shallow foundation design guidelines for practitioners and researchers working with similar soil conditions.
Optimization of Anti-Scour Device Combined with Perforated Baffle and Ring-Wing Plate Based on a Multi-Factor Orthogonal Experiment
Authors: Wang Yan , Liao Rongjun , Yuan Pei , Chen Jinchao
Published: January 2025

In this paper, a new anti-scour device combined with a perforated baffle and ring-wing plate is proposed to enhance the traditional method for better protection of bridge piers from local scour. Based on computational fluid dynamics (CFD), the orthogonal experiments investigated the general laws of the influence of the main factors, such as the ratio of baffle perforated, the position of baffle, and the height of ring-wing plate on the anti-scour effect. Under the protection of the combined device, the maximum scour depth reduction rate in front of the pier is between 65.18% and 81.01%, while that at the side of the pier is between 52.63% and 68.42%. Especially when the perforated ratio is 20%, the baffle is 2d (d is diameter of the pier) away from the pier, and the ring-wing plate is located at 1/3 of water depth, the anti-scour effect is the best. Also, the flow field around the pier under the protection of the combined device is further investigated. The results show that the structure blocks the down-flow actively and diverts and dissipates the flow energy to decrease flow below the critical velocity of sediment. Thus, the device combined with perforated baffle and ring-wing plate has a prominent anti-scour effect and provides a basis for further studies and engineering application.
Impact of Early Nutritional Intervention During Cancer Treatment on Dietary Intakes and Cardiometabolic Health in Children and Adolescents
Authors: Delorme Josianne , Dima Andra , Bélanger Véronique , Napartuk Mélanie , Bouchard Isabelle , Meloche Caroline , Curnier Daniel , Sultan Serge , Laverdière Caroline , Sinnett Daniel , Marcil Valérie
Published: January 2025

Background/Objectives: Pediatric cancer survivors are at greater risk of cardiometabolic complications than their peers. This study evaluates the preliminary impact of the VIE (Valorization, Implication, Education) intervention, which integrates nutrition, physical activity, and psychological support, on dietary intake and cardiometabolic health among children and adolescents during cancer treatment. Methods: This comparative study includes pediatric cancer patients recruited to either the VIE intervention group or a control group receiving standard care. Post-treatment data on dietary intake, anthropometric measures, blood pressure, and biochemical parameters were compared between groups and stratified by level of involvement in the nutritional intervention and age at diagnosis (children and adolescents). Results: In the intervention group, 45 participants were included (51.1% male, mean age at evaluation 10.2 ± 4.5 years, mean time since end of treatment of 1.3 ± 0.8 years), and the control group comprised 77 participants (44.2% male, mean age at evaluation 12.0 ± 5.6 years, mean time since end of treatment of 1.4 ± 0.8 years). The intervention group had lower total caloric intake (mean: 1759 ± 513 vs. 1997 ± 669 kcal, p = 0.042) and higher calcium intake (mean: 567 ± 240 vs. 432 ± 197 mg/1000 kcal, p = 0.001). The participants who were highly involved in the nutritional intervention had greater protein-derived energy intake than the controls (mean: 17 ± 5 vs. 15 ± 4%, p = 0.029). While there was a tendency for a lesser proportion of cardiometabolic risk factors in the adolescents from the intervention group, the differences did not reach statistical significance. Conclusions: The VIE intervention improved some specific dietary intakes in the medium term after treatment completion but did not significantly impact cardiometabolic health outcomes. Additional strategies are needed to improve the diet of pediatric cancer patients, and further research is warranted to assess the long-term impact of such interventions.
From Homeostasis to Neuroinflammation: Insights into Cellular and Molecular Interactions and Network Dynamics
Authors: Müller Ludmila , Di Benedetto Svetlana , Müller Viktor
Published: January 2025

Neuroinflammation is a complex and multifaceted process that involves dynamic interactions among various cellular and molecular components. This sophisticated interplay supports both environmental adaptability and system resilience in the central nervous system (CNS) but may be disrupted during neuroinflammation. In this article, we first characterize the key players in neuroimmune interactions, including microglia, astrocytes, neurons, immune cells, and essential signaling molecules such as cytokines, neurotransmitters, extracellular matrix (ECM) components, and neurotrophic factors. Under homeostatic conditions, these elements promote cellular cooperation and stability, whereas in neuroinflammatory states, they drive adaptive responses that may become pathological if dysregulated. We examine how neuroimmune interactions, mediated through these cellular actors and signaling pathways, create complex networks that regulate CNS functionality and respond to injury or inflammation. To further elucidate these dynamics, we provide insights using a multilayer network (MLN) approach, highlighting the interconnected nature of neuroimmune interactions under both inflammatory and homeostatic conditions. This perspective aims to enhance our understanding of neuroimmune communication and the mechanisms underlying shifts from homeostasis to neuroinflammation. Applying an MLN approach offers a more integrative view of CNS resilience and adaptability, helping to clarify inflammatory processes and identify novel intervention points within the layered landscape of neuroinflammatory responses.