bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison between MODFLOW Groundwater Modeling with Traditional and Distributed Recharge
Authors: Navarro-Farfán María del Mar , García-Romero Liliana , Martínez-Cinco Marco Antonio , Hernández-Hernández Mario Alberto , Sánchez-Quispe Sonia Tatiana
Published: January 2024

Groundwater models serve the function of predicting and analyzing aquifer behavior. They require input information, such as hydrogeological parameters like hydraulic conductivity and storage coefficient, which are used to calibrate the model, and elementary actions that include recharge and extracted volumes. There are cases in which it is insufficient to know the homogeneous recharge entering through the surface basin, referred to as traditional recharge, since, in many instances, the distribution is altered by changes in land use. For this reason, based on the geomorphological characteristics of the basin, weighting is proposed for sites with greater recharge capacity. The present work shows a solution to the recharge distribution using the potential groundwater recharge (PGR) map, which is formed by weighting spatially distributed information: (i) drainage, (ii) precipitation, (iii) land use, (iv) geological faults, (v) soil type, (vi) slope, and (vii) hydrogeology. A comparison is made between groundwater modeling using traditional recharge and PGR recharge. It is noted that the modeling perform similarly for both recharges, and the errors do not exceed 5% absolute error, which validates the model’s reliability. This manuscript demonstrates how to model and calibrate groundwater in aquifers with scarce information and variable recharge, making it reproducible.
Rapid Forecasting of Cyber Events Using Machine Learning-Enabled Features
Authors: Ahmed Yussuf , Azad Muhammad Ajmal , Asyhari Taufiq
Published: January 2024

In recent years, there has been a notable surge in both the complexity and volume of targeted cyber attacks, largely due to heightened vulnerabilities in widely adopted technologies. The Prediction and detection of early attacks are vital to mitigating potential risks from cyber attacks and network resilience. With the rapid increase of digital data and the increasing complexity of cyber attacks, big data has become a crucial tool for intrusion detection and forecasting. By leveraging the capabilities of unstructured big data, intrusion detection and forecasting systems can become more effective in detecting and preventing cyber attacks and anomalies. While some progress has been made on attack prediction, little attention has been given to forecasting cyber events based on time series and unstructured big data. In this research, we used the CSE-CIC-IDS2018 dataset, a comprehensive dataset containing several attacks on a realistic network. Then we used time-series forecasting techniques to construct time-series models with tuned parameters to assess the effectiveness of these techniques, which include Sequential Minimal Optimisation for regression (SMOreg), linear regression and Long Short-Term Memory (LSTM) to forecast the cyber events. We used machine learning algorithms such as Naive Bayes and random forest to evaluate the performance of the models. The best performance results of 90.4% were achieved with Support Vector Machine (SVM) and random forest. Additionally, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) metrics were used to evaluate forecasted event performance. SMOreg’s forecasted events yielded the lowest MAE, while those from linear regression exhibited the lowest RMSE. This work is anticipated to contribute to effective cyber threat detection, aiming to reduce security breaches within critical infrastructure.
Unmanned Autonomous Intelligent System in 6G Non-Terrestrial Network
Authors: Wang Xiaonan , Guo Yang , Gao Yuan
Published: January 2024

Non-terrestrial network (NTN) is a trending topic in the field of communication, as it shows promise for scenarios in which terrestrial infrastructure is unavailable. Unmanned autonomous intelligent systems (UAISs), as a physical form of artificial intelligence (AI), have gained significant attention from academia and industry. These systems have various applications in autonomous driving, logistics, area surveillance, and medical services. With the rapid evolution of information and communication technology (ICT), 5G and beyond-5G communication have enabled numerous intelligent applications through the comprehensive utilization of advanced NTN communication technology and artificial intelligence. To meet the demands of complex tasks in remote or communication-challenged areas, there is an urgent need for reliable, ultra-low latency communication networks to enable unmanned autonomous intelligent systems for applications such as localization, navigation, perception, decision-making, and motion planning. However, in remote areas, reliable communication coverage is not available, which poses a significant challenge for intelligent systems applications. The rapid development of non-terrestrial networks (NTNs) communication has shed new light on intelligent applications that require ubiquitous network connections in space, air, ground, and sea. However, challenges arise when using NTN technology in unmanned autonomous intelligent systems. Our research examines the advancements and obstacles in academic research and industry applications of NTN technology concerning UAIS, which is supported by unmanned aerial vehicles (UAV) and other low-altitude platforms. Nevertheless, edge computing and cloud computing are crucial for unmanned autonomous intelligent systems, which also necessitate distributed computation architectures for computationally intensive tasks and massive data offloading. This paper presents a comprehensive analysis of the opportunities and challenges of unmanned autonomous intelligent systems in UAV NTN, along with NTN-based unmanned autonomous intelligent systems and their applications. A field trial case study is presented to demonstrate the application of NTN in UAIS.
Secure Genomic String Search with Parallel Homomorphic Encryption
Authors: Aziz Md Momin Al , Tamal Md Toufique Morshed , Mohammed Noman
Published: January 2024

Fully homomorphic encryption (FHE) cryptographic systems enable limitless computations over encrypted data, providing solutions to many of today’s data security problems. While effective FHE platforms can address modern data security concerns in unsecure environments, the extended execution time for these platforms hinders their broader application. This project aims to enhance FHE systems through an efficient parallel framework, specifically building upon the existing torus FHE (TFHE) system chillotti2016faster. The TFHE system was chosen for its superior bootstrapping computations and precise results for countless Boolean gate evaluations, such as AND and XOR. Our first approach was to expand upon the gate operations within the current system, shifting towards algebraic circuits, and using graphics processing units (GPUs) to manage cryptographic operations in parallel. Then, we implemented this GPU-parallel FHE framework into a needed genomic data operation, specifically string search. We utilized popular string distance metrics (hamming distance, edit distance, set maximal matches) to ascertain the disparities between multiple genomic sequences in a secure context with all data and operations occurring under encryption. Our experimental data revealed that our GPU implementation vastly outperforms the former method, providing a 20-fold speedup for any 32-bit Boolean operation and a 14.5-fold increase for multiplications.This paper introduces unique enhancements to existing FHE cryptographic systems using GPUs and additional algorithms to quicken fundamental computations. Looking ahead, the presented framework can be further developed to accommodate more complex, real-world applications.
Public Health Implications for Effective Community Interventions Based on Hospital Patient Data Analysis Using Deep Learning Technology in Indonesia
Authors: Putri Lenni , Girsang Ermi , Lister I , Kung Hsiang , Kadir Evizal , Rosa Sri
Published: January 2024

Public health is an important aspect of community activities, making research on health necessary because it is a crucial field in maintaining and improving the quality of life in society as a whole. Research on public health allows for a deeper understanding of the health problems faced by a population, including disease prevalence, risk factors, and other determinants of health. This work aims to explore the potential of hospital patient data analysis as a valuable tool for understanding community implications and deriving insights for effective community health interventions. The study recognises the significance of harnessing the vast amount of data generated within hospital settings to inform population-level health strategies. The methodology employed in this study involves the collection and analysis of deidentified patient data from a representative sample of a hospital in Indonesia. Various data analysis techniques, such as statistical modelling, data mining, and machine learning algorithms, are utilised to identify patterns, trends, and associations within the data. A program written in Python is used to analyse patient data in a hospital for five years, from 2018 to 2022. These findings are then interpreted within the context of public health implications, considering factors such as disease prevalence, socioeconomic determinants, and healthcare utilisation patterns. The results of the data analysis provide valuable insights into the public health implications of hospital patient data. The research also covers predictions for the patient data to the hospital based on disease, age, and geographical residence. The research prediction shows that, in the year 2023, the number of patients will not be considerably affected by the infection, but in March to April 2024 the number will increase significantly up to 10,000 patients due to the trend in the previous year at the end of 2022. These recommendations encompass targeted prevention strategies, improved healthcare delivery models, and community engagement initiatives. The research emphasises the importance of collaboration between healthcare providers, policymakers, and community stakeholders in implementing and evaluating these interventions.
The Road Network Design Problem for the Deployment of Automated Vehicles (RNDP-AVs): A Nonlinear Programming Mathematical Model
Authors: Conceição Lígia , Correia Gonçalo Homem de Almeida , van Arem Bart , Tavares José Pedro
Published: January 2024

Once trusted, automated vehicles (AVs) will gradually appear in urban areas. Such a transition is an opportunity in transport planning to control undesired impacts and possibly mitigate congestion at a time when both conventional vehicles (CVs) and AVs coexist. This paper deals with the complex transport decision problem of designing part of the network that is exclusive for AVs through a nonlinear programming model. The objective function minimises the costs of travel times where vehicles circulate under user equilibrium. The model evaluates the benefits of having an AVs-dedicated infrastructure and the associated costs from the detouring of CVs. Three planning strategies are explored: incremental, long-term and hybrid planning. The first creates a subnetwork evolving incrementally over time. The second reversely designs a subnetwork from the optimal solution obtained at a ratio of 90% AVs. The third limits the incremental planning towards that optimal long-term solution. The model is applied to the city of Delft, in the Netherlands. Two scenarios are analysed, with and without AV-dedicated roads, at several AV penetration rates. We find that implementing dedicated roads for AVs reduces the overall costs and congestion up to 16%. However, CV detouring is inevitable at later network stages, increasing the total distance travelled (up to 8%) and congestion in the surroundings of AV subnetworks. Concerning the planning strategies, incremental planning is appropriate for starting in the initial stages and is the strategy that most tackles CV detouring. The hybrid or the long-term strategies are more suitable to be applied after a ratio of 50% AVs, and the hybrid planning is the strategy that most reduces delay.
Fungal Communities Associated with Siricid Wood Wasps: Focus on Sirex juvencus, Urocerus gigas, and Tremex fuscicornis
Authors: Marčiulynas Adas , Lynikienė Jūratė , Gedminas Artūras , Povilaitienė Aistė , Menkis Audrius
Published: January 2024

We investigated the diversity and occurrence of wood wasps in Lithuania and determined communities of associated fungi. Trapping of wood wasps resulted in three different species, including Sirex juvencus, Urocerus gigas, and Tremex fuscicornis. Fungal culturing from adult females of T. fuscicornis mainly resulted in fungi from the genera Penicillium and Trichoderma. High-throughput sequencing of ITS2 rDNA resulted in 59,797 high-quality fungal sequences, representing 127 fungal OTUs. There were 93 fungal OTUs detected in U. gigas, 66 in S. juvencus, and 10 in T. fuscicornis. The most common fungi were Fusarium sporotrichioides (63.1% of all fungal sequences), Amylostereum chailletii (14.9%), Penicillium crustosum (7.8%), Microascus sp. 2261_4 (5.0%), and Pithoascus ater (2.1%). Among these, only A. chailletii was found in all three insect species with the highest relative abundance in U. gigas (15.2%), followed by S. juvencus (7.7%), and the lowest in T. fuscicornis (0.3%) (p < 0.0003). Correspondence analysis of fungal communities showed a distant placement of different species of wood wasps, indicating that fungal communities in each of these were largely different. In conclusion, the study showed that the economically important tree pathogen A. chailletii was among the most common fungal OTUs associated with siricid wood wasps.
Particle Number Concentration and SEM-EDX Analyses of an Auxiliary Heating Device in Operation with Different Fossil and Renewable Fuel
Authors: Nagy Péter , Szabó Ádám István , Zsoldos Ibolya , Szabados György
Published: January 2024

Pollution from road vehicles enters the air environment from many sources. One such source could be if the vehicle is equipped with an auxiliary heater. They can be classified according to whether they work with diesel or gasoline and whether they heat water or air. The subject of our research series is an additional heating system that heats the air, the original fuel is gasoline. This device has been built up in a modern engine test bench, where the environmental parameters can be controlled. The length of the test cycle was chosen to be 30 min. The tested fuels were E10, E30, E100 and B7. A 30-min operating period has been chosen in the NORMAL operating mode of the device as a test cycle. The focus of the tests was particle number concentration and soot composition. The results of the particle number concentration showed that renewable fuel content significantly reduces the number concentration of the emitted particles (9.56 × 108 #/cycle for E10 vs. 1.65 × 108 #/cycle for E100), while B7 causes a significantly higher number of emissions than E10 (3.92 × 1010 #/cycle for B7). Based on the elemental analysis, most deposits are elemental carbon, but non-organic compounds are also present. Carbon (92.18 m/m% for E10), oxygen (6.34 m/m% for E10), fluorine (0.64 m/m% for E10), and zinc (0.56 m/m% for E10) have been found in the largest quantity of deposits taken form the combustion chamber.
Using Machine Learning Methodology to Model Nutrient Discharges from Ports: A Case Study of a Fertilizer Terminal
Authors: Lappalainen Suvi-Tuuli , Kotta Jonne , Tombak Mari-Liis , Tapaninen Ulla
Published: January 2024

Marine eutrophication is a pervasive and growing threat to global sustainability. Thereby, nutrient discharges to the marine environment should be reduced to a minimum. When fertilizers are loaded to the vessels in ports, a significant amount of nutrients are released into the sea, but so far these actions have received little attention. Here, we employed the Boosted Regression Trees modeling (BRT) to define the relationships between fertilizer loading, the loading area, rain intensity, nutrient discharge, and the marine environment, and then used the established relationships to predict the daily nutrient discharge due to fertilizer loading. The studied subject was a port in the Gulf of Finland, where significant amounts of both nitrogen and phosphorus are loaded to vessels. BRT models accounted for a significant proportion of the variability of nutrient discharge. As expected, the nutrient discharge increased with the number of fertilizers loaded and the intensity of rain. On the other hand, with the increasing loading area, the total nitrogen discharge increased, but the total phosphorus discharge decreased. The latter result may be due to the different characteristics of the loading areas of different terminals. The model predicted that at the studied port, the total nitrogen and phosphorus discharge to the marine environment due to fertilizer loading was 272,906 and 196 kg per year, respectively. Importantly, the developed model can be used to predict the nutrient loads for different future scenarios in order to propose the best mitigation methods for nutrient discharges to the sea.
Using Machine Learning to Predict Oil–Mineral Aggregates Formation
Authors: Zhong Xiaomei , Wu Yongsheng , Yu Jie , Liu Lei , Niu Haibo
Published: January 2024

The formation of oil–mineral aggregates (OMAs) is essential for understanding the behavior of oil spills in estuaries and coastal waters. We utilized statistical methods (screening design) to identify the most influential variables (seven factors in total) during OMA formation. Time was the most important factor, followed by temperature and oil/clay ratio. Moreover, machine learning was applied to predict the OMA median diameter (D50). Among the three tested algorithms, the Random Forest (RF) algorithm showed the highest accuracy, with a training R2 of 0.99 and testing R2 of 0.93. An open-source software tool that integrates the RF algorithm was developed, allowing users to easily estimate the OMA D50 based on input variables. The valuable results and the practical tool we have developed enhance the understanding and management of environmental impacts associated with oil spills.
Tax Tightrope: The Perils of Foreign Ownership, Executive Incentives and Transfer Pricing in Indonesian Banking
Authors: Putri Vidiyanna Rizal , Zakaria Nor Balkish , Said Jamaliah , Ghapar Farha , Anita Rizqa
Published: January 2024

Despite being a crucial source of funding for the government, tax revenue collection in Indonesia has yet to reach its ideal and satisfying level for the economy. Therefore, this study explores the impact of executive incentives, foreign ownership, and transfer pricing on tax avoidance. The conventional banks of Indonesia that were listed on the Indonesia Stock Exchange (IDX) between 2015 and 2019 are the subject of this study. This study employed a purposive selection technique, with a final sample of 17 banks chosen after screening to ensure they met the requirements of having foreign ownership and not having suffered losses during the study year. The results of this study show that while CEO incentives harm tax avoidance, foreign ownership has a beneficial effect. Furthermore, tax avoidance is not significantly impacted by transfer pricing. The findings of this investigation open the door for accountable authorities in the economy.
Dynamics of Built-Up Areas and Challenges of Planning and Development of Urban Zone of Greater Lomé in Togo, West Africa
Authors: Blakime Têtou-Houyo , Adjonou Kossi , Komi Kossi , Hlovor Atsu K. Dogbeda , Gbafa Kodjovi Senanou , Zoungrana Jean-Bosco Benewinde , Polorigni Botolisam , Kokou Kouami
Published: January 2024

The expansion of African cities leads to the occupation of peripheral urban areas without respecting planning rules. The Greater Lomé (Togo) is no exception to this phenomenon of high-speed horizontal spreading, which causes recurrent flooding. The objective of this research is to understand the spatio-temporal changes in the dynamics of built-up areas in Greater Lomé. The methodology used is based on the analysis of Landsat images from the years 2007, 2012, 2016, and 2020 coupled with direct field observations and a literature review. The results showed an increase in residential areas to the detriment of the other land use/cover types. Estimated at 15,481 ha in 2007, the built-up area reached 35,521 ha in 2020, an increase of 33% to the detriment of vegetation and cultivation areas. This increase was marked by constructions in the floodplain of the Zio River. The field surveys revealed an increase in the density of most of the agglomerations. From 1863 ha in 2007, they increased to 14,485 ha in 2020, an increase of 12,622 ha or approximately 33%. These results indicate that attention needs to be paid to both the planning and control of the development of spaces in the outlying areas of Greater Lomé.
Universal Jamming Gripper: Experimental Analysis on Envelope and Granular Materials
Authors: de Rodrigo Ignacio , Belart Jorge , Lopez-Lopez Alvaro J.
Published: January 2024

This article presents a materials optimization for the universal jamming gripper, one of the most versatile tools for robotic grasping. For this purpose, we analyze both the granular interior material and its surrounding deformable envelope. We combine four different granulate sizes (glass balls ranging from 0.2 to 1 mm) with four envelope materials (three silicones and latex), resulting in 16 prototype combinations. We use a tensile test machine to recreate the robot’s vertical movement in a real scenario situation. Thus, we can have precise control of the gripper’s immersion depth, forces, and displacements. Thanks to the tensile test, we extract the critical parameters to evaluate every material combination and the gripper’s performance. Therefore, we provide an experimental guide to selecting the right materials and rule out bad combinations for soft robots and specifically for the universal jamming gripper.
Existence and Stability Results for Differential Equations with a Variable-Order Generalized Proportional Caputo Fractional Derivative
Authors: O’Regan Donal , Agarwal Ravi P. , Hristova Snezhana , Abbas Mohamed I.
Published: January 2024

An initial value problem for a scalar nonlinear differential equation with a variable order for the generalized proportional Caputo fractional derivative is studied. We consider the case of a piecewise constant variable order of the fractional derivative. Since the order of the fractional integrals and derivatives depends on time, we will consider several different cases. The argument of the variable order could be equal to the current time or it could be equal to the variable of the integral determining the fractional derivative. We provide three different definitions of generalized proportional fractional integrals and Caputo-type derivatives, and the properties of the defined differentials/integrals are discussed and compared with what is known in the literature. Appropriate auxiliary systems with constant-order fractional derivatives are defined and used to construct solutions of the studied problem in the three cases of fractional derivatives. Existence and uniqueness are studied. Also, the Ulam-type stability is defined in the three cases, and sufficient conditions are obtained. The suggested approach is more broadly based, and the same methodology can be used in a number of additional issues.
A Novel Method for Medical Predictive Models in Small Data Using Out-of-Distribution Data and Transfer Learning
Authors: Jeong Inyong , Kim Yeongmin , Cho Nam-Jun , Gil Hyo-Wook , Lee Hwamin
Published: January 2024

Applying deep learning to medical research with limited data is challenging. This study focuses on addressing this difficulty through a case study, predicting acute respiratory failure (ARF) in patients with acute pesticide poisoning. Commonly, out-of-distribution (OOD) data are overlooked during model training in the medical field. Our approach integrates OOD data and transfer learning (TL) to enhance model performance with limited data. We fine-tuned a pre-trained multi-layer perceptron model using OOD data, outperforming baseline models. Shapley additive explanation (SHAP) values were employed for model interpretation, revealing the key factors associated with ARF. Our study is pioneering in applying OOD and TL techniques to electronic health records to achieve better model performance in scenarios with limited data. Our research highlights the potential benefits of using OOD data for initializing weights and demonstrates that TL can significantly improve model performance, even in medical data with limited samples. Our findings emphasize the significance of utilizing context-specific information in TL to achieve better results. Our work has practical implications for addressing challenges in rare diseases and other scenarios with limited data, thereby contributing to the development of machine-learning techniques within the medical field, especially regarding health inequities.
Normalized Error-Based PI Controller and Its Application to the DC–DC Buck Converter
Authors: Chincholkar Satyajit , Tariq Mohd , Poshtan Majid , Sharaf Mohamed
Published: January 2024

In this article, the structure of the normalized error-based proportional-integral (PI) controller is presented and its application to the DC–DC buck converter is discussed. The main motivation is to overcome the drawbacks of saturation and the limited range of controller gains offered by the traditional PI controller. Initially, the theoretical structure and advantages of an improved PI controller are shown. Next, the problem of regulation of the step-down DC–DC converter is addressed using the proposed controller. The objective is to keep the load voltage constant even when the converter parameters vary. The averaged state-space model of the converter is presented and a detailed stability analysis based on the Lypunov indirect method is carried out. The results show an improved range of controller parameters when the proposed controller is employed. Finally, some simulation results are shown to illustrate the effect of controller parameter variations on the output response. These results also verify the ability of the proposed controller to handle the changes in the load, input voltage, and reference voltage of the converter. Moreover, a comparative simulation study validates the superior transient response of the proposed normalized error-based PI controller over the traditional PI controller.
Guaranteed H∞ Performance of Switched Systems with State Delays: A Novel Low-Conservative Constrained Model Predictive Control Strategy
Authors: Hassan Yasser Falah , Zarkani Mahmood Khalid Hadi , Alali Mohammed Jasim , Daealhaq Haitham , Chaoui Hicham
Published: January 2024

In this paper, for the first time, a simultaneous design of a model predictive control plan and persistent dwell-time switching signal utilizing the conventional multiple Lyapunov–Krasovskii functional is proposed for linear delayed switched systems that are affected by physical constraints and exogenous disturbances. The conventional multiple Lyapunov–Krasovskii functional with a ‘jump high’ condition is used as a step forward to reduce the strictness of constraints on controller design compared with the switched Lyapunov–Krasovskii functional. However, a dwell-time constraint is inflicted on the switching signal by the ‘jump-high’ condition. Therefore, to decrease the dwell-time limit, the persistent dwell-time structure is used and compared with other structures. Also, a new online framework is proposed to reduce the number of constraints on controller design at each time step. Moreover, for the first time, exogenous disturbances are considered in the procedure of MPC design for delayed switched systems, and non-weighted H∞ performance is ensured. The simulation outcome demonstrates the great performance of the suggested plan and its ability to asymptotically stabilize the switched system.
Improvement of the Antioxidant and Antitumor Activities of Benzimidazole-Chitosan Quaternary Ammonium Salt on Drug Delivery Nanogels
Authors: Ma Bing , Li Qing , Zhang Jingjing , Mi Yingqi , Tan Wenqiang , Guo Zhanyong
Published: January 2024

The present study focused on the design and preparation of acid-responsive benzimidazole-chitosan quaternary ammonium salt (BIMIXHAC) nanogels for a controlled, slow-release of Doxorubicin HCl (DOX.HCl). The BIMIXHAC was crosslinked with sodium tripolyphosphate (TPP) using the ion crosslinking method. The method resulted in nanogels with low polydispersity index, small particle size, and positive zeta potential values, indicating the good stability of the nanogels. Compared to hydroxypropyl trimethyl ammonium chloride chitosan-Doxorubicin HCl-sodium tripolyphosphate (HACC-D-TPP) nanogel, the benzimidazole-chitosan quaternary ammonium salt-Doxorubicin HCl-sodium tripolyphosphate (BIMIXHAC-D-TPP) nanogel show higher drug encapsulation efficiency and loading capacity (BIMIXHAC-D-TPP 93.17 ± 0.27% and 31.17 ± 0.09%), with acid-responsive release profiles and accelerated release in vitro. The hydroxypropyl trimethyl ammonium chloride chitosan-sodium tripolyphosphate (HACC-TPP), and benzimidazole-chitosan quaternary ammonium salt-sodium tripolyphosphate (BIMIXHAC-TPP) nanogels demonstrated favorable antioxidant capability. The assay of cell viability, measured by the MTT assay, revealed that nanogels led to a significant reduction in the cell viability of two cancer cells: the human lung adenocarcinoma epithelial cell line (A549) and the human breast cancer cell line (MCF-7). Furthermore, the BIMIXHAC-D-TPP nanogel was 2.96 times less toxic than DOX.HCl to the mouse fibroblast cell line (L929). It was indicated that the BIMIXHAC-based nanogel with enhanced antioxidant and antitumor activities and acidic-responsive release could serve as a potential nanocarrier.
The Performance of Different Etchants on the Carbides of Ni600 and Ni625
Authors: Fang Ning , Zhou Ziyao , Britton Ben
Published: January 2024

Nickel-based alloys that contain chromium are widely used in corrosion-resistant applications in industry, but they are sensitive to the environment when the passive chromium oxide layer is damaged. In Ni600 and Ni625 alloys, precipitates can deplete the surface layer of chromium oxide. To better characterize and analyze the nickel alloy surfaces and their chromium carbides, chemical etching with different etchants and electrolytic etching were applied to sample surfaces. This paper revealed their efficacy in etching various carbides within the nickel alloys, and orange phases ranging from 2 to 20 μm in optical micrographs were identified as titanium-containing compounds. Carbides located on the grain boundaries were determined to be Cr23C6 and were surrounded by chromium-depleted zones. The findings and figures in this paper provide a more intuitive reference for future analysis of carbides and titanium nitrides, enhancing the understanding of their impact on the corrosion resistance of these alloys, which will not only contribute to the material science field but also aid in developing the Ni-based alloys for industrial applications.
Dysbiotic Vaginal Microbiota Induces Preterm Birth Cascade via Pathogenic Molecules in the Vagina
Authors: Ansari AbuZar , You Young-Ah , Lee Gain , Kim Soo Min , Park Sun Wha , Hur Young Min , Kim Young Ju
Published: January 2024

Dysbiotic vaginal microbiota (DVM) disturb the vaginal environment, including pH, metabolite, protein, and cytokine profiles. This study investigated the impact of DVM on the vaginal environment in 40 Korean pregnant women and identified predictable biomarkers of birth outcomes. Cervicovaginal fluid (CVF) samples were collected in the third trimester using vaginal swabs, examined for pH, and stored at −80 °C for further analysis. The samples were grouped as full-term (FTB, n = 20) and preterm (PTB, n = 20) births. The microbiota was profiled in the V1–V9 regions. The levels of targeted metabolites, TLR-4, and cytokines were determined. The pH of CVF from PTB (>4.5) was significantly higher than that of the CVF from FTB (>3.5) (p < 0.05). Neonatal gestational age at delivery, birth weight, and Apgar score differed significantly between groups. The relative abundances of beneficial Lactobacillus spp., such as Lactobacillus gasseri, Lactobacillus jensenii, and Bifidobacterium, were higher in FTB, whereas those of pathogenic Enterococcus faecalis, Staphylococcus, Prevotella, Ureaplasma parvum, and Corynebacterium spp. were higher in PTB. Acetate, methanol, TLR-4, and TNF-α levels were negatively correlated with gestational age at delivery and birth weight. Moreover, ethanol, methanol, TLR-4, IL-6, IL-1β, and TNF-α levels were positively correlated with succinate, acetate, acetoacetate, formate, and ammonia. Overall, DVM induces preterm birth via pathogenic molecules in the vagina.
Optimizing Optical Dielectrophoretic (ODEP) Performance: Position- and Size-Dependent Droplet Manipulation in an Open-Chamber Oil Medium
Authors: Islam Md , Park Sung-Yong
Published: January 2024

An optimization study is presented to enhance optical dielectrophoretic (ODEP) performance for effective manipulation of an oil-immersed droplet in the floating electrode optoelectronic tweezers (FEOET) device. This study focuses on understanding how the droplet’s position and size, relative to light illumination, affect the maximum ODEP force. Numerical simulations identified the characteristic length (Lc) of the electric field as a pivotal factor, representing the location of peak field strength. Utilizing 3D finite element simulations, the ODEP force is calculated through the Maxwell stress tensor by integrating the electric field strength over the droplet’s surface and then analyzed as a function of the droplet’s position and size normalized to Lc. Our findings reveal that the optimal position is xopt= Lc+ r, (with r being the droplet radius), while the optimal droplet size is ropt = 5Lc, maximizing light-induced field perturbation around the droplet. Experimental validations involving the tracking of droplet dynamics corroborated these findings. Especially, a droplet sized at r = 5Lc demonstrated the greatest optical actuation by performing the longest travel distance of 13.5 mm with its highest moving speed of 6.15 mm/s, when it was initially positioned at x0= Lc+ r = 6Lc from the light’s center. These results align well with our simulations, confirming the criticality of both the position (xopt) and size (ropt) for maximizing ODEP force. This study not only provides a deeper understanding of the position- and size-dependent parameters for effective droplet manipulation in FEOET systems, but also advances the development of low-cost, disposable, lab-on-a-chip (LOC) devices for multiplexed biological and biochemical analyses.
Editorial for the Special Issue on Microfluidic Device Fabrication and Cell Manipulation
Authors: Matsuura Koji
Published: January 2024

Microfluidic devices have been utilized for separation sciences, environmental sciences, food processing, drug delivery, bioimaging, diagnostics, and cell cultures [...]
Preparation and Properties of GO/ZnO/nHAp Composite Microsphere Bone Regeneration Material
Authors: Wu Jiang , Wang Chunmei , Zhang Shuangsheng , Zhang Ling , Hao Jingshun , Jia Zijian , Zheng Xiaomei , Lv Yuguang , Fu Shuang , Zhang Guoliang
Published: January 2024

The purpose of this study is to explore the possibility of using graphene–zinc oxide–hydroxyapatite (GO/ZnO/nHAp) composite microspheres as bone regeneration materials by making use of the complementary advantages of nanocomposites, so as to provide reference for the clinical application of preventing and solving bacterial infection after implantation of synthetic materials. Firstly, GO/ZnO composites and hydroxyapatite nanoparticles were synthesized using the hydrothermal method, and then GO/ZnO/nHAp composite microspheres were prepared via high-temperature sintering. The graphene–zinc oxide–calcium phosphate composite microspheres were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FE-SEM), X-ray photoelectron spectroscopy (XPS), energy dispersion spectroscopy (EDS), water contact angle measurement, degradation and pH determination, and differential thermal analysis (DiamondTG/DTA). The biocompatibility, osteogenic activity, and antibacterial activity of GO/ZnO/nHAp composite microspheres were further studied. The results of the cell experiment and antibacterial experiment showed that 0.5% and 1% GO-ZnO-nHAp composite microspheres not only had good biocompatibility and osteogenic ability but also inhibited Escherichia coli and Staphylococcus aureus by more than 45% and 70%. Therefore, GO/ZnO/nHAp composite microspheres have good physical and chemical properties and show good osteogenic induction and antibacterial activity, and this material has the possibility of being used as a bone regeneration material.
The Printability, Microstructure, and Mechanical Properties of Fe80−xMnxCo10Cr10 High-Entropy Alloys Fabricated by Laser Powder Bed Fusion Additive Manufacturing
Authors: Li Kai , Trofimov Vyacheslav , Han Changjun , Hu Gaoling , Dong Zhi , Zou Yujin , Wang Zaichi , Yan Fubao , Fu Zhiqiang , Yang Yongqiang
Published: January 2024

This work investigated the effect of Fe/Mn ratio on the microstructure and mechanical properties of non-equimolar Fe80−xMnxCo10Cr10 (x = 30% and 50%) high-entropy alloys (HEAs) fabricated by laser powder bed fusion (LPBF) additive manufacturing. Process optimization was conducted to achieve fully dense Fe30Mn50Co10Cr10 and Fe50Mn30Co10Cr10 HEAs using a volumetric energy density of 105.82 J·mm−3. The LPBF-printed Fe30Mn50Co10Cr10 HEA exhibited a single face-centered cubic (FCC) phase, while the Fe50Mn30Co10Cr10 HEA featured a hexagonal close-packed (HCP) phase within the FCC matrix. Notably, the fraction of HCP phase in the Fe50Mn30Co10Cr10 HEAs increased from 0.94 to 28.10%, with the deformation strain ranging from 0 to 20%. The single-phase Fe30Mn50Co10Cr10 HEA demonstrated a remarkable combination of high yield strength (580.65 MPa) and elongation (32.5%), which surpassed those achieved in the FeMnCoCr HEA system. Comparatively, the dual-phase Fe50Mn30Co10Cr10 HEA exhibited inferior yield strength (487.60 MPa) and elongation (22.3%). However, it displayed superior ultimate tensile strength (744.90 MPa) compared to that in the Fe30Mn50Co10Cr10 HEA (687.70 MPa). The presence of FCC/HCP interfaces obtained in the Fe50Mn30Co10Cr10 HEA resulted in stress concentration and crack expansion, thereby leading to reduced ductility but enhanced resistance against grain slip deformation. Consequently, these interfaces facilitated an earlier attainment of yield limit point and contributed to increased ultimate tensile strength in the Fe50Mn30Co10Cr10 HEA. These findings provide valuable insights into the microstructure evolution and mechanical behavior of LPBF-printed metastable FeMnCoCr HEAs.
Improving the Comprehension of Pathogenicity and Phylogeny in ‘Candidatus Phytoplasma meliae’ through Genome Characterization
Authors: Fernández Franco Daniel , Yan Xiao-Hua , Kuo Chih-Horng , Marcone Carmine , Conci Luis Rogelio
Published: January 2024

‘Candidatus Phytoplasma meliae’ is a pathogen associated with chinaberry yellowing disease, which has become a major phytosanitary problem for chinaberry forestry production in Argentina. Despite its economic impact, no genome information of this phytoplasma has been published, which has hindered its characterization at the genomic level. In this study, we used a metagenomics approach to analyze the draft genome of the ‘Ca. P. meliae’ strain ChTYXIII. The draft assembly consisted of twenty-one contigs with a total length of 751.949 bp, and annotation revealed 669 CDSs, 34 tRNAs, and 1 set of rRNA operons. The metabolic pathways analysis showed that ChTYXIII contains the complete core genes for glycolysis and a functional Sec system for protein translocation. Our phylogenomic analysis based on 133 single-copy genes and genome-to-genome metrics supports the classification as unique ‘Ca. P. species’ within the MPV clade. We also identified 31 putative effectors, including a homolog to SAP11 and others that have only been described in this pathogen. Our ortholog analysis revealed 37 PMU core genes in the genome of ‘Ca. P. meliae’ ChTYXIII, leading to the identification of 2 intact PMUs. Our work provides important genomic information for ‘Ca. P. meliae’ and others phytoplasmas for the 16SrXIII (MPV) group.
Geochemical Behavior of Shallow Buried Nodules from Clarion–Clipperton Fracture Zone in the East Pacific: A LA-ICP-MS Mapping Analysis Perspective
Authors: Fan Zedong , Li Xiaohu , Li Zhenggang , Ma Weilin , Zhu Zhimin , Li Jie , Wang Hao , Yang Kehong , Li Huaiming , Chu Fengyou , Dong Yanhui
Published: January 2024

The Clarion–Clipperton Fracture Zone of the east Pacific contains numerous shallow buried nodules that are in direct contact with pore water in sediment, providing a direct reflection of the interaction between nodules and sediment. However, research on the geochemical behavior of these shallow-buried nodules is limited. This study used laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), high-resolution transmission electron microscopy (HRTEM), and X-ray diffraction (XRD) to compare mineral and element distribution in shallow buried nodules with surface nodules. The shallow buried nodules are products of nodules entering the burial stage. In comparison to surface nodules, shallowly buried nodules develop a fourth oxidized-suboxic diagenetic growth layer after entering the burial stage, in addition to the three main growth inner layers (L1, L2, L3). We suggest that L4 is not influenced by the bottom water source and that the presence of todorokite and the high flux of Mn2+ in the sediment pore water compete with other metal elements to enter the lattice of manganate, resulting in significantly higher Mn, W, and Li contents in L4 compared to L2. However, the content of Ni, Mg, and other hydrogenetic elements is much lower in L4 compared to L2. We suggest that the instantaneous change in surface primary productivity results in a sudden shift in the redox environment of the upper sediment layer. This reaction leads to the reduction of solid-phase Mn, providing growth opportunities for the buried nodules. Simultaneously, this may also be the reason why the growth layer of the nodules is jointly controlled by the sedimentary processes of hydrogenetic, oxic diagenetic, and suboxic diagenetic processes.
Application and Development of Smart Thermally Conductive Fiber Materials
Authors: Sun Zhan , Yu Huitao , Feng Yiyu , Feng Wei
Published: January 2024

In recent years, with the rapid advancement in various high-tech technologies, efficient heat dissipation has become a key issue restricting the further development of high-power-density electronic devices and components. Concurrently, the demand for thermal comfort has increased; making effective personal thermal management a current research hotspot. There is a growing demand for thermally conductive materials that are diversified and specific. Therefore, smart thermally conductive fiber materials characterized by their high thermal conductivity and smart response properties have gained increasing attention. This review provides a comprehensive overview of emerging materials and approaches in the development of smart thermally conductive fiber materials. It categorizes them into composite thermally conductive fibers filled with high thermal conductivity fillers, electrically heated thermally conductive fiber materials, thermally radiative thermally conductive fiber materials, and phase change thermally conductive fiber materials. Finally, the challenges and opportunities faced by smart thermally conductive fiber materials are discussed and prospects for their future development are presented.
Variation of the Orientations of Organic Structure-Directing Agents inside the Channels of SCM-14 and SCM-15 Germanosilicates Obtained by Ab Initio Molecular Dynamic Simulations
Authors: Gramatikov Stoyan P. , Petkov Petko St. , Wang Zhendong , Yang Weimin , Vayssilov Georgi N.
Published: January 2024

We report ab initio molecular dynamic simulations of the organic structure-directing agent (OSDA) in the channels of SCM-14 and SCM-15 germanosilicates for models with different germanium distribution. Since OSDA was free to move inside the channels, independent of its initial orientation after the simulations in all structures the OSDA, protonated 4-pyrrolidinopyridine, is positioned almost perpendicular to the large channels of SCM-14. The structures obtained from the dynamic simulation are more stable by 157 to 331 kJ/mol than the structures obtained by initial geometry optimization. After simulations, the average distance between the N atom of the pyridine moiety of the OSDA and O from Ge-O-Ge is shorter by 0.2 Å than the same distance obtained from initial optimization. The stretching N-H frequencies in the IR spectra of the OSDA and other calculated vibrational frequencies are not characteristic of the orientation of the molecule and cannot be used to detect it.
Effect of Synchrotron X-ray Irradiation Time on the Particle Size and DFAFC Performance of Pd/CNT Catalysts
Authors: Tsou Sheng-Jung , Mazurkiewicz-Pawlicka Marta , Chiou Yuh-Jing , Lin Chung-Kwei
Published: January 2024

Global energy sources are limited, and energy requirements are ever-increasing due to the demand for developments in human life and technology. The environmentally friendly direct formic acid fuel cell (DFAFC) is an attractive electronic device due to its clean energy. In a DFAFC, an anodic catalyst plays an important role concerning the oxidation pathway and activity. In the present study, palladium (Pd) was synthesized by synchrotron X-ray photoreduction using various irradiation times (0.5–4 min) to control the particle size. An acid-treated carbon nanotube (A-CNT) was used as the template for Pd deposition. The A-CNT and Pd/A-CNT were examined using scanning electron microscopy, X-ray diffraction, Raman spectroscopy, and transmission electron microscopy to reveal the microstructural characteristics. Electrochemical evaluation, electrocatalytic activity, and the DFAFC performance of so-obtained Pd/A-CNT catalysts were investigated. The experiment’s results showed that the Pd/A-CNT-2 (i.e., synchrotron photoreduction for 2 min) underwent a direct formic acid oxidation pathway and possessed a high ECSA value of 62.59 m2/gPd and superior electrocatalytic activity of 417.7 mA/mgPd. In a single DFAFC examination, the anodic Pd/A-CNT-2 catalyst had a power density of 106.2 mW/mgPd and a relatively long lifetime of 2.91 h. Pd/A-CNT-2 anodic catalysts synthesized by surfactant-free synchrotron X-ray photoreduction with a rapid processing time (2 min) are potential candidates for DFAFC applications.